medica scientific case study

• Publications
• Conferences & Events
• Professional Learning
• Science Standards
• Awards & Competitions
• Instructional Materials
• Free Resources
• For Preservice Teachers

NCCSTS Case Collection

• Science and STEM Education Jobs
• Interactive eBooks+
• Digital Catalog
• Regional Product Representatives
• e-Newsletters
• Browse All Titles
• Bestselling Books
• Latest Books
• Popular Book Series
• Submit Book Proposal
• Web Seminars
• National Conference • New Orleans 24
• Leaders Institute • New Orleans 24
• National Conference • Philadelphia 25
• Exhibits & Sponsorship
• Submit a Proposal
• Conference Reviewers
• Past Conferences
• Latest Resources
• Professional Learning Units & Courses
• For Districts
• Online Course Providers
• Schools & Districts
• College Professors & Students
• The Standards
• Teachers and Admin
• eCYBERMISSION
• Toshiba/NSTA ExploraVision
• Junior Science & Humanities Symposium
• Teaching Awards
• Climate Change
• Earth & Space Science
• New Science Teachers
• Early Childhood
• Middle School
• High School
• Postsecondary
• Informal Education
• Journal Articles
• Lesson Plans
• e-newsletters
• Science & Children
• Science Scope
• The Science Teacher
• Journal of College Sci. Teaching
• Connected Science Learning
• NSTA Reports
• Next-Gen Navigator
• Science Update
• Teacher Tip Tuesday
• Trans. Sci. Learning

MyNSTA Community

• My Collections

Case Study Listserv

Permissions & Guidelines

Submit a Case Study

Resources & Publications

Enrich your students’ educational experience with case-based teaching

The NCCSTS Case Collection, created and curated by the National Center for Case Study Teaching in Science, on behalf of the University at Buffalo, contains over a thousand peer-reviewed case studies on a variety of topics in all areas of science.

Cases (only) are freely accessible; subscription is required for access to teaching notes and answer keys.

Subscribe Today

Browse Case Studies

Latest Case Studies

Development of the NCCSTS Case Collection was originally funded by major grants to the University at Buffalo from the National Science Foundation , The Pew Charitable Trusts , and the U.S. Department of Education .

Unfortunately we don't fully support your browser. If you have the option to, please upgrade to a newer version or use Mozilla Firefox , Microsoft Edge , Google Chrome , or Safari 14 or newer. If you are unable to, and need support, please send us your feedback .

We'd appreciate your feedback. Tell us what you think!   opens in new tab/window

The do’s and don’ts of writing and publishing case reports

March 6, 2023 | 5 min read

Lessons from a recent Researcher Academy webinar

As a method of documenting a single clinical observation, case reports offer timely and valuable information, especially with regards to rare diseases. They show medical professionals how fellow practitioners have acted in similar situations and thus aid in the decision-making process by sharing best practices. Not only do they significantly contribute to the knowledge pool, they also help add to a researcher’s own publication portfolio. Producing a good case report requires much more than just an interesting case, however.

To assist researchers with this task, Professors Oliver Kurzai and Adilia Warris, editors of the journal  Medical Mycology Case Reports   opens in new tab/window  shared tips on writing high impact case reports in the latest Researcher Academy  webinar   opens in new tab/window . We are pleased to share here some quick do’s and don’ts from the webinar.

Tell a story

The best way to compose a case report is to tell a story. This can be accomplished by arranging the events in chronological order, being specific about your differential diagnostic considerations, elucidating the arguments for your clinical decision-making process, and following up to round off the story neatly. This will create an imaginary journey where your readers can follow every development of the case and understand why you have performed specific tests or made certain decisions during a particular treatment.

Get the details right

Make sure to describe the relevant signs and symptoms which have resulted in the differential diagnosis, both positive and negative in order to provide readers with the context in which you have made your decisions. You can also include in your case reports descriptions of actual values for blood test results, detailed dosages for medications prescribed or other variables that should be taken into account with respect to the outcome of the situation.

Employ pictures/figures where relevant

A picture, as they say, is worth a thousand words, especially for case reports where findings can be clearly and efficiently illustrated via images. Don’t make use of pictures without justification, however – do so only if they have a function. For example, macroscopic and microscopic images of a newly-identified causative microorganism are an essential whereas a picture of the model you have clearly explained elsewhere in the text may be overkill.

Formulate short and sharp titles

The title is the first selling point of your case report. Therefore, you would want it to be interesting and something that grasps the reader’s attention. Make sure you phrase it concisely, but still in an eye-catching way. Take a look at the examples shared by the speakers below.

An OK title: " Treatment of cerebral mucormycosis with drug therapy alone: a case report"

Versus a compelling title:  "Successful outcome of cerebral mucormycosis with drug therapy alone"

Secure written consent from patient

Due to its nature of being a detailed description of an individual patient’s clinical presentation and therapy, a case report almost always contains information that could be traced back to the individual in question. Thus, a written, informed consent from the patient is a key requirement for the publication. Keep in mind that your patient is your partner in completing a case report, therefore make sure to discuss the report proactively with them including being explicit about any potential images that you are going to use, especially if they show or could identify the patient.

Don’t write your case report before doing your homework

If your case is not unique or interesting enough, there is a high chance that it will not be published. Even when your case is unique but is not well-documented or misses some crucial diagnostic elements, the same outcome might still ensue. This is not only a waste of your precious time but also a discouragement which might prevent you from producing more case reports in the future. To avoid this outcome, make sure to carry out careful research  before  writing your case reports. Make sure it meets all necessary characteristics and requirements before spending a lot of time and effort on the writing part.

Don’t publish a case report without the patient’s consent

As explained above, informed patient consent is mandatory for the publication of your case reports. Ignoring this requirement can result in a rejection for your work and worse, ruin your relationship and reputation with patients. However, there is an exception for publishing a case report without patient consent when the benefit of publication toward to society outweighs potential harm for individual. This happens when the case report contains an extremely important public health message but impossible to obtain informed consent despite all efforts as the patient has died, for example.

Don’t forget, moreover that clinical practitioners are not required to, and should not reveal personal patient information to a journal that is not relevant to the case.

Don’t include everything

“Less is more” goes the popular adage… It is not recommended to provide an extensive overview or discuss every single aspect of the patient’s disease in the introduction and conclusion. This will only serve to disengage readers and will distract them from the main ideas you want to communicate. If you want to give a focused introduction and discussion, make sure your case report mentions only the key messages and information related and relevant to these points.

To learn more about other insightful tips on how to write influential case reports and more importantly to get them published, you can watch the full webinar recording at the  Researcher Academy   opens in new tab/window . If, after doing so you still have unresolved questions, why not post in the  Researcher Academy Mendeley group   opens in new tab/window , where the team will endeavour to find expert answers for you.

Contributor

Marketing and Communications Intern

Authors' Update - keeping journal authors in touch with industry developments, support and training

• - Google Chrome

Intended for healthcare professionals

• My email alerts
• BMA member login
• Username * Password * Forgot your log in details? Need to activate BMA Member Log In Log in via OpenAthens Log in via your institution

Search form

• Advanced search
• Search responses
• Search blogs
• Writing a case report...

Writing a case report in 10 steps

• Related content
• Peer review
• Victoria Stokes , foundation year 2 doctor, trauma and orthopaedics, Basildon Hospital ,
• Caroline Fertleman , paediatrics consultant, The Whittington Hospital NHS Trust
• victoria.stokes1{at}nhs.net

Victoria Stokes and Caroline Fertleman explain how to turn an interesting case or unusual presentation into an educational report

It is common practice in medicine that when we come across an interesting case with an unusual presentation or a surprise twist, we must tell the rest of the medical world. This is how we continue our lifelong learning and aid faster diagnosis and treatment for patients.

It usually falls to the junior to write up the case, so here are a few simple tips to get you started.

First steps

Begin by sitting down with your medical team to discuss the interesting aspects of the case and the learning points to highlight. Ideally, a registrar or middle grade will mentor you and give you guidance. Another junior doctor or medical student may also be keen to be involved. Allocate jobs to split the workload, set a deadline and work timeframe, and discuss the order in which the authors will be listed. All listed authors should contribute substantially, with the person doing most of the work put first and the guarantor (usually the most senior team member) at the end.

Getting consent

Gain permission and written consent to write up the case from the patient or parents, if your patient is a child, and keep a copy because you will need it later for submission to journals.

Information gathering

Gather all the information from the medical notes and the hospital’s electronic systems, including copies of blood results and imaging, as medical notes often disappear when the patient is discharged and are notoriously difficult to find again. Remember to anonymise the data according to your local hospital policy.

Write up the case emphasising the interesting points of the presentation, investigations leading to diagnosis, and management of the disease/pathology. Get input on the case from all members of the team, highlighting their involvement. Also include the prognosis of the patient, if known, as the reader will want to know the outcome.

Coming up with a title

Discuss a title with your supervisor and other members of the team, as this provides the focus for your article. The title should be concise and interesting but should also enable people to find it in medical literature search engines. Also think about how you will present your case study—for example, a poster presentation or scientific paper—and consider potential journals or conferences, as you may need to write in a particular style or format.

Background research

Research the disease/pathology that is the focus of your article and write a background paragraph or two, highlighting the relevance of your case report in relation to this. If you are struggling, seek the opinion of a specialist who may know of relevant articles or texts. Another good resource is your hospital library, where staff are often more than happy to help with literature searches.

How your case is different

Move on to explore how the case presented differently to the admitting team. Alternatively, if your report is focused on management, explore the difficulties the team came across and alternative options for treatment.

Finish by explaining why your case report adds to the medical literature and highlight any learning points.

Writing an abstract

The abstract should be no longer than 100-200 words and should highlight all your key points concisely. This can be harder than writing the full article and needs special care as it will be used to judge whether your case is accepted for presentation or publication.

Discuss with your supervisor or team about options for presenting or publishing your case report. At the very least, you should present your article locally within a departmental or team meeting or at a hospital grand round. Well done!

Competing interests: We have read and understood BMJ’s policy on declaration of interests and declare that we have no competing interests.

Journal of Medical Case Reports

In the era of evidence-based practice, we need practice-based evidence. The basis of this evidence is the detailed information from the case reports of individual people which informs both our clinical research and our daily clinical care. Each case report published in this journal adds valuable new information to our medical knowledge. Prof Michael Kidd AO, Editor-in- Chief

Join the Editorial Board

We are recruiting Associate Editors to join our Editorial Board. Learn more about the role and how to apply  here !

• Meet the Editors

Get to know the Editors behind  Journal of Medical Case Reports !

megaflopp / Getty Images / iStock

Requirements for case reports submitted to JMCR

•  Patient ethnicity must be included in the Abstract under the Case Presentation section.

•  Consent for publication is a mandatory journal requirement for all case reports . Written informed consent for publication must be obtained from the patient (or their parent or legal guardian in the case of children under 18, or from the next of kin if the patient has died). For more information, please see our editorial policies .

Report of the Month

Superior mesenteric vein thrombosis due to covid-19 vaccination.

Vaccines have made a significant contribute to sowing the spread of the COVID-19 infection. However, side effects of the vaccination are beginning to appear, and one of which, thrombosis, is a particular problem as it can cuase serious complications. While cases of splanchnic venous thrombosis (SVT) after ChAdOx1 nCoV-19 vaccinations have been reported, cases of SVT mRNA-1273 vaccines are rare. 

In this case report, clinicians describe a patient presenting with superior mesentric vein thrombosis following a COVID-19 vaccination, and examine the relationship between the mRNA-1273 vaccines and intestinal ischemia. 

• Most accessed

Infective endocarditis with metastatic infections in a renal transplant recipient: a case report

Authors: Isabella Asamoah, Nicholas Mawuena Joppa, Vincent Boima, Edward Kwakyi, Stefan Adomako and Dwomoa Adu

Bilateral tuberculosis psoas abscess in a human immunodeficiency virus-positive patient: a case report

Authors: A. A. Olasinde, J. B. Munihire, M. Mugenyi, F. T. Kasereka, O. Adetan and J. K. Bankole

Enterobius vermicularis (pinworm) infestation mimicking acute appendicitis in two children from Palestine: a case report

Authors: Issam Jawabreh, Ahmad Amro, Kifaya Azmi, Hamza Batran, Ziad Abdeen and Omar Hamarsheh

Spontaneous hepatic hemorrhage as presentation of metastasized papillary thyroid carcinoma: a case report

Authors: Jacob Thomasson, Bodil Andersson, Lo Hallin Thompson and Caroline Williamsson

Colonoscopy diagnosis of recurrent abdominal pain in a 4-year-old boy with intestinal duplication cyst involving colon, appendix, and ileum: a case report

Authors: Faling Chen and Jiangbin Liu

Most recent articles RSS

View all articles

An itchy erythematous papular skin rash as a possible early sign of COVID-19: a case report

Authors: Alice Serafini, Peter Konstantin Kurotschka, Mariabeatrice Bertolani and Silvia Riccomi

Red ear syndrome precipitated by a dietary trigger: a case report

Authors: Chung Chi Chan and Susmita Ghosh

How to choose the best journal for your case report

Authors: Richard A. Rison, Jennifer Kelly Shepphird and Michael R. Kidd

The Erratum to this article has been published in Journal of Medical Case Reports 2017 11 :287

COVID-19 with repeated positive test results for SARS-CoV-2 by PCR and then negative test results twice during intensive care: a case report

Authors: Masafumi Kanamoto, Masaru Tobe, Tomonori Takazawa and Shigeru Saito

Transient congenital hyperinsulinism and hemolytic disease of a newborn despite rhesus D prophylaxis: a case report

Authors: Sandra Simony Tornoe Riis, Marianne Hoerby Joergensen, Kristina Fruerlund Rasmussen, Steffen Husby, Jane Preuss Hasselby, Lise Borgwardt, Klaus Brusgaard, Christina Ringmann Fagerberg and Henrik Thybo Christesen

Most accessed articles RSS

A Guide to Writing and Using Case Reports

This thematic series, published in 2016, provides a valuable resource for clinicians who are considered producing a case report. It comprises of a special editorial series of guides on writing, reviewing and using case reports. 

Aims and scope

Journal of Medical Case Reports will consider any original case report that expands the field of general medical knowledge, and original research relating to case reports.

Case reports should show one of the following:

• Unreported or unusual side effects or adverse interactions involving medications
• Unexpected or unusual presentations of a disease
• New associations or variations in disease processes
• Presentations, diagnoses and/or management of new and emerging diseases
• An unexpected association between diseases or symptoms
• An unexpected event in the course of observing or treating a patient
• Findings that shed new light on the possible pathogenesis of a disease or an adverse effect

Suitable research articles include but are not limited to: N of 1 trials, meta-analyses of published case reports, research addressing the use of case reports and the prevalence or importance of case reporting in the medical literature and retrospective studies that include case-specific information (age, sex and ethnicity) for all patients.

Article accesses

Throughout 2022, articles were accessed from the journal website more than 4.17   million times; an average of over 11 ,400  accesses per day.

Latest Tweets

Your browser needs to have JavaScript enabled to view this timeline

Peer Review Mentoring Scheme

The Editors at Journal of Medical Case Reports endorse peer review mentoring of early career researchers. 

If you are a senior researcher or professor and supervise an early career researcher with the appropriate expertise, we invite you to co-write and mentor them through the peer review process. Find out how to express your interest in the scheme  here .

Call for Papers

The Journal of Medical Case Reports  is calling for submissions to our Collection on  COVID-19 – a look at the past, present and future of the pandemic . Guest Edited by Dr. Jean Karl Soler, The Family Practice Malta, Malta

• Editorial Board
• Manuscript editing services
• Instructions for Editors
• Sign up for article alerts and news from this journal

Annual Journal Metrics

Citation Impact 2023 Journal Impact Factor: 0.9 5-year Journal Impact Factor: N/A Source Normalized Impact per Paper (SNIP): 0.591 SCImago Journal Rank (SJR): 0.304

Speed 2023 Submission to first editorial decision (median days): 33 Submission to acceptance (median days): 148

Usage 2023 Downloads: 4,048,208 Altmetric mentions: 2,745

• More about our metrics

• Follow us on Twitter

ISSN: 1752-1947

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

799k Accesses

1122 Citations

41 Altmetric

Metrics details

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Peer Review reports

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar  

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article   Google Scholar  

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article   PubMed   Google Scholar  

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed   PubMed Central   Google Scholar  

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article   PubMed Central   Google Scholar  

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS   PubMed   PubMed Central   Google Scholar  

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article   PubMed   PubMed Central   Google Scholar  

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article   CAS   PubMed   Google Scholar  

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book   Google Scholar  

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

Pre-publication history

The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1471-2288/11/100/prepub

Download references

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

Author information

Authors and affiliations.

Division of Primary Care, The University of Nottingham, Nottingham, UK

Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Kathrin Cresswell, Ann Robertson & Aziz Sheikh

School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Sarah Crowe .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article.

Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

Download citation

Received : 29 November 2010

Accepted : 27 June 2011

Published : 27 June 2011

DOI : https://doi.org/10.1186/1471-2288-11-100

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Case Study Approach
• Electronic Health Record System
• Case Study Design
• Case Study Site
• Case Study Report

BMC Medical Research Methodology

ISSN: 1471-2288

• General enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

The importance of case reports in advancing scientific knowledge of rare diseases

Affiliation.

• 1 Department of Pediatrics, The University of Utah, Salt Lake City, UT 84108, USA. [email protected]
• PMID: 20824440
• DOI: 10.1007/978-90-481-9485-8_5

Case reports are defined as the scientific documentation of a single clinical observation and have a time-honored and rich tradition in medicine and scientific publication. Case reports represent a relevant, timely, and important study design in advancing medical scientific knowledge especially of rare diseases. While there are clear limitations to the methodology of case studies in determination of treatment and establishment of new tests, the observation of a single patient can add to our understanding of etiology, pathogenesis, natural history, and treatment of particularly rare diseases, and to the training of potential junior investigators. In recent years this class of scientific publication has come under scrutiny and disfavor among some in the medical scientific publication community and case studies are frequently relegated to the lowest rung of the hierarchy of study design. In this chapter the author will review and summarize the debate around the scientific publication of case reports in the context of the study of rare diseases and will present a taxonomy that ideally will encourage further dialogue on the topic. Future research on the importance of case reports in advancing knowledge of rare diseases is recommended.

PubMed Disclaimer

Similar articles

• [The importance of case reports in current pediatric endocrinology and metabolism literature--the analysis of publications indexed in Medline in the years 2004-2009]. Kuchar E. Kuchar E. Pediatr Endocrinol Diabetes Metab. 2010;16(2):119-22. Pediatr Endocrinol Diabetes Metab. 2010. PMID: 20813090 Review. Polish.
• Are medical breakthroughs declining - The importance of case reports? Mishra S. Mishra S. Indian Heart J. 2015 Dec;67 Suppl 3(Suppl 3):S1-3. doi: 10.1016/j.ihj.2016.01.005. Indian Heart J. 2015. PMID: 26995410 Free PMC article.
• A report on case reports. Gopikrishna V. Gopikrishna V. J Conserv Dent. 2010 Oct;13(4):265-71. doi: 10.4103/0972-0707.73375. J Conserv Dent. 2010. PMID: 21217956 Free PMC article.
• Significance of case reports in the advancement of medical scientific knowledge. Carey JC. Carey JC. Am J Med Genet A. 2006 Oct 1;140(19):2131-4. doi: 10.1002/ajmg.a.31449. Am J Med Genet A. 2006. PMID: 16964619
• [Scientific publishing in the journal Nuclear Medicine]. Lerch H, Jigalin A. Lerch H, et al. Nuklearmedizin. 2002;41(4):171-7. Nuklearmedizin. 2002. PMID: 12224400 Review. German.
• Are case reports valuable? Exploring their role in evidence based medicine and patient care. Suvvari TK. Suvvari TK. World J Clin Cases. 2024 Aug 26;12(24):5452-5455. doi: 10.12998/wjcc.v12.i24.5452. World J Clin Cases. 2024. PMID: 39188604 Free PMC article.
• Laryngeal features in Lipoid proteinosis: a systematic review and meta-analysis of individual participant data. Cocchi C, Milanese A, Abdul-Messie L, Vestri AR, Longo L. Cocchi C, et al. Eur Arch Otorhinolaryngol. 2024 Sep;281(9):4555-4564. doi: 10.1007/s00405-024-08713-x. Epub 2024 May 7. Eur Arch Otorhinolaryngol. 2024. PMID: 38713291 Review.
• How to Overcome the Barriers Behind Writing Case Reports for Beginners and Young General Physicians. Ishizuka K, Yamashita S, Mine Y, Yamamoto Y, Kojima H, Someko H, Miyagami T. Ishizuka K, et al. Int J Gen Med. 2024 Apr 29;17:1723-1727. doi: 10.2147/IJGM.S459810. eCollection 2024. Int J Gen Med. 2024. PMID: 38706748 Free PMC article.
• Writing Case Reports Can Improve Seven Components in Clinical Reasoning. Nishizawa T, Ishizuka K, Otsuka Y, Nakanishi T, Kawashima A, Miyagami T, Yamashita S. Nishizawa T, et al. Int Med Case Rep J. 2024 Mar 21;17:195-200. doi: 10.2147/IMCRJ.S449310. eCollection 2024. Int Med Case Rep J. 2024. PMID: 38533427 Free PMC article.
• Editorial: Case reports in schizophrenia and psychotic disorders. Tusconi M, Nibbio G, Gupta R, Carr E. Tusconi M, et al. Front Psychiatry. 2023 Sep 13;14:1282780. doi: 10.3389/fpsyt.2023.1282780. eCollection 2023. Front Psychiatry. 2023. PMID: 37779634 Free PMC article. No abstract available.

Publication types

• Search in MeSH

Related information

Linkout - more resources, full text sources.

• MedlinePlus Health Information
• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Advertisement

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

• Survey and State of the Art
• Open access
• Published: 03 February 2023
• Volume 9 , pages 4705–4731, ( 2023 )

Cite this article

You have full access to this open access article

• A. H. Alamoodi 1 ,
• B. B. Zaidan 2 ,
• O. S. Albahri 3 ,
• Salem Garfan 4 ,
• Ibraheem Y. Y. Ahmaro 5 ,
• R. T. Mohammed 6 ,
• A. A. Zaidan 7 ,
• Amelia Ritahani Ismail 8 ,
• A. S. Albahri 9 ,
• Fayiz Momani 10 ,
• Mohammed S. Al-Samarraay 4 ,
• Ali Najm Jasim 11 &
• R.Q.Malik 12  

4160 Accesses

19 Citations

1 Altmetric

Explore all metrics

When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic’s main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of ( n  = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis ( n  = 6), (2) safety ( n  = 11), (3) hospital ( n  = 8), (4) treatment ( n  = 4), and (5) review ( n  = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID‐19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.

Similar content being viewed by others

The role of artificial intelligence in healthcare: a structured literature review

Trends on Decision Support Systems: A Bibliometric Review

A Guide to an Iterative Approach to Model-Based Decision Making in Health and Medicine: An Iterative Decision-Making Framework

Explore related subjects.

• Artificial Intelligence
• Medical Ethics

Avoid common mistakes on your manuscript.

Introduction

The earliest large-scale pandemic witnessed by people who may still be alive today was the Spanish flu (during World War 2) [ 1 ]. Since then, the preparation for pandemics has gained increased attention from researchers, governments, and decision makers [ 2 ]. However, when COVID-19 started spreading, humans knew that beyond any doubt that the preparations were not up to the event [ 3 ]. Tens of millions of people lost their jobs, and the world witnessed global financial crises, millions of death cases, and slow economic and health-system recovery [ 4 ]. The results of COVID-19 pandemic are different decisions, including long and/or long lockdowns [ 5 ], borders closing [ 6 ], quarantines [ 7 ], months/years of mask policy [ 8 ], offer financial aids [ 9 ], imposing vaccine policy [ 10 ], and many other decisions. They are not pre-planned for pandemic cases but have been decided during the evaluation of health and economic system by decision makers. Since then, researchers from all scientific disciplines have exerted immense effort in their respective areas of specializations [ 11 ]. Doctors and medical practitioners are not the only heroes during the pandemic; all researchers who have utilized their academic disciplines to provide assistance are also heroes [ 12 ]. Given that COVID-19 has affected many domains, particularly healthcare (HC), and left a knock-on effect on diagnoses and treatments [ 13 ], among other challenges, [ 14 ], people have become concerned with the future and strength of medical institutions should a similar pandemic hit us again in the future [ 15 ]. The World Health Organization (WHO) claims that evaluating and understanding pandemic-associated factors is crucial [ 16 ]. Globally, COVID-19 is acknowledged to have altered many aspects of daily human life, ranging from the medical area [ 17 ] to the social [ 18 ], economic [ 19 ], technological [ 20 ], and patient-related fields [ 21 ]. Additionally, COVID-19 has significantly impacted academics, specifically in terms of scientific studies on the different COVID-19 cases and factors [ 22 ]. Nevertheless, scientific research on COVID-19 related context can be turned into valuable insights to assist in the curb against the pandemics, and among the variable examples in that regard is the role of decision support systems, and others [ 23 ]. The involvement of expert systems includes optimization techniques [ 24 ] (to optimize limited resources during pandemics), artificial intelligence (AI; to predicting or analyzing different pandemics situations) [ 25 ], and decision making (DM; to make the best decision among several available options or analyzing different decisions) [ 26 ]. This involvement can help in better preparing against emerging epidemics. Technological advances, particularly those associated with AI and decision science, have relatively contributed in addressing the pandemic [ 27 ]. AI is one of the most emergent technologies, particularly when incorporated it to medicine-related decisions to fight COVID-19 [ 28 , 29 , 30 ]. Whether used for detection, control or any other purposes, technological advances have been assessed against this pandemic from different viewpoints [ 31 ]. Another associated emerging technology is the DM algorithm [ 32 ], which present various potentials and other views. Capacity evaluation of contributions for COVID-19 using multicriterion decision analysis (MCDA) techniques is extensively used to reveal the relationship among the evaluation criteria and select other alternative cases [ 33 ].

Multicriterion DM (MCDM) is considered among the most utilized tools in various COVID-19 related areas. MCDM can assist in providing different benefits in eliminating COVID-19 conditions and infected patients’ concerns [ 34 ]. Additionally, it can help in developing proper decision regimens, prevention strategies, and drug and vaccine development with precise judgment. Academic literature indicates that MCDM is utilized during the COVID-19 pandemic in various cases and aspects, particularly in terms of case studies or method enhancement. Case studies discuss various studies, in which MCDM was used in such areas as medical decision assistance and economic and financial aspects. Method enhancement refers to researchers pursuing theoretical MCDM enhancements and using enhanced methods in COVID-19 case studies. Nevertheless, additional investigation should be conducted in reviewing all MCDM and COVID-19 studies in terms of medical applications and identifying potential future research gaps. To the best of the authors’ knowledge, most MCDM and COVID-19-related studies have primarily present the role of MCDM in specific case studies, and no detailed reviews of medicine-related research have been conducted. Accordingly, focus must be directed on addressing current gaps based on the challenge of real treatment distribution and appropriate methodologies must be used in the future. The present study aimed to analyze the MCDM and COVID-19 medicine-related studies, present the current challenges and gaps, and propose a detailed methodology for future results. The contributions of this study are as follows.

A comprehensive review and analysis of MCDM and COVID-19-related medicine case studies are conducted to classify academic literature into four categories: diagnosis, safety, hospital, and treatment.

A bibliographic analysis was presented in the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship.

Different challenges, motivations and recommendations for COVID‐19 cases under MCDM theory are discussed.

New emerging gaps are identified and a solution with detailed methodology is proposed.

Systematic Literature Review (SLR) Protocol

This study is conducted using a systematic literature review (SLR) approach to help thoroughly understand the research topic and supplement subsequent investigations with extensive data [ 11 ]. Compared with traditional review methods, SLR is a well-structured procedure capable of improving research synthesis by identifying relevant papers based on selected parameters. SLR is also a cutting-edge method applicable to a wide variety of research domains and scientific disciplines. It entails several key steps, including scope identification, search-mechanism development, study selection and extraction, and information synthesis. Given the advantages of SLR, it is adopted in this research to study MCDM utilization in medical settings during the COVID-19 pandemic. The following subsections elaborate on the SLR subprocesses.

Information source

This study collected information based on the strategically search method following the SLR and meta-analysis (PRISMA) phases. To collect information, five scientific database search engines are utilized to search, filter, extract, and draft this survey: (1) ScienceDirect, which contains wide high-impact studies in various domains; (2) Web of Science, which includes numerous scientific research publications in different fields; (3) IEEE Xplore, which provides access to numerous scientific studies from multidisciplinary technologies in numerous domains; and (4) Scopus. The selected databases are considered most suitable and adequate for this review owing to their scientific soundness and academic resilience by including various SLR publications in high-impact scientific journals.

Search strategy

The search was conducted on 28 June 2020 and updated on August 2022. The most recent studies are included by performing another search in August 2022 in the advanced search boxes of the aforementioned databases. Boolean operators (e.g., OR and AND) are utilized for the search to combine the different synonyms with the two groups of keywords in the process. In searching and filtration, different types of publications, such as conference papers, research and review articles, are selected.

Study selection

The study selection procedure is performed through three steps, as presented in Fig.  1 . First, all articles found in the search are collected initially and scanned thereafter to remove duplicates. The initial number of collected articles is 1402, 87 of which are duplicates. Second, the titles and abstracts of the extracted articles are scanned based on our inclusion and exclusion criteria to identify the relevant articles and be included in the final round. Third, full-text reading is conducted for each article that matches our inclusion criteria to extract valuable information and be analyzed for the review. Accordingly, 1104 articles not matching our inclusion criteria and are excluded. The final set of relevant articles for this review comprises 35 articles.

SLR protocol

Inclusion and exclusion criteria

We define a set of inclusion and exclusion criteria to identify the related articles during the study selection. Articles are included if they are research or review articles, published in the English language, and discuss the utilization of MCDM techniques under the medical field during the COVID-19 pandemic. By contrast, articles are excluded if any of the preceding criteria is not identified.

Discussion flow

The process of this systematic review begins with the standard protocol items. Afterwards, the main layouts of this work are presented, showing how the flow of the discussion is presented (Fig.  2 ).

As shown in Fig.  2 , the flow starts with a taxonomy analysis of all the MCDM medical-related research. Afterwards, a discussion is presented to present the main highlights, including challenges faced in previous works, motivations and recommendations. All these three aspects are utilized in defining the current research gap. Accordingly, the research gap is presented in two stages; the first to discuss the problem formulation, and the second to discuss the proposed solution.

Comprehensive taxonomy

While scanning literature, articles are grouped in accordance with their medical perspectives. Given that this paper is an SLR, which combines decision science represented by MCDM and the medical applications of COVID-19, five main categories in the form of taxonomy are represented. The first category discusses how MCDM is integrated in such areas as COVID-19 diagnosis, whereas the second category discusses the safety aspect. The third category called “hospital” primarily discusses patients’ admission to hospitals and their prioritization during the COVID-19 pandemic. The fourth category discusses treatment through prescribed medicine and plasma transfusion. The last category is called “reviews” and primarily discusses and presents other SLR or reviews discussing MCDM and COVID-19 studies. At the end of the section, a critical point of view presents the differences of this SLR with that in previous research published. The design of the taxonomy in this form has been agreed upon among the authors and in consideration of their main observations of literature. Therefore, this presentation of the taxonomy enables a more comprehensive understanding of the topic, as shown in Fig.  3 .

Taxonomy categorization

The first category has two main subcategories: (1) research discussing diagnosis through computerized and hospital-based tests and (2) studies related to safety measures, such as regional assessment, masks and sanitizer. Two main themes are observed. The first by [ 35 ] utilizes MCDM in identifying key indicators from initial blood routine test results to predict COVID-19. The technique for order of preference by similarity to ideal solution (TOPSIS) and machine learning (ML) classifiers are subsequently used to further select effective indicators from patients’ initial blood-test results, which are later used in the prediction. TOPSIS is also used with the best–worst method (BWM) in Ref. [ 36 ], in which an MCDM model is constructed to distinguish COVID-19 from four other viral chest infections in an uncertain environment by utilizing the viruses’ primary symptoms and CT scans. The authors re-use TOPSIS in Ref. [ 37 ], in which a spherical intelligent fuzzy-decision model is developed to diagnose COVID-19 and control emergency situations to choose the best path to overcome this deadly disease. Authors in Ref. [ 38 ] used complex fuzzy (CF) sets and developed an MCDM Dombi operations-supported model for diagnosing COVID-19. Another CF set called m-polar neutrosophic set is utilized to diagnose COVID-19 in Ref. [ 39 ]. Lastly, [ 40 ] used the TOPSIS and entropy approaches in discussing an MCDM methodology for the problem of evaluation and benchmarking of COVID diagnosis ML models.

In the safety subcategory, four main safety aspects are discussed linking MCDM in medical settings with regional assessment, sanitizers, mask selection, and vaccine. For regional assessment, [ 41 ] presented a comparative research among well-known MCDM methods, including TOPSIS, VIKOR, and complex proportional assessment. A total of 100 world regions are utilized to evaluate and analyze the safety levels for COVID-19 in these regions. Other remaining studies in the safety subcategory includes Ref. [ 42 ], which presents a new MCDM approach based on a Pythagorean fuzzy soft-set environment. The approach presents its capability in dealing with unsatisfactory data, ambiguity, and inconsistency presented in the MCDM context. The aforementioned research is used to select effective hand sanitizers during the COVID-19 pandemic, and the approach is compared with others in terms of effectiveness. Two other studies in this category have focused solely on the selection of antivirus masks during the COVID-19 pandemic. The first study is Ref. [ 43 ], the main aim of which is maximizing the usage of anti-virus masks while using the MCDM approach presented over a spherical normal fuzzy (SpNoF) set. The second research is Ref. [ 44 ], which presents the same application over q-rung orthopair uncertain linguistic sets. Four topics are discussed for the vaccine. The first topic is vaccine accessibility, discussed by [ 45 ] concerning vaccination centers, particularly in the case of disasters and pandemics (e.g., COVID-19). For the second topic, Ref. [ 46 ] discussed the issue of vaccine distribution using AHP and TOPSIS for COVID-19 vaccine alternatives. The authors use the MCDM approaches, and their findings suggest that HC personnel, people with pre-existing medical conditions, the elderly, essential employees, and pregnant and breastfeeding mothers are the most prioritized groups to receive the vaccines first. The next three studies utilize MCDM methodologies, including fuzzy-weighted zero-inconsistency (FWZIC) and fuzzy decision by opinion score method (FDOSM) for prioritizing COVID-19 vaccine dose recipients. The first attempt is conducted using Pythagorean fuzzy set [ 47 ], followed by T-spherical fuzzy environment [ 48 ] and q-rung orthopair fuzzy set (q-ROFS) [ 49 ]. The topic on vaccine willingness is presented in Ref. [ 50 ], which states that vaccination willingness is a significant concern. In this context, AHP is used as an MCDM strategy to ascertain the public’s willingness to receive COVID-19 vaccines. These findings suggest that individual choice, vaccine origin, adjusting to change, and perceived barriers to vaccination are the primary determinants of the willingness to receive COVID-19 vaccines. The most recent research presented in the vaccine category is Ref. [ 51 ], which uses q-ROFSs and VIKOR for applications in mass-vaccination campaigns in the COVID-19 context.

The hospital category discusses academic literature focusing on the use of MCDM in medical settings for COVID-19 in terms of (1) hospital selection and admission enabled by MCDM in various settings, (2) hospital services and (3) patient prioritization. For hospital selection and admission, a total of ( n  = 3) related studies are reported. The first study [ 52 ] utilizes the MCDM approach with the use of the BWM method in choosing the right place to build temporary hospitals as one of the most important and urgent measures for pandemic response. Meanwhile, Ref. [ 53 ] develops an emergency MCDM decision-support model based on spherical hesitant fuzzy for patient care and admission scheduling (PCAS). Lastly, selection and admission research by [ 54 ] elaborates on how the pandemic has resulted in an intense flow of patients to hospitals, particularly intensive care units (ICUs). This situation presents a challenge in admission decisions, in which MCDM is introduced to address the aforementioned challenge by prioritizing the admission criteria using AHP. Thereafter, a multiobjective optimization approach is used to rank COVID-19 patients. The following theme reports on hospital services regarding their quality and preparedness. Two main studies are presented. First, Ref. [ 55 ] studies prioritization factors contributing to hospitals’ quality of service from the viewpoint of patients and their companions during the COVID-19 pandemic. Accordingly, a hybrid MCDM approach is used in the process of using fuzzy AHP and PROMETHEE for hospitals ranking under normal conditions and during the pandemic. Second, a hospital services study used three MCDM methodologies, namely, FAHP, fuzzy DM trial and evaluation laboratory (FDEMATEL), and TOPSIS. A previous study [ 56 ] has evaluated and ranked the disaster preparedness of hospitals. The next topic discusses MCDM utilization in hospital settings during the COVID-19 pandemic for patient prioritization-related research. Three studies are presented. First, Ref. [ 57 ] used TOPSIS in patient prioritization while using multilaboratory criteria and patient data set, particularly for asymptomatic COVID-19 carriers. Second, Ref. [ 58 ] conducts patient prioritization based on biological laboratory examination criteria and COVID-19 patients’ list. The two MCDM techniques, namely, AHP and VIKOR, are used in the process. Lastly, Ref. [ 59 ] utilizes MCDM in medical settings in prioritizing non-critical COVID-19 patients in HC settings with limited resources.

The two main topics discussed for treatment-related studies are medicine and plasma. The first topic discusses medicine treatment for COVID-19 through two studies. First, Ref. [ 60 ] develops an MCDM approach extended over hesitant fuzzy sets to treat mild COVID-19 symptoms. The study is primarily for drug selection for COVID-19, and demonstrated practicability and efficacy in real-life applications. Second, Ref. [ 61 ] presents a close case study for medicine selection for patients with mild COVID-19 symptoms. The authors clarify the usage of the MULTIMOORA method because it is specific with the peculiarities of three subordinate models. The final topic in the treatment section discusses utilizing plasma in the COVID-19 and MCDM contexts. First, Ref. [ 62 ] suggests that patients recovering from COVID-19 have antibodies circulating in their blood, which, if given to deteriorating patients, may conceivably assist in enhancing their immune system. Thus, a hybrid methodology proposes to utilize ML and unique MCDM methodologies to present a rescue framework for the transfusion of the best convalescent plasma (CP) to the most critically ill patients with COVID-19 based on biological needs. Second, Ref. [ 63 ] provides CP to the most vulnerable patients, preventing the virus from spreading and healing those infected. The distinction between this effort and others is that the former is recommended on the basis of a centralized/decentralized telemedicine environment to provide CP from eligible donors to patients who are most in need.

This category discussed the review of related research in this taxonomy section in relation to MCDM studies related to medicine. Three studies are presented. First, Ref. [ 64 ] presents a systematic review for detection and classification of COVID-19 medical images in terms of evaluation and benchmarking. The review also proposes a detailed MCDM methodology for evaluating and benchmarking AI techniques used in all classification tasks of COVID-19 medical images. This method serves as a future direction on the basis of the integrated AHP and VIKOR methods. Second, Ref. [ 65 ] discusses the utilization of MCDM in the fight against COVID-19 in various applications, including medical, social, and technological. Accordingly, the authors perform interesting patterns of analysis that can assist future studies in the area, including MCDM-COVID-19 challenges, contributions, and bibliographic analysis. Lastly, Ref. [ 66 ] discussed the MCDM utilization for treating COVID-10, with theoretical analysis discussing all aspects in applying MCDM in COVID-19-related studies. Several interesting topics covered in this paper include standardizing the assessment criteria, applying MCDM theory to rank and weigh alternative evaluation criteria, normalizing data utilized in the study, MCDM theory contexts, and selecting experts and validation methodology for effective MCDM theory. The authors conclude with a suggested future direction to provide scholars and the broader community with an overview of the current state of MCDM assessment and development methodologies that can be used to harness MCDM potentials in combating COVID-19. By recognizing the preceding medical cases, none of them are clearly presented in the manner by which this study is formed. The first review [ 64 ] is concerned only with the identification and detection part, and MCDM is part of the entire process. However, it included others such as ML, and is concerned only with medical image, evaluation, and benchmarking. For the second review [ 65 ], MCDM is reviewed in relation to numerous cases, among them is the medical one. However, as the authors conduct their research, detailed explanation reflecting a real case-study challenge with the proposed methodology is not presented, which is the main focus of the current study. In Ref. [ 66 ], they are concerned with the theoretical development of MCDM in various COVID-19 cases. However, a detailed medical discussion is not presented, let alone a real challenge concerning medical case studies of treatment by using the proposed methodology, which is also the main discussion and idea of the current review.

Bibliometric analysis

The rapid increase in publications and ongoing research has increased the challenge of keeping up with empirical contributions and enormous research streams. Hence, accumulating decisive evidence from previous studies is becoming increasingly complicated. Accordingly, the SLRs aim to summarize the results of literature, formulate problems, and propose solutions accordingly. The reviews also provide compilation of literature results, broadening the knowledge base, identifying theoretical, practical, and methodological gaps, and enhancing the research plan. However, the issue of reliability and objectivity in systematic reviews remains a challenge that needs to be resolved. To address the issue of reliability and transparency, numerous ongoing studies suggest quantitative and qualitative approaches that enhance systematic reviews by reorganizing the findings of literature. Among the quantitative and qualitative tools, bibliometrics based on R-tool and VOSviewer is considered the most reliable and transparent method [ 109 ]. The bibliometric method provides organized results, summarizes research trends, explores prolific countries, institutions, and authors, thereby presenting the big picture of extant research. Bibliometrics based on R-tool and VOSviewer is not cumbersome for researchers to use, does not require professional, and is open source to perform comprehensive bibliometric analyzes. Furthermore, this study adopted bibliometrics based on R-tool and VOSviewer to explore annual scientific production, country scientific production, co-occurrence, and co-authorship.

Annual scientific production

The scientific production of medical case studies of COVID-19 based on the MCDM approach is developing at a rapid pace. To identify the applicable methodological results, the annual scientific production aims to describe the structure of scientific disciplines and research developed over time. Figure  4 shows the historical development of publications for medical case studies of COVID-19 through the MCDM approach.

As illustrated in Fig.  4 , the most productive category over the years is safety. COVID-19 created a danger to human life and caused a complete closure of many countries. Various academics and practitioners have focused on the topic of safety to mitigate the risk of COVID-19. The years 2021 and 2022 have seen an increase in academic publications that develop medical protective tools such as masks and gloves. However, hospitals and health centers faced the challenge of the enormous increase in the number of patients, especially in 2021. Consequently, the scientific production of the hospital category for the years 2020 and 2021 rose to improve the level of quality and treat patients according to the priorities of the health condition. At the beginning of the epidemic’s spread, the interest in identifying methods of diagnosing the virus and controlling emergency situations increased. Such increase in the academic scientific of the diagnosis category was high in the year 2020. Moreover, the risks of the spread of the COVID-19 pandemic have overwhelmed academics and practitioners to mitigate the pandemic. In the year 2021, attempts to eliminate the epidemic increased. Hence, the scientific publications in 2021 for the treatment category were high. For the review category, the attempts were minor for the last three years. Thus, the current study pursues to address the literature gap by providing a comprehensive and insightful view of ongoing and future research.

Country scientific production

COVID-19 has affected all countries. Governments have responded in various ways to mitigate the threat of such a disease to life. Country scientific production describes the scientific publications of medical case studies of COVID-19 through the MCDM approach at the country level. Figure  5 demonstrates country scientific production to provide an insight for practitioners and academics regarding the most effective category in crises and pandemics.

The safety category is receiving extensive attention from literature in all countries because countries and organizations have implemented work from home to reduce the risks of interaction and spread of COVID-19 infection. Bibliometric analysis of literature confirms that Malaysia is the most productive country for studies using MCDM with medical aspects in the safety, review, and treatment category, followed by China for the treatment, safety, review, and diagnosis category. Nevertheless, Turkey is interested in improving the quality of health services and is the highest contribution at the level of the hospital category. Analysis of country scientific production delivers practitioners with insight into identifying the most interesting countries in improving HC services and developing medical protection tools. Moreover, governments can benefit from the success stories of countries to overcome future crises. Identification of practitioners for countries that have failed in facing the epidemic at the level of treatment, safety, review, diagnosis, and hospital category contributes to addressing the most important challenges and issues that the medical system suffers from in such countries. Country scientific production also provides guidance for academics to address theoretical and practical gaps in literature on the basis of country application.

Co-occurrence

Co-occurrence is a methodology containing common keywords introduced by literature. Co-occurrence analysis maps the conceptual structure of a field. Such an analysis is referred to as a semantic network. Hence, academics and practitioners identify the relationship of the main topic with the emerging subfields. This analysis depicts the frequency of occurrence of keywords. Figure  6 presents co-occurrence analysis for the diagnosis, safety, hospital, treatment, and review category.

For the diagnosis category, ML and DM are the most frequent topics. Increasing the thickness of the line separating two keywords indicates the close relationship between the keywords of diagnosis category. For safety categories, previous literature has investigated the impact of COVID-19 on gender and age based on the use of the MCDM approach. However, the review category indicates that literature is interested in reviewing the mechanism of application of MCDM methods with COVID-19. Additionally, the vaccine is the most important common issue addressed in the safety category. Co-occurrence analysis indicates DM is a vital method to prioritize COVID-19 patients and distributing plasma for them. By capturing the co-occurrence of keywords for medical case studies of COVID-19, practitioners and academics can use information networks to facilitate efforts to reorganize the available information and findings. Furthermore, stakeholders could identify the intellectual base of MCDM approach applied with medical case studies of COVID-19.

Co-authorship

Co-authorship networks are defined as scientific publications by a group of scholars. Co-authorship analysis contributes to identifying networks of cooperation among countries, institutions, and authors. Such an analysis determines the number of papers written by researchers, identify the patterns of cooperation between researchers, and explore the number of co-authors. Figure  7 shows the results of a co-authorship analysis of medical case studies of COVID-19.

The node size represents the number of articles, the nodes represent authors, and the lines show the pattern of co-authorship. For the diagnosis category, scientific cooperation exists among Iraq, Malaysia, Spain, and Saudi Arabia to mitigate the risks of COVID-19 and benefit from the experiences of European and Asian governments. However, the hospital category does not witness scientific cooperation owing to the different ways of admitting, exiting, and treating COVID-19 patients between countries. Scientific cooperation exists among Malaysia, Iraq, Australia, and Canada at the level of review, safety, and treatment categories. In this context, Malaysia and Iraq represent the main players in international cooperation, followed by Australia and Canada, in descending order. Identification of scientific cooperation regarding the application of the MCDM approach with medical aspects enables practitioners to maximize the outcomes of resources and contributes to maximizing impact for academics by increasing citations. Scientific cooperation contributes to increasing the learning of new skills and increasing the chances of solving problems on a strong scientific basis. However, the co-authorship analysis confirms the weakness of scientific cooperation in applying the MCDM approach with medical aspects of COVID-19. Moreover, weak scientific cooperation reduces the chances of career expansion and science promotion.

Challenges refer to issues and gaps identified and encountered by researchers from previous scientific studies, addressing them openly for new potential research in the area and promoting future ideas. For this review, challenges are discussed in relation to a disease (i.e., COVID-19) and MCDM techniques, as shown in Fig.  8 . The details are as follows.

Main challenges

Disease-related issues

The COVID-19 pandemic has posed a serious threat to society and the economy, eventually exploding into a public health crisis. An increasing number of academics have noted data and understanding gaps in relation to how the COVID-19 pandemic spreads within and between communities, as well as its potential effects on vulnerable and general populations [ 67 ]. Furthermore, COVID-19’s rapid spread globally poses a significant threat to public safety and potential therapy. Some COVID-19 symptoms are similar to those of other viral chest disorders, resulting in difficult creation of models for effective COVID-19 detection [ 36 ]. The proliferation of COVID-19 has likewise resulted in extensive economic and social damages. COVID-19 affects the majority of population groups, but it is most dangerous to the elderly, people with disabilities, those living in poverty, homeless people, refugees, migrants, youth, and indigenous peoples [ 51 ]. Evidently, addressing this challenge appropriately constitutes substantial difficulties. Meanwhile, identifying mild from serious health cases is a difficult but crucial task, particularly when the medical sector offers HC services, especially because these services incorporates treatment aspects [ 58 ]. The management of COVID-19 spread in crisis situations is challenge [ 37 ]. Additionally, national and global health organizations (e.g., WHO, UNICEF, and CDC) have consistently recommended national governments to use various measures to curb the spread of COVID-19 and devise effective treatment protocols and strategies [ 68 , 69 ]. However, national treatment and immunization programs must be trained to elucidate global guidelines and make decisions best suited to their context.

Healthcare concerns

The spread of COVID-19 has prompted governments to establish national policies aimed at mitigating the disease’s burden on HC systems [ 70 ] and developing proper treatment strategies. The scarcity of resources and endless demands restrict HC services to be supplied to all individuals in need. This situation became increasingly evident during the COVID-19 pandemic [ 71 ]. The COVID-19 pandemic has placed a significant burden on global HC systems, with developing countries bearing the brunt of the damage owing to their underdeveloped HC infrastructure and limited financial resources [ 72 ]. Hospitals’ emergency reaction to HC management lacks sufficient systems for providing HC to COVID-19 patients [ 53 ]. Additionally, the COVID-19 pandemic has strained emergency response systems globally, resulting in the breakdown of health systems, law enforcement, and first responders [ 73 ], as well as decentralized hospital administration factors, such as scalability and management challenges for concurrently prioritizing COVID-19 patients and donors [ 63 ]. The preceding aspects further pose a significant threat to the health and lives of people globally, thereby providing exceptional strain to medical systems [ 35 ]. Hence, building the resilience of HC systems has become essential.

Preparedness of hospital concerns

As the number of COVID-19 patients increases, several health structures are impacted, including the requirement for additional beds and ventilators. Hospitals must anticipate the impact of COVID-19 on all sectors and work collaboratively to share knowledge and resources to guarantee optimal care. This situation contributes to good administration by ensuring the inclusion and care of all HC workers and organization of contact with the general public [ 53 ]. Similarly, a dearth of adequate hospital beds and ICU facilities for severely ill patients have been important issues [ 59 ]. In prioritizing ICU admissions for particular patients, guidelines based on a scientific approach should be developed to determine which COVID-19 patients should be prioritized for ICU admission or treatment in emergency or resource-constrained situations [ 54 ]. Consequently, the demand for operating room efficiency has a significant impact on hospitals’ financial and final ethical outcomes. Another crucial issue is that with the unexpected occurrence of natural and man-made disasters globally, the relevance of hospital preparation becomes evident. Notably, hospital preparation is the first point of contact for individuals seeking HC services. Hence, determining the level of disaster readiness of hospitals is a critical problem [ 56 ]. Additionally, no specific guidelines have been formulated for prioritizing COVID-19 patients for hospital admission in situations with significant bed shortage [ 59 ]. Accordingly, selecting the best location for temporary hospitals is one of the most crucial and urgent pandemic-response measures [ 52 ].

Treatment concerns

Patients with COVID-19 exhibit wide-ranging symptoms during the course of their illness, thereby creating an uncertain situation, in which doctors are unsure of the most effective medication. The medical community remains concerned with the absence of a standard therapeutic protocol leading to variability in the management of COVID-19 patients [ 74 ]. Accordingly, a realistic way to increase the efficiency of treatment and optimize the allocation of medical resources is needed. Another issue is determining the best way to distribute vaccines on a local and global scale. The issues of procurement, storage and distribution of vaccines and other therapeutic alternatives must be regulated. Additionally, rules should be formulated and a timeframe must be provided for assigning the generally accessible COVID-19 therapy choices for distinct priority groups.

Vaccine concerns

COVID-19 vaccines are supposed to protect humans against COVID-19. However, many individuals are on the fence regarding whether or not they should be vaccinated [ 50 ]. Considerably limited public trust in vaccines, resulting in poor vaccination uptake, continues to be a critical issue for European Union policy makers [ 75 ]. Serious side effects have not been encountered in COVID-19 vaccine clinical trials and current vaccination endeavors. Post-vaccination side effects are often mild [ 76 ]. Clinical signs are not observed in either clinical trials or current immunization undertakings. Post-vaccination side effects are often minor [ 77 ]. However, vaccination research should be conducted to address low vaccine confidence and uptake.

Technique issues

From a theoretical standpoint, the increase in MCDM in addressing COVID-19 requires deeper examination to fulfill the main characteristic factors that fit in merging MCDM and COVID-19 [ 66 ]. HC restriction has consistently been present and unavoidable, and the HC industry is impacted by numerous COVID-19 patients. A solution is urgently required to prevent the danger of deteriorating patient health in terms of prioritizing based on their health conditions. Owing to (1) numerous biological laboratory screening criteria, (2) criteria weight, and (3) trade-offs between criteria, prioritized COVID-19 patients considered a complicated MCDA issue [ 58 ]. Additionally, prioritizing access to care treatment during extremely difficult times is needed [ 59 ]. Determining priorities is a difficult and seemingly unsolvable problem because it includes balancing efficiency with equality across several different criteria [ 71 ].

Vaccine effectiveness concerns

Various vaccines have been developed and are currently being evaluated by health authorities globally. However, numerous countries, particularly those with minimal resources, have significant difficulties in ensuring widespread access to vaccines [ 68 ]. Several firms are also attempting to correctly distribute vaccines and treatments, but it is bound to be difficult to implement for approximately 8 billion people. Consequently, competition has emerged, and competitiveness is becoming considerably fierce. Hence, governments must firstly select priority groups for providing COVID-19 vaccine doses [ 46 ]. The final solution to halt the COVID-19 pandemic is the development of effective vaccines. Experts and governments agree that vaccines may not be ready for another 2 years, but this situation does not imply that it cannot become available earlier [ 36 ]. Accordingly, an efficient and immediate protection technique must be developed before vaccines are produced.

Vaccine-distribution concerns

The difficulty of the MCDM issue is highlighted in the distribution of COVID-19 vaccines, so strong and durable MCDM approaches are needed [ 48 ]. Governments must adopt a priority system for distributing COVID-19 vaccine doses throughout the populace and prevent their random distribution [ 48 ]. Authorities must create a prioritized approach for allocating COVID-19 vaccine doses to people and avoid randomization of vaccine distribution [ 48 ]. Evidently, choosing the best vaccines and other treatments for target populations is critical [ 76 ].

Location selection concerns

MCDM is infrequently applied in analyzing government intervention strategies against COVID-19. Furthermore, MCDM difficulties are exacerbated by imprecision and unpredictability [ 78 ]. Government solutions are evaluated using several contradictory criteria, including cost effectiveness, simplicity of implementation and efficacy in limiting COVID-19 transmission [ 67 ]. Additionally, selective state action during the COVID-19 pandemic is an MCDM issue in a hazy and unclear environment. Governments and medical communities shift their priorities in response to emerging difficulties, and the success of interventions implemented in various countries [ 78 ]. Site selection of vaccination centers is a major challenge for the health sector [ 45 ]. For the hospital-site selection issue, various MCDM studies have been conducted but none of them has proposed an all-encompassing set of criteria for addressing this issue [ 52 ]. Inadequate sensitivity in clinical diagnostic procedures is one of the primary causes of the rapid spread of COVID-19 in communities [ 64 ]. Therefore, effective and immediate methods for hospital location selection are needed.

Motivations

Reviewing and analyzing MCDM and COVID-19 motivate researchers, decision makers, and governments because of the evident and compelling benefits. This section is organized into five categories: COVID-19 diagnosis, DM, HC resources, vaccines/treatment and COVID-19 detection. Motivations in relation to the COVID-19 pandemic are discussed (Fig.  9 ).

Main motivations

COVID-19 diagnosis significance

Scientists have been investigating various strategies to combat the COVID-19 pandemic since the first cases were discovered among the general population. Accordingly, they have identified the critical roles played by numerous scientific fields throughout this pandemic. MCDM has been implemented extensively in our everyday lives in many ways with several successes stories to aid in analyzing complicated problems and delivering an accurate DM process [ 66 ]. MCDM is used to solve health problems faced by workers in various environments [ 79 ]. It assists governments in developing the optimal strategy because a better grasp of methods is essential in battling the pandemic [ 78 ]. MCDM may also be used to assess and benchmark the various diagnostic models for COVID-19 in terms of the evaluation criteria [ 40 ]. The purpose of a diagnosis assistant is to classify patients as confirmed, suspected or suspicion of COVID-19 infection. A diagnosis assistant also classifies patients as mild, moderate, severe or critical [ 80 ].

Decision-making significance

For medical specialists, MCDM may be utilized to resolve and mitigate the aforementioned complexities because it is a verified and robust scientific process that produces exact and effective outcomes in important situations of MCDM [ 74 ]. Additionally, it assists decision makers in achieving an effective outcome by enabling the evaluation of all possible elements affecting the choice issue [ 41 , 81 ]. Prioritizing options for complete catastrophe preparation and response is rendered easier with MCDM use [ 78 ]. A DM tool has been established to address the issue of defining priorities among patients contending for minimal health facilities [ 71 , 82 ]. Consequently, providing decision assistance may aid in improving decision quality, reliability, and clarity.

Healthcare-resource significance

MCDM approaches have been proven effective in numerous HC data-focused applications [ 36 ]. A resilient HC sector can address any type of emergencies in a country [ 70 , 72 ]. It is capable of identifying priority locations, comparing populations, and providing alternatives for government agencies to respond. Hospitals are among the most significant HC facilities because it is the primary provider of HC services, particularly during a pandemic, such as COVID-19 [ 55 ]. Hospitals often lack medical equipment and manpower [ 53 , 56 ], so identifying hospitals with a poor degree of preparation is critical for disaster preparedness planning. Additionally, hospitals should plan for physical infrastructure and resource allocation because they are the only locations that can offer immediate treatment in the event of a crisis [ 56 ]. Undoubtedly, hospitals can mitigate the harm caused by disasters by arranging hospital resources (e.g., treatment areas, equipment and employees) and determining their disaster readiness levels. MCDM methods may aid in addressing hospital-site selection because to their intrinsic benefits than other OR methodologies, such as their capacity to include qualitative criteria together with quantitative ones [ 52 ]. Beneficial PCAS that is successful and precise has a good impact on hospitals in terms of service availability, management quality, affordability and social impact, among others [ 53 ]. Prioritizing infected individuals for treatment and distinguishing their important health issues are advantageous and could aid hospitalization worries in detecting health disorders [ 57 ]. By implementing an active risk management strategy, illnesses may be prevented and beneficial organizational improvements can be facilitated [ 82 ], thereby decreasing mortality and hospitalization costs.

Vaccines and treatment significance

Vaccines are a significantly effective means to protect people against deadly diseases and save millions of lives. Public-health officials and multiple countries have shown positive indications on COVID-19 vaccines and treatment, which are intended to protect the public against severe COVID-19 [ 50 ]. Various researchers have been working on finding an effective single course of COVID-19 treatment [ 74 ]. Medical professionals and pharmacologists are also working relentlessly to identify and prescribe a standardized and effective course of treatment for COVID-19 patients [ 74 ]. Similarly, COVID-19 vaccine studies have been conducted by numerous governments/manufacturers using various methods [ 45 ]. Numerous health organizations have been working with biopharmaceutical companies to accelerate the process of finding a drug or vaccine for novel coronavirus [ 68 ]. WHO and other governing bodies have formulated guidelines and remedial activities to minimize the spread of COVID-19. As the death ratio caused by COVID-19 increases, the most suitable vaccine for people should be selected [ 76 ], and the best approaches for distributing such vaccines and other treatment forms must also be established [ 77 ]. Mass vaccination campaigns (MVCs) are implemented to control and remove infectious diseases in large populations [ 45 ]. MVC implementation encourages the prevention and control from vaccine-preventable diseases and high-impact diseases [ 51 ].

COVID-19 detection significance

The use of AI and ML is expanding in different fields, specifically in medical detection. AI has been widely used to gain more accurate detection results and decrease the burden on HC system. It can decrease the decision time associated with the detection process of traditional methods [ 40 , 64 ]. Using MCDM can also assist researchers to leverage lessons learned through investigating past widespread disease events to predict who may be infected, where vaccination and treatment effort should be prioritized and how to limit the spread of infectious diseases in the future [ 67 ]. Meanwhile, awareness on COVID-19 and its early detection and proper treatment can help contain the disease.

Recommendations

Literature provides numerous recommendations, and components of these recommendations are technical related and the others are related to medical cases. This section presents the main recommendations in literature as seen in Fig.  10 .

Main recommendations

Environments and methods recommendations

Various studies are recommended to be extended to other MCDM methods [ 53 , 54 , 55 , 68 , 71 , 79 , 80 , 83 , 84 ]. For example, a recommendation is to deal with the issue of uncertainty in HC setting prioritization using fuzzy, intuitionistic fuzzy, hesitant fuzzy, neutrosophic fuzzy, or probabilistic information [ 71 ]. Moreover, a study for evaluating strategies on enhancing HC resilience to combat COVID-19 recommended to be extended to other MCDM methods (e.g., AHP, TOPSIS and VIKOR) [ 39 , 72 ]. The FDOSM and FWZIC approaches are recommended to be employed in the different COVID-19 cases owing to their promising results in terms of accuracy and consistency of their weighting and ranking [ 66 ]. Fuzzy MCDM techniques are recommended to be utilized to overcome the uncertainty problem for COVID-19 cast studies [ 41 ]. Different studies have recommended to be extended to other fuzzy environments [ 62 , 73 ], such as interval-valued spherical fuzzy environments [ 37 ]. Others recommended hesitant fuzzy sets [ 37 ]. Additionally, a study on COVID-19 has recommended to be extended to probabilistic linguistic term, bipolar CF, q-rung orthopair fuzzy and neutrosophic sets [ 60 ]. Neutrosophic, intuitionistic and interval-valued and interval type-2 hesitant sets are recommended to overcome the uncertainty limitation [ 48 ]. T-spherical fuzzy, plithogenic hypersoft and complex neutrosophic hesitant fuzzy sets are recommended as well [ 44 ].

Different case studies recommendations

Literature recommends the proposed methods to be applied in different fields [ 39 , 53 ], such as medical diagnosis [ 37 ] and temporary hospital locations during the COVID-19 pandemic [ 52 ]. Furthermore, a method is proposed for selecting anti-virus mask to extend their proposed method into other HC problems, such as brain hemorrhage, disease recognition and medical diagnosis [ 43 ].

Different operators and structure recommendations

Literature recommends the use of different DM techniques operators [ 39 ] and structures [ 39 ]. A study recommended different structures to be established under the Pythagorean fuzzy sets, such as ordered, algebraic and topological structures [ 42 ]. Moreover, the fuzzy symmetry concept is recommended to be utilized for antivirus mask selection to give more uncertain linguistic set applications in symmetry [ 44 ], Subset neighborhood rough sets [ 85 ], dense sets [ 86 ], and other rough sets environments [ 87 ]. Information-aggregation operators are also recommended to be utilized and investigated under spherical normal fuzzy environment, such as spherical normal fuzzy interaction operators and spherical normal fuzzy Hamy mean operators [ 43 ].

Additional criteria recommendations

Literature recommends different parameters or criteria to be added for further analysis. For example, a recommendation is to add more symptoms and larger data sets to identify COVID-19 [ 36 ]. Another study recommends to add more preventive measures for COVID-19 spread assessment [ 68 ]. Additional criteria are likewise recommended to be added to the decision matrix of the study to support their evaluation and benchmarking in selecting the best methodology of diagnosing COVID-19 [ 40 ]. New criteria or sub-criteria are likewise recommended to be added to improve the COVID-19 regional safety assessment using the MCDM methods [ 41 ]. To improve the COVID-19 vulnerability geospatial modeling using fuzzy MCDM methods, age distribution, ethnic factors, and climatic factors are recommended to be added as parameters [ 83 ].

Diseases-related recommendations

For COVID-19 vaccination accessibility analysis, a recommendation is to include the coordination and planning of procurement activities, storage, distribution, and monitoring of vaccine-dose availability [ 45 ]. Another study suggested to consider additional criteria and facts to improve the developed COVID-19 vulnerability map to accurately predict future COVID-19 outbreaks [ 83 ]. Another recommendation is to classify COVID-19 vaccine priority groups on the basis of availability, safety, delivery and cost [ 46 ]. Furthermore, it is recommended to analyze more COVID-19 vaccines and provide additional criteria to the MCDM approaches on the basis of individual priorities [ 77 ]. Ranking hospitals during the COVID-19 pandemic is recommended to identify more criteria, including the quality of equipment and hospital staff satisfaction, along with the quality of services and patients satisfaction [ 55 ]. To assure care for many people during COVID-19 pandemic, further analysis is suggested by including different variables, such as safe nursing homes, safe mask, safe homes, location for quarantine centers, and isolation planning, as well as an epidemic controlling model and ICU bed augmentation model [ 73 ]. Lastly, prioritizing COVID-19 vaccine dose recipients is recommended to present and process a large-scale data set of COVID-19 vaccine recipients by considering all probabilities frequently augmented for each alternative.

Critical analysis

MCDM is one of the most intriguing and helpful tools that aided, and continues to aid, during the COVID-19 pandemic. Regardless of where it is applied, MCDM pioneered in many aspects of literature, including social, science and even medical research. Among the most important aspects is the medical application of MCDM-related research in COVID-19 settings. In this review, a comprehensive analysis is conducted from taxonomy analysis and discussion for main literature aspects. Some of these aspects are challenges, motivations, and recommendations related to COVID-19 directly (as a disease) or to the integration of MCDM with COVID-19 cases (application level). Notably, the authors report back on their previous peer’s issues, which hinder previous research effort. An important aspect is that the authors reflect their own point of view and implications based on the analysis conducted. For the current study, numerous attempts have been made to address many of the current challenges, such as those related to the MCDM techniques, COVID-19 and those that combine them. However, minimal focus has been directed to the security of medical data used in the process. Medical data are generally sensitive because they involve confidential information on patients’ treatment and should not be disclosed. These medical data are occasionally shared between hospitals and patients for medical decisions, such as the prioritization of patients or even assigning them for treatment.

Based on our taxonomy analysis, MCDM is used in the medical context for many medical-related cases (diagnosis models, safety aspects, hospital related aspects, and treatment). All aforementioned cases have their own medical data, whether patient-, treatment- or even hospital related. These medical data are sensitive, and sharing them between hospitals even for treatment purposes requires approval. During the COVID-19 pandemic, a difficult undertaking is to continue sharing medical data between hospitals while maintaining privacy and security. This endeavor poses a significant challenge because MCDM cannot work without actual data, and that data are transferred and prone to online misconduct, such as hacking or any malicious activities, resulting in the inseparable nature of hospitals in using online hospital networks [ 88 ]. For example, if hackers gain access to the hospital network and found patient data, they would have the ability to alter the course of treatment of patients and jeopardize the entire treatment process. Consequently, death may ensue in severe cases. Therefore, hospital networks should keep its performance in distributing data within more than one hospital to provide HC services and maintain data security and privacy, while important findings related to patient treatment are still generated.

Motivated by the preceding fact, the academic literature has presented a concept called “federated learning” (FL), in which a distributed set of machine processes are trained on huge medical data [ 89 ]. This concept focuses more on bringing the code to the data rather than having the data transferred into the code or processing, thereby reducing privacy and security issues. This approach has been recently introduced but is also already extensively utilized in ML research for various cases, the most important of which is medical-related. This situation is apparent because of the influx of patients and their medical data during the COVID-19 pandemic. FL is considered an exact-fit approach that only applies distributed learning to fit the privacy data challenge. FL has been applied in treatment-related studies for COVID-19, including [ 90 ], which presents FL to build prediction models of mortality for COVID-19 patients based on their e-health records (EHR). Moreover, Ref. [ 91 ] used FL for developing a diagnostic model for SARS-COV-2 to provide a robust model that can serve medical centers without sharing patient data. Evidently, FL is widely utilized in the context of ML, but patient medical data during crisis related times and for treatment related purposes such as the one with COVID-19 should also be studied. Given the advantages of FL, we propose to integrate it as a novel solution with decision science, particularly MCDM for different applications, such as treatment distribution. The following sections detail a proposed methodology on the utilization of FL as a novel application with MCDM for COVID-19 treatment distribution. All major steps to be considered will be detailed along with their rationale and how to apply it.

Proposed methodology

This section discusses the proposed methodology for integrating FL fundamentals in the context of MCDM for treatment purposes. Four subsections are likewise presented, in which the first discusses the formulation of the MCDM problem requiring FL (Fig.  11 ).

Problem formulation

We discuss the formulation of the problem, leading to the integration of federated MCDM in the proposed case study. Two main challenges are discussed, i.e., those related to the case study and those related to the technical aspect. Figure  11 illustrates the main sections of problem formulation (Fig. 12 ).

Case study (treatment)

No specific treatment is available at the start of the COVID-19 pandemic. Hence, numerous research endeavors have emerged to assist, including the vaccine, and others. In spite of the substantial benefits provided by previous treatment effort, the introduction of monoclonal antibodies (mAb’s) is presented as a treatment solution with more feasibility [ 92 ]. This type of treatment has long been recognized for giving immediate, passive immunity to individuals and help decrease disease symptoms and progression [ 93 ]. Typically, it is better if individuals are vaccinated prior to being infected, but the virus typically moves faster than the vaccination pace. In this regard, and given the impossibility of preventing infection, symptoms should be reduced to certain levels [ 94 ], and mAb’s is a pioneer in this aspect [ 93 , 95 ]. Despite the suitability of mAb’s as treatment, if its distribution effort is not as quick as the virus spread, many people’s health would worsen and severely influence patients’ quality of life, even the economy [ 96 ]. This issue is worthy of consideration because it is a normal situation distribution problem and also because of the limited supply of this treatment, thereby raising a significant challenge regarding who should have it and the order of receiving it. Accordingly, a global interest is generated on the distribution of SARS-CoV-2 medicinal treatments [ 96 ]. The distribution significance is observant for treatment and is also reported for various medical and COVID-19-related cases, such as vaccine distribution . Therefore, this problem is worthy of investigation because there are factors that may play a role in the distribution process that differ from one country to another [ 97 ]. This type of treatment cannot be given or distributed without medical supervision. Furthermore, this supervision is constantly directed at medical centers or hospitals, making them an integral challenging part in the process.

Case study (hospitals providing treatment)

While addressing the problem of mAb treatment distribution, hospitals play a significant role in the process. Hospitals often administer their treatment distribution in such pandemic times. They rely on their network infrastructure to process the huge amount of patient data and to keep their channel of communication open with other hospitals, particularly if they are placed in different geographical locations [ 88 ]. These types of networking services are introduced to improve the efficiency of HC delivery and share specialized medical services and specialties [ 98 ]. Moreover, such a noble process does not come without risks, which are in the form of patient data privacy and security challenges [ 99 ]. They are important in usual circumstances and when they are used for SARS-CoV-2 treatment availability in the distribution hospitals. Therefore, this issue is a significant challenge to be considered. The following section discusses the data-privacy challenge for SARS-CoV-2 medical treatment and distribution.

Case study (data privacy)

Data sharing and privacy are among the most studied topics in many academic fields. They present a significant aspect for consideration, and they have a huge set of significantly different data cases, such as those for patient medical data. This issue is presented in this study’s context because medical data are often shared for treatment purposes between hospitals using network and telehealth services [ 100 ]. There are serious security breaches that may endanger patients’ health severely should hackers successfully hack medical data {MEDICA, 2020 #85}. These breaches may cause unprecedented alteration in patient treatment regimen, thereby potentially causing serious concerns. Therefore, the confidentiality of patient data must be safeguarded against unauthorized use and disclosure to third parties without patient consent. To safeguard patient data, two data privacy subchallenges are worthy of addressing: data sharing and independence. These aspects are reported in the following subsections.

Data sharing Data sharing among hospitals must be ensured as part of data-privacy protection. This process is mostly needed during difficult times, such as during the COVID-19 pandemic, when data are shared between medical institutions and researchers globally to develop good counter-strategies and treatment. This issue is worthy of consideration, particularly in a centralized system to establish a secure communication path between hospitals.

Data independence Another subchallenge for data privacy is data independence. This issue is part of data handling when used alongside database-management system (DBMS). DBMS enables users to alter data definitions and structure without influencing hardware and software. This practice enables various users to access and process data for different purposes. This issue is also apparent in a hospital setting, where DBMS are used to manage patient medical data, thereby assisting in making medical decisions. However, each hospital has its own DBMS format for storing and processing patient medical data. This situation presents data-privacy issues, in which no single representation of data distribution of patients exists [ 101 ]. This issue plays significant role in the privacy challenge for each hospital and is worthy of pursuing.

A summary of all previously discussed challenges and issues associated with the case study is presented as follows.

Statement 1: Providing mAb treatment to COVID-19 patients is challenging because of limited resources and different patient priority groups.

Statement 2: Using patient medical data for mAb treatment purposes among different hospital networks while maintaining privacy is a challenging task.

Statement 3: Maintaining patient medical data privacy for mAb treatment is challenging when data sharing is not secured and data used between hospitals are not unified.

The three statements present valid challenging problems that should be addressed in future research. Upcoming issues for future research in terms of technical aspects should be discussed to show how these problems are solved. Accordingly, the proposed problem definition subsection discusses the technical-problem definition.

Technical issues (prioritization)

For the technical challenges, the distribution of treatment should be prioritized. Hence, it is important to know which factors are influencing and to which extent this prioritization process. According to the National Institutes of Health, treatment guidelines suggest the use of Anti-SARS-CoV-2 for treating mild-to-moderate symptoms and SARS-CoV-2 infection PEP for those with severe symptoms [ 92 ]. For the ones from the last severe category, differences exist between patients who have been fully vaccinated because they are less likely to be infected again compared with patients who are partially vaccinated or even patients fully vaccinated but are not expected to generate a significant immunological response to the vaccine [ 102 , 103 ]. This situation presents an issue of which patients may benefit the most from the treatment when treatment supply restrictions render impossible the treatment of all eligible patients. Therefore, triage becomes essential [ 104 ]. When this issue is presented, hospitals should utilize clinical discretion when prioritizing the use of anti-SARS-CoV-2 mAb’s for treatment or PEP in a particular context. This situation presents a multi-attribute decision challenge. Given the variety of treatment decision criteria, their importance level and data variation affect the prioritization main technical challenge. Details of the three subchallenges are presented in the following subsection.

Multiple criteria The issue of multiple evaluation criteria occurs when patient prioritization to receive mAb medical treatment for COVID-19 is subjected to different aspects, which influence the prioritization process. Examples of these aspects are (1) age, (2) hypertension, (3) cardiovascular disease, (4) heart diseases, (5) chronic respiratory disease, (6) obesity body mass index, (7) immunosuppressive disease, (8) pregnancy, and COVID-19 severity. The different aspects are referred to as criteria from literature and they are used to determine the urgency of a patient in the process of treatment distribution. Some of these criteria hold more importance than others, which are not particularly applicable in normal life situations. However, when they are presented to patients who are about to receive mAb medical treatment, some of these criteria are more important than others, which affect the patient prioritization. Details of the criterion importance are discussed in the next sub-problem.

Criterion-importance level Criterion importance in the context of MCDM refers to how significantly these criteria can affect the treatment-distribution process. For example, two patients require mAb treatment but the first one is 70 years old and the other is 35 years old. The first one suffers from diabetes and the second one suffers from kidney failure. According to the criterion importance, the second patient received treatment even though he is younger. The reason is that his other criterion of having kidney disease outweighs the diabetes criteria and the old age of the first patient. This example shows how different criteria with different importance significantly affect the prioritization process. The importance level for these criteria can either be conducted subjectively by decision makers (experts) [ 105 , 106 ] or objectively via the fixed-weight method [ 107 ]. Regardless of which of them is the most qualified, they are both presented to address the main issue; In other words, which among the criteria is more important than the others. However, even if these criteria are given different importance levels by the previous means, l some medical data, particularly the ones in mAb’s, can be varied in their representation. For example, age is represented by the number of years, while having diabetes or kidney disease is a Yes/No question. This situation presents a data variation issue that also affects the prioritization process for mAb medical treatment. Details of the data variation issue are presented in the next section.

Criterion data variation The data-variation issue refers to the different representations of data criteria from literature. Variations listed in the academic literature have been generally concerned with the ranking process in eligible high-risk patients [ 108 , 109 , 110 , 111 ]. Moreover, data variations can be considered a special scenario to offer a clear discussion and analysis of this concern. For example, a scenario may occur as a goal with maximum representation, which is related to the distribution matrix for patients and their different criteria. In this context, the scenario can be observed when the maximization values of the criteria (↑) affect the data of the alternatives (i.e., high, higher and highest levels), in which the aim is to achieve a better selection process. Therefore, the prioritization process involves a simultaneous consideration of multicriterion matrices of the treatment-distribution process for eligible high-risk patients, in which different maximization goal scenarios are represented by the varying high, higher and highest levels that generate various data. A summary of all previously discussed technical challenges and issues is presented as follows.

Statement 4: Distributing mAb treatment to COVID-19 patients is challenging because of the criterion tube considered in the decision process.

Statement 5: Distributing mAb treatment to COVID-19 patients is challenging because of the importance level for the prioritization decision criteria.

Statement 6: Distributing mAb treatment to COVID-19 patients is challenging because of the variety of the criterion tube considered in the decision process.

Proposed solution

This subsection discusses the federated MCDM methodology used as proposed solution. Figure  13 shows the flow of the method.

Proposed solution flow

• Federated learning

FL is a new application of AI, in which data training and learning occur on decentralized serve, and the findings are taken into the edge or on-device. FL is a popular trending topic, even though it is still in its early stages. FL works by distributing ML training models on data and training and takes learning to the edge or on-device large corpus of distributed data, according to the definition in Ref. [ 89 ]. It has been utilized in various medical applications, and its integration during the COVID-19 pandemic is apparent in different areas of research. Several studies have been conducted in this regard. Ref. [ 90 ] used FL to build prediction models of mortality in SARS-COV-2 patients based on their e-health records (EHR). Reference [ 91 ] adopted FL for developing a diagnostic model for SARS-COV-2 to provide a robust model that can serve as much as possible medical centers without sharing patient data. Reference [ 112 ] proposed an innovative collaborative model that allows numerous city Digital Twin (city DT) in the same region to immediately communicate the local plan and status for crisis management. Reference [ 113 ] that proposed a novel framework for early warning of SARS-COV-2 using crowd source and federated surveillance models that protect the privacy and allow social participants who do not have mutual trust to share the verified surveillance resources and blend their surveillance solutions. By considering how FL works, it enables local hospitals to learn collaboratively without the need for patient data sharing with a centralized or medical central server. In other words, patients’ data located and processed in the hospital. Nevertheless, FL has some medical applications, such as for COVID-19. However, most studies have utilized it in ML or deep-learning context. To the best of the author’s knowledge, no study has utilized it for mAb treatment distribution as prioritization challenge. Accordingly, addressing this challenge requires decision science. The next section describes MCDM and its potential as a proposed solution.

MCDM integration

MCDM is defined as a decision-theory extension covering any decision with multiple objectives. It is a branch of science long recognized for its capability in addressing prioritization issues when several conflicting criteria are to be considered [ 65 ]. It provides immense benefits not only in theoretical research but also in many applied research cases, such as COVID-19 mAb treatment prioritization challenges. MCDM in literature has been used in different cases to prioritize COVID-19 treatments. For example, Ref. [ 63 ] proposed an intelligent framework on the basis of the MCDM context’s success in handling the patients’ prioritization issue over distribution hospitals networking for the transfusion of efficient CP from donor to the most critical SARS-COV-2 patients. In spite of the aforementioned medical studies, MCDM has only handled prioritization issues in normal settings, where no data challenges in terms if privacy are considered. Therefore, it having MCDM integrated as a supporting tool to FL is warranted in mAb treatment distribution and prioritization challenges. To the best of our knowledge, it has not been applied previously in such a context, so it is a noteworthy research focus. Therefore, we call for the formulation of a new federated fundamental concept called federated DM distributor (FDMD) to overcome both challenges, thereby ensuring the privacy of SARS-COV-2 health data and prioritizing the anti-SARS-CoV-2 mAb recipients within distribution hospitals.

Theoretical background of the FDMD fundamentals

This solution enables hospitals to collaboratively learn to prioritize patients without data exchange/sharing with a centralized medical center server. Hence, FDMD should comprise two key sequence processes, namely, a patient-prioritization process that uses the hospital’s local decision matrix (a unique decision matrix for each hospital). Moreover, the global distribution transmission process ensures privacy protection and equitable distribution across all hospitals concurrently. The first process occurs using representative data (abstract data) obtained from local decision matrices. This step ensures patient data privacy, but the issue of patients’ prioritization process continues to be confronted with other challenging issues (e.g., multi criteria, data variation, criterion weighting). Accordingly, we need to formulate an MCDM methodology that can address the aforementioned issue. The following subsection presents a short review of the most used MCDM techniques with their pros and cons and best suited for the proposed FDMD.

MCDM methods

Several MCDM methods have been used in literature for variety of decision problem cases. MCDM methods have been categorized as either mathematical or human approaches. Among these methods is a simple additive weighting (SAW), which obtains the weighted sum of the performance ratings of each alternative overall attribute [ 114 , 115 ]. It comprises two basic steps: the scale of the values of all attributes to make them comparable and the sum of the values of all attributes for each alternative [ 115 ]. Another method is hierarchical adaptive weighting (HAW), which is one of the earliest and possibly the simplest MCDM technique. WSM allows the comparison of the alternatives by assigning scores, and using these scores thereafter to generate standard values for the alternatives under consideration. Another method is weighted-product method, which presents numerous similarities with WSM but different in terms of the main mathematical operation. The last technique is TOPSIS, which is based on the concept that the ideal alternative has the best level for all attributes, but the negative ideal is the one with all of the worst attribute values [ 116 , 117 ]. Evidently, MCDM and its techniques cover a wide area of research. While determining which of these techniques can be suitable for the FDMD concept, TOPSIS evidently has the best fit because of its nature with positive and negative ideals. This characteristic enables the creation of numerous matrices distributed between local federated hospital clients and central servers. However, the classical version of the TOPSIS method has some weaknesses: (1) insensitive to small values [ 118 ], (2) distorts the original information [ 119 ], (3) ranks reversal flaws [ 120 ], and (4) relatively small distance between the positive and negative ideal solutions [ 121 , 122 , 123 ]. Therefore, an improvement in TOPSIS is considerably warranted. The following subsection explains the improvement of TOPSIS and how it can be used as an FDMD concept.

Step 1: TOPSIS as FDMD.

Literature has indicated many improved versions of TOPSIS to overcome the classical TOPSIS flaws [ 119 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 ]. For the same purpose, Ref. [ 130 ] developed classical TOPSIS in terms of improving positive and negative ideal solutions, as well as the closeness degree formula to avoid the possibility of rank reversal. FDMD is an iterative prioritization process among hospitals, including periodically admitting or discharge patients (i.e., increasing or decreasing in the alternatives) at each hospital for a given time, thereby causing a rank-reversal issue. Improved TOPSIS proposed by [ 130 ] entails the use of the efficacy coefficient method (ECM)) to avoid a potential rank reversal when absolute ideal solutions used is adopted in this study for prioritization. In return for protecting patients’ privacy during the prioritization process, the adopted TOPSIS [ 130 ] is utilized with the federated fundamental concept to introduce federated TOPSIS (F-TOPSIS). The main contribution of F-TOPSIS is the unification of the positive and negative ideal vectors that compute at the server side and provided to all local machines, with the preliminary settings. Meanwhile, each local machine uses it for the local prioritization process and sent back to the server for combining and computing the global prioritization ranks for each alternative (i.e., patients) over the LM networking. This sequence synchronized process of F-TOPSIS that implemented between CFS, and LM consist of the following eight steps.

Step 1: Proposed the dynamic decision matrix (DDM) locally.

For each local machine, DDM is constructed on the basis of the crossover of the mAb treatment distribution criteria and eligible patients, as shown in Table 1 using Eq. ( 1 ).

\({K}\) : represent the number of the local machine.

\({n}\) : represent the number of alternatives.

\({m}\) : represent the number of criteria.

Step 2: Allocation of DDM values locally .

This step includes the allocation of each alternative related to each criterion using Eq. ( 2 ).

\({K}\) : represent the number of the local hospital.

\({n}\) : represent the number of patients.

Step 3: Unified local positive and negative vectors at CFS.

In this step, positive and negative ideal vectors are determined for each registered LM and passed to the federated central server for unifying process of the positive and negative ideal values using Eqs. ( 3 ) and ( 4 ) [ 130 ]. The equation generalized for all \({{{a}}^{{k}}}_{{j}}^{+}\) and \({{{a}}^{{k}}}_{{j}}^{-}\) for all LM.

Equation ( 4 ) generalized the \({{{a}}^{{k}}}_{{j}}^{+}\) and \({{{a}}^{{k}}}_{{j}}^{-}\) for all LMs in the federate negative and positive ideal vectors. Specifically, \({{{a}}^{{g}}}_{{j}}^{+}\) is the maximum value over all local maximum values and \({{{a}}^{{g}}}_{{j}}^{-}\) is the minimum value over all local minimum values.

Step 4: Normalization. In this step, the decision matrix for each local machine is normalized using Eq. ( 5 ) [ 130 ] based on the federated positive and negative ideal values and \(\upbeta\) interval value sent by CFS.

Step 5: Application of external weight values. In this step, weights of each used criterion will be applied to the normalized decision matrix at each LM, using Eq. ( 6 ) [ 130 ].

Step 6: Closeness determination. This step includes defining the negative and positive using Eq. ( 7 ) [ 130 ] at LM.

Step 7: Ranking the alternatives. This step is the last one, in which alternative ranking is computed locally using LM and combine and sort globally at server side. At LM, the local score at each alternative compute using the project from each alternative \({{y}}_{{i}}\) to positive ideal solution y * using Eq. ( 8 ) [ 130 ].

Lastly, the patient rank will set \({X }= \{{x}1,{ x}2, \dots ,{ xm}\}\) according to the value of \({{Pr}}^{{k}}\left({{{y}}^{{k}}}_{{ij}}\right)\) ( \({i }\in {M}\) ).

Thereafter, global rank orders the alternative \({X }= \{{{x}}^{1},{{x}}^{2}, \dots , {{x}}^{{k}}\}\) according to the value of \({Pr}\) .

In the FDMD sequence process, the criterion importance has a vital role in the final results. However, one of the main limitations of federated-TOPSIS is the criteria weight are required an external method for weighting the criteria. In the MCDM context, there are two ways to assign weights to the criteria: objectively and subjectively [ 131 ]. In the objective weighting methods, the importance of criteria is computed based on raw data. In such a situation, raw data changes affect the accuracy of the weight value and are required to share the private data of patients. By contrast, the subjective weighting methods represent the experts’ cumulative knowledge and their subjective opinions [ 132 ]. Many subjective weighting methods have been introduced in literature. The following subsection discusses the main ones and which is best suited for the case study of this research.

Weighting method

For the future treatment case studies, and according to the MCDM approach, different criteria should be presented from literature on medical guidelines. They are used in the prioritization/ranking process. However, each of these criteria differs in significance and impact on the overall treatment decision. Notably, many approaches are presented, such as AHP [ 63 ] and BWM [ 133 ], which presents a high rate of success in weighting criteria. However, the inconsistency in their weighing methods continues to be an unsolved issue. Addressing these issues is resolved by the FWZIC [ 134 ] method achieved zero inconsistency by precisely determining the weight values of each criterion. Moreover, it can determine the criterion importance in the DM process with the assistance of experts [ 135 ]. The following section explains the FWZIC methodology.

Criterion weighting technique

Based on literature, a net method called novel fuzzy-weighted zero-inconsistency (FWZIC) [ 136 ] is proposed and proven more robust in mitigating the short comings of the previous weighting techniques. FWZIC has been proven to provide weights for criteria with zero inconstancy. Thus, this method is more promising in weighting criteria for the vast cases of MCDM integration with COVID-19 cases. This method also comes in different versions with different fuzzy types. Here, we describe its main steps.

Phase 1: Criterion definition. In this phase, all the ready-to-be-utilized criteria are introduced to FWZIC after being evaluated and defined.

Phase 2: Structured expert judgment. In this phase, the criterion defined from previous step is evaluated for their importance level by panel of expert. These experts should be specialists with sufficient academic and research experience. Afterwards, a nomination process is established through the following steps.

Expert identification. Experts are identified as those who have been or still involved in the subjects of the case study and regarded as knowledgeable by others.

Expert selection. After completing expert identification, some of them are deemed most suitable for the case study. A minimum of four experts are needed in this stage. For the expert’s panel, they should be between 10 and 16. All experts from the previous stage are reached out via email to determine their availability and willingness to be considered potential experts for the panel.

Developing evaluation form. The evaluation form used in the case study is developed in this stage for collecting experts’ consensus, and it undergoes reliability and validity check.

Defining the importance level scale. All selected experts from previous step define the importance level for each criterion with the use of a five-point Likert scale.

Converting linguistic scale to numerical scale. This step includes transforming all preference values are from subjective form into numerical form so they can be utilized in the analysis. Thus, the importance level for every criterion from each expert in the used Likert scale is converted into numerical scale, as shown in Table 2 .

Phase 3: Building EDM. This step includes creating EDM with the main parts, which include the criteria and alternatives, as shown in Table 3 .

The previous phase provides a definition for the list of selected experts and the preference of each expert within a single criterion. EDM is constructed in this step. The main parts of EDM are the decision criteria and alternatives.

Phase 4: Application of Fuzzy memberships.

FWZIC is a technique of MCDM used to measure the criteria weight based on human subjective assessment. The earliest version of this method developed with fuzzy to help reducing the uncertainty associated with the subjectivity of human decision makers. In this step, the main formulae to be used in FWZIC [ 137 ] are presented based on the triangular fuzzy numbers set. Below are the formulas of the selected fuzzy set:

Fuzzy membership

Arithmetic operations

Subtraction

Multiplication

Division on crisp value

Defuzzification

Phase 5: Final weight computing.

In this step, FWZIC technique applied with the identified fuzzy set-in Formulas 9 to 15 are used to measure the final weight. These steps can be compromised into three substeps.

The ratio of fuzzification data is computed using Eqs. ( 11 ) and ( 14 ).

Average values are computed to find the final fuzzy values of the weight coefficients of the evaluation criteria \({(\widetilde{{w}1},\widetilde{{w}2}, ...,\widetilde{{wn}})}^{{\rm T}}\) , using Eq. ( 15 ).

Defuzzification is conducted to determine the final weight. In particular, defuzzification methods are used to find the crisp weight value using Eq. ( 16 ) Prior to calculating the final values of the weight coefficients, the weight of importance of each criterion is assigned based on the sum of the weights of all criteria for the rescaling purpose applied in this stage.

We conduct an SLR of several COVID-19 cases studies using the MCDM approach and obtain a final set of 32 selected studies ( n  = 32). These studies are taxonomized and categorized into different classes, namely, diagnosis ( n  = 6), safety ( n  = 11), hospital ( n  = 8), treatment ( n  = 4), and review ( n  = 3). Two aspects are identified in diagnosis class: (1) computerized and hospital-based tests and (2) regional assessment, masks and sanitizer toward the safety measures. For safety class, four topics are identified considering the linkage of MCDM with medical settings, which are regional assessment, sanitizers, mask selection and vaccine. For the hospital class, the discussion is made on the basis of the use of MCDM in medical settings for COVID-19 situation in term of hospital selection and admission, hospital services, and patient prioritization. Another two topics are discussed with the treatment class: medicine and plasma. Finally, the review articles that discuss MCDM studies in relation to COVID-19 applications. A state-of-the-art bibliographic analysis is presented based on R-tool and VOSviewer to explore annual scientific production, country scientific production, co-occurrence, and co-authorship. Moreover, different highlights including challenges (diseases and techniques), motivations (diagnosis, DM, HC resources, vaccines/treatment, and detection), and recommendations (other environments and methods, different case studies, different operators and structure, additional criteria, diseases) are analyzed. However, this study identifies research gaps for distributing mAb vaccine doses among different hospitals given the data-related issues, such as privacy, data type and being an MCDM issue given the difference priority groups eligible for the vaccine given the lack of resource. Lastly, a desirable solution comprising two main aspects is proposed. The first is involves integrating MCDM to address the distribution issue given the different priority groups and lack of vaccine resources. The second involves modifying the typical MCDM to make it comparable with the FL concept and address the issues associated with data sharing and privacy expected to occur during patient-information exchange among different hospitals for treatment. The proposed method in this research is based on TOPSIS. However, in the future, other MCDM techniques with normalization (i.e., VIKOR, MULTIMOORA, and MARCOS) and others can be integrated into the federated concept. Lastly, the security aspect can also be considered by integrating the future federated concept with more robust technologies such as blockchain between client and server to ensure multilevel privacy.

Data availability

Availability of data and material not applicable.

Berkessel JB, Ebert T, Gebauer JE, Jonsson T, Oishi S (2022) Pandemics initially spread among people of higher (not lower) social status: evidence from COVID-19 and the Spanish Flu. Soc Psychol Pers Sci 13(3):722–733

Google Scholar  

Colman E, Wanat M, Goossens H, Tonkin-Crine S, Anthierens S (2021) Following the science? Views from scientists on government advisory boards during the COVID-19 pandemic: a qualitative interview study in five European countries. BMJ Glob Health 6(9):e006928

Ebrahim SH, Memish ZA (2020) COVID-19: preparing for superspreader potential among Umrah pilgrims to Saudi Arabia. Lancet (London, England) 395(10227):e48

Buheji M et al (2020) The extent of covid-19 pandemic socio-economic impact on global poverty. a global integrative multidisciplinary review. Am J Econ 10(4):213–224

Koh D (2020) COVID-19 lockdowns throughout the world. Occup Med 70(5):322–322

Harper L et al (2020) The impact of COVID-19 on research. J Pediatr Urol 16(5):715–716

Mazza M, Marano G, Lai C, Janiri L, Sani G (2020) Danger in danger: interpersonal violence during COVID-19 quarantine. Psychiatry Res 289:113046

Betsch C et al (2020) Social and behavioral consequences of mask policies during the COVID-19 pandemic. Proc Natl Acad Sci 117(36):21851–21853

Wójcik D, Ioannou S (2020) COVID-19 and finance: market developments so far and potential impacts on the financial sector and centres. Tijdschr Econ Soc Geogr 111(3):387–400

Forman R, Shah S, Jeurissen P, Jit M, Mossialos E (2021) COVID-19 vaccine challenges: What have we learned so far and what remains to be done? Health Policy 125(5):553–567

Alamoodi AH et al (2021) Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: a systematic review. Expert Syst Appl 167:114155

Adom D, Osei M, Adu-Agyem J (2020) COVID-19 lockdown: a review of an alternative to the traditional approach to research. Res J Adv Soc Sci 1:1–9

Nitpolprasert C, Anand T, Phanuphak N, Reiss P, Ananworanich J, Peay HL (2022) A qualitative study of the impact of coronavirus disease (COVID-19) on psychological and financial wellbeing and engagement in care among men who have sex with men living with HIV in Thailand. HIV Med 23(3):227–236

Anžej Doma S, Lukič M (2022) Severe COVID-19 infection management in a patient with mild haemophilia—a case report. Hematol Rep 14(2):103–107

Bou-Hamad I, Hoteit R, Harajli D (2021) Health worries, life satisfaction, and social well-being concerns during the COVID-19 pandemic: insights from Lebanon. PLoS ONE 16(7):e0254989

Rasheed J et al (2020) A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic. Chaos Solitons Fract 141:110337

Woolliscroft JO (2020) Innovation in response to the COVID-19 pandemic crisis. Acad Med 95:1140–1142

Banks S et al (2020) Practising ethically during COVID-19: social work challenges and responses. Int Soc Work 63(5):569–583

Borio C (2020) The Covid-19 economic crisis: dangerously unique. Bus Econ 55(4):181–190

Elavarasan RM, Pugazhendhi R (2020) Restructured society and environment: a review on potential technological strategies to control the COVID-19 pandemic. Sci Total Environ 725:138858

Rajan S et al (2021) Impact of COVID-19 pandemic on cancer surgery: patient’s perspective. J Surg Oncol 123(5):1188–1198

Sohrabi C et al (2021) Impact of the coronavirus (COVID-19) pandemic on scientific research and implications for clinical academic training—a review. Int J Surg 86:57–63

Shearer FM et al (2021) Development of an influenza pandemic decision support tool linking situational analytics to national response policy. Epidemics 36:100478

Jordan E, Shin DE, Leekha S, Azarm S (2021) Optimization in the context of COVID-19 prediction and control: a literature review. IEEE Access 9:130072

Castillo O, Castro JR, Pulido M, Melin P (2022) Interval type-3 fuzzy aggregators for ensembles of neural networks in COVID-19 time series prediction. Eng Appl Artif Intell 114:105110

Castillo O, Melin P (2021) A new fuzzy fractal control approach of non-linear dynamic systems: the case of controlling the COVID-19 pandemics. Chaos Solitons Fract 151:111250

Di Vaio A, Boccia F, Landriani L, Palladino R (2020) Artificial intelligence in the agri-food system: rethinking sustainable business models in the COVID-19 scenario. Sustainability 12(12):4851

Mansour RF, Escorcia-Gutierrez J, Gamarra M, Gupta D, Castillo O, Kumar S (2021) Unsupervised deep learning based variational autoencoder model for COVID-19 diagnosis and classification. Pattern Recogn Lett 151:267–274

Tolga AC, Parlak IB, Castillo O (2020) Finite-interval-valued type-2 Gaussian fuzzy numbers applied to fuzzy TODIM in a healthcare problem. Eng Appl Artif Intell 87:103352

Al-Shami TM (2022) Maximal rough neighborhoods with a medical application. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-022-03858-1

Wang CJ, Ng CY, Brook RH (2020) Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing. JAMA 323(14):1341–1342

Al-shami TM (2021) An improvement of rough sets’ accuracy measure using containment neighborhoods with a medical application. Inf Sci 569:110–124

MathSciNet   Google Scholar  

Dulmin R, Mininno V (2003) Supplier selection using a multi-criteria decision aid method. J Purch Supply Manag 9(4):177–187

Farrell NF, Klatt-Cromwell C, Schneider JS (2020) Benefits and safety of nasal saline irrigations in a pandemic—washing COVID-19 away. JAMA Otolaryngol Head Neck Surg 146(9):787–788

Luo J, Zhou L, Feng Y, Li B, Guo S (2021) The selection of indicators from initial blood routine test results to improve the accuracy of early prediction of COVID-19 severity. PLoS ONE 16(6):e0253329 https://doi.org/10.1371/journal.pone.0253329

Abdel-Basst M, Mohamed R, Elhoseny M (2020) A model for the effective COVID-19 identification in uncertainty environment using primary symptoms and CT scans. Health Inform J 26(4):3088–3105

Ashraf S, Abdullah S, Almagrabi AO (2020) A new emergency response of spherical intelligent fuzzy decision process to diagnose of COVID19. Soft Comput 1–17 https://doi.org/10.1007/s00500-020-05287-8

Karaaslan F, Dawood MAD (2021) Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making. Complex Intell Syst 7(5):2711–2734

Hashmi MR, Riaz M, Smarandache F (2020) m-polar neutrosophic generalized weighted and m-polar neutrosophic generalized Einstein weighted aggregation operators to diagnose coronavirus (COVID-19). J Intell Fuzzy Syst 39(5):7381–7401

Mohammed MA et al (2020) Benchmarking methodology for selection of optimal COVID-19 diagnostic model based on entropy and TOPSIS methods. IEEE Access 8:99115–99131

Hezer S, Gelmez E, Özceylan E (2021) Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID-19 regional safety assessment. J Infect Public Health 14(6):775–786

Zulqarnain RM, Xin XL, Garg H, Ali R (2021) Interaction aggregation operators to solve multi criteria decision making problem under pythagorean fuzzy soft environment. J Intell Fuzzy Syst 1151–1171

Yang Z, Li X, Garg H, Qi M (2020) Decision support algorithm for selecting an antivirus mask over COVID-19 pandemic under spherical normal fuzzy environment. Int J Environ Res Public Health 17(10):3407

Yang M-S, Ali Z, Mahmood T (2021) Complex q-rung orthopair uncertain linguistic partitioned Bonferroni mean operators with application in antivirus mask selection. Symmetry 13(2):249

Alemdar KD, Kaya Ö, Çodur MY, Campisi T, Tesoriere G (2021) Accessibility of vaccination centers in COVID-19 outbreak control: a GIS-based multi-criteria decision making approach. ISPRS Int J Geo Inf 10(10):708

Hezam IM, Nayeem MK, Foul A, Alrasheedi AF (2021) COVID-19 vaccine: a neutrosophic MCDM approach for determining the priority groups. Results Phys 20:103654

Albahri O et al (2021) Novel dynamic fuzzy decision-making framework for COVID-19 vaccine dose recipients. J Adv Res 37:147–168

Alsalem M et al (2021) Based on T-spherical fuzzy environment: a combination of FWZIC and FDOSM for prioritising COVID-19 vaccine dose recipients. J Infect Public Health 14(10):1513–1559

Albahri A et al (2022) Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: a distribution case study of COVID-19 vaccine doses. Comput Stand Interfaces 80:103572

Sarwar A, Nazar N, Nazar N, Qadir A (2021) Measuring vaccination willingness in response to COVID-19 using a multi-criteria-decision making method. Human Vaccines Immunother 17(12):4865–4872

Khan MJ, Ali MI, Kumam P, Kumam W, Al-Kenani AN (2021) q-Rung orthopair fuzzy modified dissimilarity measure based robust VIKOR method and its applications in mass vaccination campaigns in the context of COVID-19. IEEE Access 9:93497–93515

Kheybari S, Ishizaka A, Salamirad A (2021) A new hybrid risk-averse best-worst method and portfolio optimization to select temporary hospital locations for Covid-19 patients. J Oper Res Soc 1–18

Khan A, Abosuliman SS, Ashraf S, Abdullah S (2021) Hospital admission and care of COVID-19 patients problem based on spherical hesitant fuzzy decision support system. Int J Intell Syst 36(8):4167–4209

Özkan B, Özceylan E, Kabak M, Dikmen AU (2021) Evaluation of criteria and COVID-19 patients for intensive care unit admission in the era of pandemic: a multi-criteria decision making approach. Comput Methods Progr Biomed 209:106348

Shirazi H, Kia R, Ghasemi P (2020) Ranking of hospitals in the case of COVID-19 outbreak: a new integrated approach using patient satisfaction criteria. Int J Healthc Manag 13(4):312–324

Ortiz-Barrios M, Gul M, López-Meza P, Yucesan M, Navarro-Jiménez E (2020) Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: the case of Turkish hospitals. Int J Disaster Risk Reduct 49:101748

Albahri AS, Hamid RA, Albahri OS, Zaidan A (2021) Detection-based prioritisation: framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated entropy-TOPSIS methods. Artif Intell Med 111:101983

Albahri AS et al (2020) Multi-biological laboratory examination framework for the prioritization of patients with COVID-19 based on integrated AHP and group VIKOR methods. Int J Inf Technol Decis Mak 19(05):1247–1269

De Nardo P et al (2020) Multi-criteria decision analysis to prioritize hospital admission of patients affected by COVID-19 in low-resource settings with hospital-bed shortage. Int J Infect Dis 98:494–500

Mishra AR, Rani P, Krishankumar R, Ravichandran K, Kar S (2021) An extended fuzzy decision-making framework using hesitant fuzzy sets for the drug selection to treat the mild symptoms of Coronavirus Disease 2019 (COVID-19). Appl Soft Comput 103:107155

Xiaozhen Z, Mao J, Yanan L (2020) A new computational method based on probabilistic linguistic Z-number with unbalanced semantics and its application to multi-criteria group decision making. IEEE Access 9:2950–2965

Albahri OS et al (2020) Helping doctors hasten COVID-19 treatment: towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Comput Methods Progr Biomed 196:105617

Mohammed TJ et al (2021) Convalescent-plasma-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on AHP-group TOPSIS and matching component. Appl Intell 51(5):2956–2987

Albahri O et al (2020) Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: taxonomy analysis, challenges, future solutions and methodological aspects. J Infect Public Health 13(10):1381–1396

Alsalem MA et al (2021) Rise of multiattribute decision-making in combating COVID-19: a systematic review of the state-of-the-art literature. Int J Intell Syst 37:3514–3624

Alsalem M et al (2022) Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review. Artif Intell Rev 1–84

Mokhtari A, Mineo C, Kriseman J, Kremer P, Neal L, Larson J (2021) A multi-method approach to modeling COVID-19 disease dynamics in the United States. Sci Rep 11(1):1–16

Sarwar A, Imran M (2021) Prioritizing infection prevention and control activities for SARS-CoV-2 (COVID-19): a multi-criteria decision-analysis method. J Healthc Leadersh 13:77

Botwright S et al (2021) The CAPACITI decision-support tool for national immunization programs. Value Health 24(8):1150–1157

Requia WJ, Kondo EK, Adams MD, Gold DR, Struchiner CJ (2020) Risk of the Brazilian health care system over 5572 municipalities to exceed health care capacity due to the 2019 novel coronavirus (COVID-19). Sci Total Environ 730:139144

Pinho M, Moura A (2021) A decision support system to solve the problem of health care priority-setting. J Sci Technol Policy Manag 13:610–624

Khan F, Ali Y, Pamucar D (2021) A new fuzzy FUCOM-QFD approach for evaluating strategies to enhance the resilience of the healthcare sector to combat the COVID-19 pandemic. Kybernetes 51:1429–1451

Clemente-Suárez VJ et al (2021) Performance of fuzzy multi-criteria decision analysis of emergency system in COVID-19 pandemic. An extensive narrative review. Int J Environ Res Public Health 18(10):5208

Alosaimi W et al (2021) Computational technique for effectiveness of treatments used in curing SARS-CoV-2. Intell Autom Soft Comput 28:617–638

Francis-Oliviero F, Bozoki S, Micsik A, Kieny MP, Lelièvre J-D (2021) Research priorities to increase vaccination coverage in Europe (EU joint action on vaccination). Vaccine 39(44):6539–6544

Zararsız Z, Riaz M (2022) Bipolar fuzzy metric spaces with application. Comput Appl Math 41(1):1–19

MathSciNet   MATH   Google Scholar  

Ozsahin DU, Gelisen MI, Taiwo M, Agachan Y, Rahi D, Uzun B (2021) Decision analysis of the COVID-19 vaccines. EuroBiotech J 5(s1):20–25

Nguyen P-H, Tsai J-F, Dang T-T, Lin M-H, Pham H-A, Nguyen K-A (2021) A hybrid spherical fuzzy MCDM approach to prioritize governmental intervention strategies against the COVID-19 pandemic: a case study from Vietnam. Mathematics 9(20):2626

Jain R, Rana KB, Meena ML (2021) An integrated multi-criteria decision-making approach for identifying the risk level of musculoskeletal disorders among handheld device users. Soft Comput https://doi.org/10.1007/s00500-021-05592-w

Ahmad S, Mehfuz S, Beg J, Khan NA, Khan AH (2021) Fuzzy cloud based COVID-19 diagnosis assistant for identifying affected cases globally using MCDM. Mater Today Proc

Sen G, Demirel E, Avci S, Aladag Z (2021) Evaluation of effective risk factors in COVID-19 mortality rate with DEMATEL method. J Fac Eng Archit Gazi Univ 36(4):2151–2166

Drnovšek R, MilavecKapun M, Rajkovič U (2021) Multi-criteria risk evaluation model for developing ventilator-associated pneumonia. Cent Eur J Oper Res 29(3):1021–1036

Malakar S (2021) Geospatial modelling of COVID-19 vulnerability using an integrated fuzzy MCDM approach: a case study of West Bengal, India. Model Earth Syst Environ 8(3):3103–3116

Naeem K, Riaz M, Peng X, Afzal D (2020) Pythagorean m-polar fuzzy topology with TOPSIS approach in exploring most effectual method for curing from COVID-19. Int J Biomath 13(08):2050075

Al-shami TM, Ciucci D (2022) Subset neighborhood rough sets. Knowl Based Syst 237:107868

Al-shami TM (2021) Improvement of the approximations and accuracy measure of a rough set using somewhere dense sets. Soft Comput 25(23):14449–14460

MATH   Google Scholar  

Al-shami TM (2022) Topological approach to generate new rough set models. Complex Intell Syst 8:4101–4113 https://doi.org/10.1007/s40747-022-00704-x

Lega F (2005) Strategies for multi-hospital networks: a framework. Health Serv Manag Res 18(2):86–99

Bonawitz K et al (2019) Towards federated learning at scale: system design. arXiv preprint arXiv:1902.01046

Vaid A et al (2021) Federated learning of electronic health records to improve mortality prediction in hospitalized patients with COVID-19: machine learning approach. JMIR Med Inform 9(1):e24207

Wang R, Xu J, Ma Y, Talha M, Al-Rakhami MS, Ghoneim A (2021) Auxiliary diagnosis of COVID-19 based on 5G-enabled federated learning. IEEE Netw 35(3):14–20

Chigutsa E, O’Brien L, Ferguson-Sells L, Long A, Chien J (2021) Population pharmacokinetics and pharmacodynamics of the neutralizing antibodies bamlanivimab and etesevimab in patients with mild to moderate COVID-19 infection. Clin Pharmacol Ther 110(5):1302–1310. https://doi.org/10.1002/cpt.2420

Article   Google Scholar  

Dougan M et al (2021) Bamlanivimab plus etesevimab in mild or moderate Covid-19. N Engl J Med 385(15):1382–1392

Mornese Pinna S et al (2021) Monoclonal antibodies for the treatment of COVID-19 patients: an umbrella to overcome the storm? Int Immunopharmacol 101:108200. https://doi.org/10.1016/j.intimp.2021.108200

Suárez-García I et al (2021) In-hospital mortality among immunosuppressed patients with COVID-19: analysis from a national cohort in Spain. PLoS ONE 16(8):e0255524

Bollyky TJ, Gostin LO, Hamburg MA (2020) The equitable distribution of COVID-19 therapeutics and vaccines. JAMA 323(24):2462–2463

Persad G, Peek ME, Emanuel EJ (2020) Fairly prioritizing groups for access to COVID-19 vaccines. JAMA 324(16):1601–1602

Shalev D, Shapiro PA (2020) Epidemic psychiatry: the opportunities and challenges of COVID-19. Gen Hosp Psychiatry 64:68

Azad MA et al (2020) A first look at privacy analysis of COVID-19 contact tracing mobile applications. IEEE Internet Things J 8(21):15796–15806

Daggubati LC et al (2020) Telemedicine for outpatient neurosurgical oncology care: lessons learned for the future during the COVID-19 pandemic. World Neurosurg 139:e859–e863

Feki I, Ammar S, Kessentini Y, Muhammad K (2021) Federated learning for COVID-19 screening from chest X-ray images. Appl Soft Comput 106:107330

Dispinseri S et al (2021) Neutralizing antibody responses to SARS-CoV-2 in symptomatic COVID-19 is persistent and critical for survival. Nat Commun 12(1):2670. https://doi.org/10.1038/s41467-021-22958-8

Pacific W, Hasan SAWJU (2021) Interim statement on booster doses for COVID-19 vaccination. 22

M. D. O. HEALTH (2021) Ethical framework for allocation of monoclonal antibodies during the COVID-19 pandemic. MN, USA. [Online]. https://www.health.state.mn.us/diseases/coronavirus/hcp/mabethical.pdf Accessed on April 2022

Zaidan AA, Zaidan BB, Al-Haiqi A, Kiah MLM, Hussain M, Abdulnabi M (2015) Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. J Biomed Inform 53:390–404

Abdulkareem KH et al (2020) A novel multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques. Int J Inf Technol Decis Mak 19(03):909–957

Albahri A, Hamid RA, Albahri O, Zaidan AA (2020) Detection-based prioritisation: framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods. Artif Intell Med 111:101983

Chen H, Liu H, Chu X, Zhang L, Yan B (2020) A two-phased SEM-neural network approach for consumer preference analysis. Adv Eng Inform 46:101156

Nair DJ, Rashidi TH, Dixit VVJS-EPS (2017) Estimating surplus food supply for food rescue and delivery operations. Socio-Econ Plan Sci 57:73–83

Raut RD, Priyadarshinee P, Gardas BB, Jha MKJTF, Change S (2018) Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach. Technol Forecast Soc Change 134:98–123

Raut RD, Mangla SK, Narwane VS, Gardas BB, Priyadarshinee P, Narkhede B (2019) Linking big data analytics and operational sustainability practices for sustainable business management. J Clean Prod 224:10–24

Pang J, Huang Y, Xie Z, Li J, Cai Z (2021) Collaborative city digital twin for the COVID-19 pandemic: a federated learning solution. Tsinghua Sci Technol 26(5):759–771

Ouyang L, Yuan Y, Cao Y, Wang F-Y (2021) A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts. Inf Sci 570:124–143

Zaidan AA, Zaidan BB, Hussain M, Haiqi A, Mat Kiah ML, Abdulnabi M (2015) Multi-criteria analysis for OS-EMR software selection problem: a comparative study. Decis Support Syst 78(1):15–27. https://doi.org/10.1016/j.dss.2015.07.002

Chou S-Y, Chang Y-H, Shen C-Y (2008) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. Eur J Oper Res 189(1):132–145. https://doi.org/10.1016/j.ejor.2007.05.006

Article   MATH   Google Scholar  

Önüt S, Soner S (2008) Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. Waste Manag 28(9):1552–1559. https://doi.org/10.1016/j.wasman.2007.05.019

Karahalios H (2017) The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators. Transp Res Part D Transport Environ 52(Part A):172–184. https://doi.org/10.1016/j.trd.2017.03.001

Yang T, Zhang Q, Wan X, Li X, Wang Y, Wang W (2020) Comprehensive ecological risk assessment for semi-arid basin based on conceptual model of risk response and improved TOPSIS model-a case study of Wei River Basin, China. Sci Total Environ 719:137502

Lin M, Chen Z, Xu Z, Gou X, Herrera F (2021) Score function based on concentration degree for probabilistic linguistic term sets: an application to TOPSIS and VIKOR. Inf Sci 551:270–290

Yu X, Wu X, Huo T (2020) Combine MCDM methods and PSO to evaluate economic benefits of high-tech zones in China. Sustainability 12(18):7833

Ding Z, Jiang Z, Zhang H, Cai W, Liu Y (2020) An integrated decision-making method for selecting machine tool guideways considering remanufacturability. Int J Comput Integr Manuf 33(7):686–700

Zhao Y, Su H, Wan J, Feng D, Gou X, Yu B (2020) Complementarity evaluation index system and method of multiple power sources. In: 2020 IEEE 3rd student conference on electrical machines and systems (SCEMS). IEEE, pp 200–206

Wu B, Lu M, Huang W, Lan Y, Wu Y, Huang Z (2020) A case study on the construction optimization decision scheme of urban subway tunnel based on the TOPSIS method. KSCE J Civ Eng 24(11):3488–3500

Deng Y et al (2021) Thermo-chemical water splitting: selection of priority reversible redox reactions by multi-attribute decision making. Renew Energy 170:800–810

Wang L, Yan F, Wang F, Li Z (2021) FMEA-CM based quantitative risk assessment for process industries—a case study of coal-to-methanol plant in China. Process Saf Environ Prot 149:299–311

Singh AK, Avikal S, Kumar KN, Kumar M, Thakura P (2020) A fuzzy-AHP and M-TOPSIS based approach for selection of composite materials used in structural applications. Mater Today Proc 26:3119–3123

Lv L, Deng Z, Meng H, Liu T, Wan L (2020) A multi-objective decision-making method for machining process plan and an application. J Clean Prod 260:121072

Zhang X, Lu J, Peng Y (2021) Hybrid MCDM model for location of logistics hub: a case in china under the belt and road initiative. IEEE Access 9:41227–41245

Liu J, Liu W, Jin L, Tu T, Ding Y (2020) A performance evaluation framework of electricity markets in China. In: 2020 5th Asia conference on power and electrical engineering (ACPEE). IEEE, pp 1043–1048

Tang H, Fang F (2018) A novel improvement on rank reversal in TOPSIS based on the efficacy coefficient method. Int J Internet Manuf Serv 5(1):67–84

Wang T-C, Lee H-D (2009) Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Syst Appl 36(5):8980–8985

Nigim K, Munier N, Green J (2004) Pre-feasibility MCDM tools to aid communities in prioritizing local viable renewable energy sources. Renew Energy 29(11):1775–1791

Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49–57

Pamučar D, Stević Ž, Sremac S (2018) A new model for determining weight coefficients of criteria in mcdm models: full consistency method (fucom). Symmetry 10(9):393

Mohammed RT et al (2022) Determining importance of many-objective optimisation competitive algorithms evaluation criteria based on a novel fuzzy-weighted zero-inconsistency method. Int J Inf Technol Decis Mak 1(1):1–47. https://doi.org/10.1142/s0219622021500140

Article   MathSciNet   Google Scholar  

Mohammed R et al (2021) Determining importance of many-objective optimisation competitive algorithms evaluation criteria based on a novel fuzzy-weighted zero-inconsistency method. Int J Inf Technol Decis Mak 21(01):195–241

Download references

Author information

Authors and affiliations.

Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia

A. H. Alamoodi

Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Yunlin, 64002, Taiwan, ROC

B. B. Zaidan

Computer Techniques Engineering Department, Mazaya University College, Nasiriyah, Iraq

O. S. Albahri

Department of Computing, Faculty of Arts, Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia

Salem Garfan & Mohammed S. Al-Samarraay

Computer Science Department, College of Information Technology, Hebron University, Hebron, Palestine

Ibraheem Y. Y. Ahmaro

Department of Computing Science, Komar University of Science and Technology (KUST), Sulaymaniyah, Iraq

R. T. Mohammed

SP Jain School of Global Management, Sydney, Australia

A. A. Zaidan

Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia

Amelia Ritahani Ismail

Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq

A. S. Albahri

E-Business and Commerce Department, Faculty of Administrative and Financial Sciences, University of Petra, Amman, 961343, Jordan

Fayiz Momani

Foundation of Alshuhda, Baghdad, Iraq

Ali Najm Jasim

Medical Intrumentation Techniques Engineering Department, Al-Mustaqbal University College, Babylon, Iraq

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to A. H. Alamoodi .

Ethics declarations

Conflict of interest.

The authors declare no conflict of interest. We ensure the availability of data and material and code.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Alamoodi, A.H., Zaidan, B.B., Albahri, O.S. et al. Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions. Complex Intell. Syst. 9 , 4705–4731 (2023). https://doi.org/10.1007/s40747-023-00972-1

Download citation

Received : 27 July 2022

Accepted : 01 January 2023

Published : 03 February 2023

Issue Date : August 2023

DOI : https://doi.org/10.1007/s40747-023-00972-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Data privacy
• Monoclonal antibodies
• Multi-criterion decision making

Arabic Keywords

• خصوصية البيانات
• التعلم الاتحادي
• الأجسام المضادة وحيدة النسيلة
• صنع القرار متعدد المعايير
• Find a journal
• Publish with us
• Track your research

Medicine: Case Reports and Study Protocols

• Get new issue alerts Get alerts

Secondary Logo

Journal logo, current issue.

August 2024 - Volume 5 - Issue 8

• Editor-in-Chief: Sayali Sable
• ISSN: 2691-3895
• Frequency: Continuous article-based

Latest Articles

View More Recent Articles

Colleague's E-mail is Invalid

Your message has been successfully sent to your colleague.

Save my selection

Current Issue Highlights

• Clinical Case Report

Rapid alleviation of perioperative airway obstruction through positional adjustments in a patient with a giant anterior mediastinal mass: A case report

Medicine: Case Reports and Study Protocols. 5(8):e00335, August 2024.

• Abstract Abstract
• Permissions

Go to Full Text of this Article

Most Popular

• Most Viewed
• Most Emailed
• Incomplete abortion with elevated...
• Severe iron-deficiency anemia and...
• A case report of isoniazid adverse ...
• A case report of a young woman...
• Acinetobacter ursingii</em> occult bacteremia in a healthy 9-month-old girl: A case report', 'Yoshida Rei MD; Narita, Masashi MD; Hachiman, Teruyuki BS', 'Medicine: Case Reports and Study Protocols', 'November 2020', '1', '1' , 'p e0011');" onmouseout="javascript:Tooltip_MouseOut()">Community-acquired Acinetobacter...

Writing a Case Report

This page is intended for medical students, residents or others who do not have much experience with case reports, but are planning on writing one.  

What is a case report?  A medical case report, also known as a case study, is a detailed description of a clinical encounter with a patient.  The most important aspect of a case report, i.e. the reason you would go to the trouble of writing one, is that the case is sufficiently unique, rare or interesting such that other medical professionals will learn something from it.   

Case reports are commonly of the following categories :

- Rare diseases

- Unusual presentation of disease

- Unexpected events

- Unusual combination of diseases or conditions

- Difficult or inconclusive diagnosis

- Treatment or management challenges

- Personal impact

- Observations that shed new light on a disease or condition

- Anatomical variations

It is important that you recognize what is unique or interesting about your case, and this must be described clearly in the case report.

Case reports generally take the format of :

1. Background

2. Case presentation

3. Observations and investigation

4. Diagnosis

5. Treatment

7. Discussion

Does a case report require IRB approval?

Case reports typically discuss a single patient. If this is true for your case report, then it most likely does not require IRB approval because it not considered research.    If you have more than one patient, your study could qualify as a Case Series, which would require IRB review.  If you have questions, you chould check your local IRB's guidelines on reviewing case reports.

Are there other rules for writing a case report?

First, you will be collecting protected health information, thus HIPAA applies to case reports.   Spectrum Health has created a very helpful guidance document for case reports, which you can see here:   Case Report Guidance - Spectrum Health

While this guidance document was created by Spectrum Health, the rules and regulations outlined could apply to any case report.  This includes answering questions like: Do I need written HIPAA authorization to publish a case report?  When do I need IRB review of a case report?  What qualifies as a patient identifier?

How do I get started?

1. We STRONGLY encourage you to consult the CARE Guidelines, which provide guidance on writing case reports -  https://www.care-statement.org/

Specifically, the checklist -  https://www.care-statement.org/checklist  - which explains exactly the information you should collect and include in your case report.  

2. Identify a case.  If you are a medical student, you may not yet have the clinical expertise to determine if a specific case is worth writing up.  If so, you must seek the help of a clinician.  It is common for students to ask attendings or residents if they have any interesting cases that can be used for a case report. 

3. Select a journal or two to which you think you will submit the case report.   Journals often have specific requirements for publishing case reports, which could include a requirement for informed consent, a letter or statement from the IRB and other things.  Journals may also charge publication fees (see Is it free to publish? below)   

4. Obtain informed consent from the patient (see " Do I have to obtain informed consent from the patient? " below).  Journals may have their own informed consent form that they would like you to use, so please look for this when selecting a journal.

Once you've identified the case, selected an appropriate journal(s), and considered informed consent, you can collect the required information to write the case report.

How do I write a case report?

Once you identify a case and have learned what information to include in the case report, try to find a previously published case report.  Finding published case reports in a similar field will provide examples to guide you through the process of writing a case report.    

One journal you can consult is BMJ Case Reports .  MSU has a multi-year open access publishing agreement with the publisher BM J , and an institutional fellowship with BMJ Case Reports which allows MSU faculty, staff and students to publish in this journal for free.  See this page for a link to the journal and more information on publishing-    https://lib.msu.edu/collections/scholcomm/support

There are numerous other journals where you can find published case reports to help guide you in your writing. 

Do I have to obtain informed consent from the patient?

The CARE guidelines recommend obtaining informed consent from patients for all case reports.  Our recommendation is to obtain informed consent from the patient.  Although not technically required, especially if the case report does not include any identifying information, some journals require informed consent for all case reports before publishing.  The CARE guidelines recommend obtaining informed consent AND the patient's perspective on the treatment/outcome (if possible).  Please consider this as well.  

If required, it is recommended you obtain informed consent before the case report is written.

An example of a case report consent form can be found on the BMJ Case Reports website, which you can access via the MSU library page -  https://casereports.bmj.com/ .  Go to "Instructions for Authors" and then "Patient Consent" to find the consent form they use.  You can create a similar form to obtain consent from your patient.  If you have identified a journal already, please consult their requirements and determine if they have a specific consent form they would like you to use.

Seek feedback

Once you have written a draft of the case report, you should seek feedback on your writing, from experts in the field if possible, or from those who have written case reports before.   

Selecting a journal

Aside from BMJ Case Reports mentioned above, there are many, many journals out there who publish medical case reports.   Ask your mentor if they have a journal they would like to use.  If you need to select on your own, here are some strategies:

1. Do a PubMed search.  https://pubmed.ncbi.nlm.nih.gov/

   a. Do a search for a topic, disease or other feature of your case report 

   b. When the results appear, on the left side of the page is a limiter for "article type".  Case reports are an article type to which you can limit your search results.  If you don't see that option on the left, click "additional filters". 

   c. Review the case reports that come up and see what journals they are published in.

2. Use JANE -  https://jane.biosemantics.org/

3. Check with specialty societies.  Many specialty societies are affiliated with one or more journal, which can be reviewed for ones that match your needs

4. Search through individual publisher journal lists.  Elsevier publishes many different medical research journals, and they have a journal finder, much like JANE  ( https://journalfinder.elsevier.com/ ).  This is exclusive to Elsevier journals.  There are many other publishers of medical journals for review, including Springer, Dove Press, BMJ, BMC, Wiley, Sage, Nature and many others.

Is it free to publish ?

Be aware that it may not be free to publish your case report.  Many journals charge publication fees. Of note, many open access journals charge author fees of thousands of dollars.  Other journals have smaller page charges (i.e. $60 per page), and still others will publish for free, with an "open access option".  It is best practice to check the journal's Info for Authors section or Author Center to determine what the cost is to publish.  MSU-CHM does NOT have funds to support publication costs, so this is an important step if you do not want to pay out of pocket for publishing

*A more thorough discussion on finding a journal, publication costs, predatory journals and other publication-related issues can be found here:   https://research.chm.msu.edu/students-residents/finding-a-journal

Gagnier JJ, Kienle G, Altman DG, Moher D, Sox H, Riley D. 2013. The CARE guidelines: Consensus-based clinical case reporting guideline development.  Glob Adv Health Med . 2:38-43. doi:  10.7453/gahmj.2013.008

Riley DS, Barber MS, Kienle GS, AronsonJK, von Schoen-Angerer T, Tugwell P, Kiene H, Helfand M, Altman DG, Sox H, Werthmann PG, Moher D, Rison RA, Shamseer L, Koch CA, Sun GH, Hanaway P, Sudak NL, Kaszkin-Bettag M, Carpenter JE, Gagnier JJ. 2017. CARE guidelines for case reports: explanation and elaboration document. J Clin Epidemiol . 89:218-234. doi: 10.1016/j.jclinepi.2017.04.026  

Guidelines to writing a clinical case report. 2017. Heart Views . 18:104-105. doi:  10.4103/1995-705X.217857

Ortega-Loubon C, Culquichicon C, Correa R. The importance of writing and publishing case reports during medical education. 2017. Cureus. 9:e1964. doi:  10.7759/cureus.1964

Writing and publishing a useful and interesting case report. 2019. BMJ Case Reports.  Link to document

Camm CF. Writing an excellent case report: EHJ Case Reports , Case of the Year 2019. 2020. European Heart Jounrnal. 41:1230-1231.  https://doi.org/10.1093/eurheartj/ehaa176  

*content developed by Mark Trottier, PhD

• In the News
• Impact Videos and Stories
• Frequently Asked Questions
• Policies, Disclosures and Reports

Explore Our Resources

Search for case studies, audio interviews, videos, and more.

Search for:

Clear Filters

Filter by Type

• All Categories
• Case Studies
• Medical Ethics and Policy Guidance
• Shared Decision Making and Advance Care Planning

Filter by Category

• Ethical Theory and Principles (23)
• Informed Consent (6)
• Medical Ethics (38)
• Resource Allocation (10)
• Patient/Physician Relationship (43)
• Pediatrics (3)
• Public and Population Health (71)
• Religion and Morality (14)
• Advance Care Planning (42)
• End of Life Ethics (81)
• Biotechnologies and Genomics (1)
• Procreation and Reproduction (6)
• Research Ethics (17)

Case Study – ECMO and Ethics

Case Study – Moral Culpability for Respecting Patients’ Autonomy

Case Study – Decisional Capacity of the Patient’s Surrogate

Case Study – A Multidisciplinary Healthcare Team Disagrees

Case Study – Whose Decision?

Case Study –Too little, too late… almost

Case Study – Trying to Honor Johnny’s Wishes

Case Study – “God will restore his leg. The doctors will see.” Patient Nonadherence.

Case Study – Moral Dimensions of Medical Negligence

Redirect Notice

Inclusion across the lifespan in human subjects research.

Learn about the Inclusion Across the Lifespan policy and how to comply with this policy in applications and progress reports. All human subjects research supported by NIH must include participants of all ages, including children and older adults, unless there are scientific or ethical reasons not to include them.

The purpose of the Inclusion Across the Lifespan Policy is to ensure individuals are included in clinical research in a manner appropriate to the scientific question under study so that the knowledge gained from NIH-funded research is applicable to all those affected by the researched diseases/conditions. The policy expands the Inclusion of Children in Clinical Research Policy to include individuals of all ages, including children and older adults . The policy also requires that the age at enrollment of each participant be collected in progress reports.

Implementation

The Inclusion Across the Lifespan policy is now in effect, and applies to all grant applications submitted for due dates on or after January 25, 2019 . The policy also applies to solicitations for Research & Development contracts issued January 25, 2019 or later, and intramural studies submitted on/after this date. Ongoing, non-competing awards will be expected to comply with the policy at the submission of a competing renewal application. Research that was submitted before January 25, 2019 continues to be subject to the Inclusion of Children in Clinical Research Policy .

Applications & Proposals

Applications and proposals involving human subjects research must address plans for including individuals across the lifespan in the PHS Human Subjects and Clinical Trial Information Form. Any age-related exclusions must include a rationale and justification based on a scientific or ethical basis. Refer to the PHS Human Subjects and Clinical Trial Information Form Instructions for complete guidance on what to address.

Peer Review

Scientific Review Groups will assess each application/proposal as being "acceptable" or "unacceptable" with regard to the age-appropriate inclusion or exclusion of individuals in the research project. For additional information on review considerations, refer to the Guidelines for the Review of Inclusion in Clinical Research . For information regarding the coding used to rate inclusion during peer review, see the list of NIH Peer Review Inclusion Codes .

Progress Reports

NIH recipients/offerors must submit individual-level data on participant age at enrollment in progress reports. Age at enrollment must be provided along with information on sex or gender, race, and ethnicity in the Inclusion Enrollment Report. Units for reporting age at enrollment range from minutes to years.

Policy Notices

Upcoming Events

DHSR One pager of resources for external users

• Human Subjects Research
• National Institute on Aging
• National Institute of Child Health and Human Development
• For NIH Staff

Have additional questions? Contact your program officer or the Inclusion policy team: [email protected]

• Cette page n'est pas disponible en Français

Case Study on the Use of Integrated Approaches for Testing and Assessment (IATA) for Chronic Toxicity and Carcinogenicity of Agrichemicals with Exemplar Case Studies - Ninth Review Cycle (2023)

• Environment
• Chemical safety and biosafety
• Assessment of chemicals
• Testing of chemicals

Cite this content as:

The objective of the Integrated Approaches for Testing and Assessment (IATA) Case Studies Project is to increase experience with the use of IATA by developing case studies which constitute examples of predictions that are fit for regulatory use. The aim of this project is to create common understanding of using novel methodologies and the generation of considerations/guidance stemming from these case studies. This case study was developed by the International Council on Animal Protection in OECD Programmes (ICAPO) to illustrate practical uses of IATA, and was submitted to the 2023 review cycle of the IATA Case Studies Project. The case study provides a framework to fulfil an IATA for chronic toxicity and carcinogenicity assessment through a weight of evidence (WoE)-based approach, in the absence of rodent cancer bioassays. The purpose of this IATA is to illustrate the use of the Rethinking Carcinogenicity Assessment for Agrichemicals Project (ReCAAP) framework, which is a scientific, WoE-based approach that allows the estimation of a Point of Departure (POD) for use in agrochemical risk assessment. To illustrate the use of the ReCAAP framework, two examples are presented in this IATA.

In the same series

Related publications

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 24 September 2024

Influence of sustainable waste granite, marble and nano-alumina additives on ordinary concretes: a physical, structural, and radiological study

• Alaa A. Mahmoud 1 , 2 ,
• Alaa A. El-Sayed 1 ,
• Ayman M. Aboraya 3 ,
• Islam N. Fathy 1 , 2 ,
• Mohamed A. Abouelnour 1 &
• Islam M. Nabil   ORCID: orcid.org/0000-0002-7020-9593 4  

Scientific Reports volume  14 , Article number:  22011 ( 2024 ) Cite this article

Metrics details

• Applied physics
• Materials science
• Nuclear physics

This study investigates the individual and combined effects of enhancing the radiation shielding properties of waste concrete using the optimal mix design of two waste material powders of different compositions. Marble (MD) and granite (GD) waste dust were individually utilized as partial replacements for cement at a replacement ratio of 6%. Furthermore, two additional mixes were prepared by incorporating 1% by cement weight of nano alumina (NA) to enhance the microstructure of the studied waste concrete. The MGA-concrete was analyzed using X-ray Fluorescence, Energy dispersive X-ray, X-ray diffraction analysis, transmission electron microscopy, and scanning electron microscope techniques. The radiation shielding assets of the examined Concrete samples, such as the linear attenuation coefficient (μ), half value layer (H 1/2 ), tenth value layer (T 1/10 ), and fast neutron removal cross-section were evaluated using the MCS5 Monte Carlo simulation algorithm and Phy-X software. The results showed that the linear attenuation for the GMN-concretes’ order is CO < MD < GD < NA < MD + NA < GD + NA. The GD + Na concrete sample presents the best neutron performance. The studied GMN-concrete samples provide the best protection against γ-rays and fast neutrons. Lastly, the excellent performance of the mixes of waste Granite, Marble, and Nano-Alumina on ordinary would pave the way for their employment as radiation shielding in various nuclear and medical facilities.

Similar content being viewed by others

Mechanical properties of sustainable concrete comprising various wastes

Radiation and mechanical performance of cementitious materials containing ecofriendly nano laboratory waste glass

Effect of bismuth oxide nanoparticle on the electromagnetic interference shielding and thermal stability of industrial waste based-geopolymer composites

Introduction.

These days, many industrial, medical, and nuclear settings use machines that make artificial ionizing radiation, like X-rays and γ-rays. This is possible because of advances in technology 1 , 2 , 3 . But, cancer, nausea, vomiting, and, in extreme cases, death, are some of the negative health effects that can result from long-term and excessive exposure to this radiation 4 , 5 . Tissue water molecules become ionized when high-energy photons interact with them. Because it damages DNA's outside and inside, this ionization is dangerous to DNA 6 . The environment, animals, and humans are all at risk from gamma/X-rays and neutrons. Finding better materials for radiation attenuation and shielding is an intriguing topic for many researchers for these reasons 7 , 8 , 9 , 10 . It is well knowledge that shielding and attenuation materials can reduce the amount of radiation that workers are exposed to by establishing a barrier between the radiation sources and the location where they are located or the workers themselves.

In order to reduce the negative effects of radiation, one of the fundamental concepts of radiation protection is the selection of proper shielding materials. This is an essential step in the process. It is still a challenge for researchers to gain a handle on this particular aspect. Research on the radiation-shielding capabilities of a wide variety of materials, such as synthetic and natural rubber, concrete, brick, metal, and polymers, may be found in abundance in the published literature 11 , 12 , 13 , 14 . By utilizing this knowledge, engineers are able to develop cutting-edge materials that exhibit specific traits and capabilities that were previously unreachable within the area of material science. These materials are able to be created by applying this information. Once that was accomplished, these materials would be utilized in a wide range of technological sectors worldwide. When it comes to selecting radiation shielding materials, the most important factor to take into account is the ability of different materials to offer protection against ionizing radiation. Particles of cement, borate glasses, fibers, and polymers are some examples of the types of materials that can be utilized to provide protection against radiation 15 . The complexity of these materials can range from simple to quite complex 16 , 17 , 18 . The ability of a material to absorb or diminish radiation is a primary consideration in the selection of materials for radiation attenuation. Lead and concrete are two materials that are frequently used because of their capacity to either absorb or distribute radiation. Among other things, boron has the ability to absorb neutrons 19 , 20 , 21 . Materials are chosen considering exposure rate reduction, source kind, physical constraints, and cost-effectiveness. Shielding applications in nuclear engineering extensively use gypsum, lead, glass, and cement 22 , 23 , 24 . Direct shielding applications and nuclear power plant construction use these materials 25 , 26 . Magnesium borosilicate glasses exhibit superior radiation shielding capabilities compared to traditional glass materials. Increasing ZnO content in the composite enhances neutron shielding properties. A novel glass system composed of 57.6% TeO 2 , 38.4% ZnO, and 4% NiO has been developed and evaluated for its radiation shielding capabilities 27 . The construction sector is significant in global resource extraction, consuming 40% of materials and contributing 50% of global greenhouse gas emissions 28 . As a consequence of this, construction operations result in the generation of significant quantities of garbage, which frequently finds its way into landfills. One of the most important components of the building industry is the manufacture of concrete, which is a construction material. The production process, on the other hand, requires a significant number of resources, with aggregates, cement, and water being the primary components. The output of cement around the world has increased, and it is projected to reach 4.4 billion tons in 2022. This is a 175% spike in production since the beginning of the third millennium 29 . This production process is associated with substantial carbon dioxide emissions, with approximately 1 ton of CO2 released for every ton of ordinary portland cement produced. Cement manufacturing contributes about 7% of global annual carbon dioxide emissions, positioning it as the third largest industrial emitter 30 . As an alternative to clinker or as direct mineral additives in concrete, supplementary cementitious materials (SCMs) such fly ash, calcined clays, slags, and natural pozzolans are utilized in order to mitigate the impact that this industry on the environment 31 . The current study represents an extension of a previously published study 32 , where the authors utilized varying proportions of marble and granite powders as partial replacements for cement while investigating their effects on concrete's mechanical, physical, and microstructural properties. The results revealed a significant improvement in all properties of the produced waste concrete with varying replacement ratios, with a relative superiority observed for the optimal replacement ratio at 6% for both Marble dust (MD) and Granite dust (GD). Additionally, the practical program involved harnessing the capabilities of nanotechnology by incorporating varying proportions of Nano alumina (NA) into the concrete mixes, where the results demonstrated that adding 1% by weight of NA is the optimum ratio. The second phase of the experimental program involved optimizing the results by using the optimal replacement ratios for both MD and GD, along with a 1% addition of NA. This improved the resulting concrete's mechanical properties and gave it a denser and more compact microstructure. Through the current study, the previously tested optimal replacement ratios were experimented with to investigate the impact of using waste materials and NA on the concrete's shielding properties to various radiation forms. The use of NA at small replacement ratios as a substitute for cement has shown the ability to enhance the concrete's shielding to gamma-ray penetration 33 . The reason for this is that it has the capacity to enhance the internal microstructure of concrete, so making it denser and more compact. This, in turn, disrupts the paths via which radiation is able to infiltrate. In spite of the fact that the effects of marble and granite powders are being investigated for the first time in radiation shielding concretes, the results of the literature that have been reported on the notable positive impacts on the microstructural level and density of the concrete that is produced at optimal usage ratios are encouraging in this regard. This notion is further confirmed by a number of earlier studies that have proven a significant improvement in the radiation resistance qualities of concrete, particularly with regard to gamma radiation, when materials with chemical and mineral compositions that are comparable to those of waste powders made from marble or granite are utilized 34 , 35 , 36 .

This work investigates the individual and combined effects of enhancing the radiation shielding properties of waste concrete using the optimal mix design of two waste material powders of different compositions. MD and GD were individually utilized as partial replacements for cement at a replacement ratio of 6%. Furthermore, two additional mixes were prepared by incorporating 1% by cement weight of NA to enhance the microstructure of the studied waste concrete. The MGA-concrete was analyzed using X-ray Fluorescence (XRF), Energy dispersive X-ray (EDX), X-ray diffraction analysis (XRD), Transmission Electron Microscopy (TEM), and Scanning Electron Microscope (SEM) techniques. The radiation shielding assets of the examined Concrete samples, such as the linear attenuation coefficient (μ), half value layer (H 1/2 ), and tenth value layer (T 1/10 ), were evaluated using the MCS Monte Carlo simulation algorithm and Phy-X software. The MCS code was also used to determine the fast neutron removal cross-section (GMN FNRCS ), their half-value length (GMN HVLFNRCS ), and relaxation length (GMN λFNRCS ). Most of the studied radiation attenuation parameters were compared to some commonly used glasses and concretes.

Materials and mix design

Materials properties, cement, aggregates, and water.

During the course of this investigation, the conventional ordinary Portland cement (OPC) type I grade 52.5 N was utilized. The average particle size of this cement was 9 μm, and it adhered to the specifications set forth by ASTM C 150 37 . The cement that was used has a specific gravity of 3.15 and a surface area of 3500 cm 2 /g. The information regarding the chemical composition of the cement is presented in Table 1 , which allows for easier comprehension. Sand that was naturally siliceous was used as the fine aggregate, while crushed dolomite with a maximum nominal size of 19 mm was used as the coarse aggregate. For the purposes of the concrete mixing and curing procedures, fresh, clean water that satisfies the requirements indicated in ASTM C1602/C1602M 37 was utilized 38 .

Waste material powders

The marble and granite dust were sourced from ornamental stone factories in the Shaq El-Thu’ban area, Egypt, representing a by-product generated during the cutting, shaping, and polishing processes of Karara marble and red granite. Initially present in a wet state, the dust dried at 100 °C for two hours in a laboratory oven to ensure consistent W/C ratios within the concrete mixes. Subsequently, the dried dust was ground in a ball mill for ten minutes to eliminate agglomerates and then sieved through a #200 sieve to obtain particles with a size less than 75 microns, suitable for cement replacement. The comparison between marble and granite dusts reveals distinct characteristics. Marble dust, typically white, boasts a specific gravity of 2.64 and a surface area of 7600 cm 2 .g −1 . Its average particle size (D50) is 5.1 µm. In contrast, granite dust exhibits a grayish hue, a slightly higher specific gravity of 2.73, and a significantly larger surface area of 14,650 cm 2 .g −1 . Notably, granite dust particles are finer, with an average size (D50) of 2.5 µm. These differences in color, density, surface area, and particle size influence the potential applications of each material. The final appearance of the used waste powders after preparation is shown in Fig.  1 .

Granite and marble dusts after preparation.

Nano alumina

This investigation incorporates commercially available, high-purity (> 99%) spherical nano-alumina particles with an average diameter of 20 nm ± 5 nm. Notably, these nanoparticles (shown in Fig.  2 ) possess a substantial surface area of 175 m 2 .g −1 and density of 0.3 g.cm −3 , characteristics that are anticipated to influence their effectiveness in diverse applications.

Nano alumina used in the work.

In addition to the control mix, five blends were designed to represent the individual and combined optimal replacement ratios of the investigated materials as partial replacements for cement. In the case of individual replacement, the ratios that achieved the best mechanical strength and improved microstructure of the resulting concrete in the literature research 32 were adopted for both MD, GD, and NA at 6%, 6%, and 1%, respectively. Additionally, two blends were prepared, each representing the optimal addition ratio of the waste material powders along with a 1% NA.

Theoretic base

Γ-attenuation.

The radiation performance of the materials can be described using a variety of attenuation coefficients which are as follows 39 , 40 , 41 , 42 , 43 :

The symbol I represents the strength of the γ-rays that have entered the substance. All of the following are represented by Io: the mass attenuation (μm), the half-value layer (H 1/2 ), the tenth value layer (T 1/10 ), the mean free path (MFp), and the intensity of the main gamma without the material. The thickness of the material is represented by x, to the contrary.

Neutron attenuation

The determination of the neutron attenuation potential of the materials that have been mentioned can be accomplished by computing the fast neutron removal cross-section (FNRCS) by employing the equation FNRCS = \(\sum_{i}{W}_{i}\) x ρ 44 , 45 , 46 . The sign \({W}_{i}\) is used to represent the partial density, while the symbol σ was used to represent the density of the material, and the subscript i was used to represent the mass-cross-section (σ) of the component 47 , 48 , 49 . The half-value layer (HVL FNRCS ) was determined using the formula. \({HVL}_{\text{FNRCS}} = \frac{ln2}{FNRCS}\) , and the relaxation length (λ FNRCS ) was calculated as \(\frac{1}{FNRCS}\) 18 , 50 , 51 , 52 , 53 .

Characterizations

Methods such as XRF, EDX, XRD, TEM, and SEM were employed to investigate the microstructure, particle size, crystal structure, and mineralogical makeup of the dust in order to identify the various pure and mixed materials that comprise the GMN-Concrete samples system.

Radiation shielding measurements

Using the Monte Carlo technique, the code is built to mimic real-world particles. In order to predict the theoretical strength of γ-rays released by γ-point sources, the MCS simulation system was employed. An energetic γ-emitter source operating in the photon energy range (Pγ) of 0.015 ≤ Pγ ≤ 15 in MeV was included in the simulation 54 , 55 . A comparison of the γ-ray intensity before and after passing through the investigated glass materials was the intended objective. Radiation safety and shielding, dose calculation, detector design, and other research fields frequently favor MCS codes 44 , 56 , 57 , 58 , 59 , 60 . Reasons for this preference include these codes' many useful features, such as fast calculations, adaptability to different geometrical designs, and operation across a wide range of energies. This method takes into account various photon interaction mechanisms and attempts to make electrons, neutrons, and γ-rays more mobile. Running an MCS simulation requires precise data on the geometry, source-to-detector distance, source dimensions, and chemical and elemental composition and densities of the concrete samples being examined. This data is found on the SDEF card 61 , 62 . A predetermined two-dimensional and three-dimensional setup served as the basis for the development of the simulation's geometric configuration, which can be seen in Fig.  3 . In accordance with the experimental system, each and every parameter has been recognized as being consistent. Text lines were used to generate the input files so that the MCS simulation could be run. There were six distinct components that comprised the cell, which included a radioactive source, a collimator for 1rays and 2rays γ-radiations, a sample with a cubic shape, and a detector. An SDEF mono γ-energetic flow was identified as a point source of γ-rays for every input file that fell within the range of 0.015 ≤ Pγ ≤ 15 MeV during the analysis. It has been established that the neutron source is a californium spectrum, which functions within the En ≤ 11 MeV range for the purpose of achieving rapid elimination σ attenuation. The specimens emerged in the shape of a cubic layer during the generation process. In addition to this, the densities and elemental compositions of the specimens that were examined were documented in the material card of the text lines. Within a lead collimator that was specifically designed for the 2ry γ-rays, the detector was effectively mounted. By using a Tally command, we may add up all the values from F4:P 56 , 63 . At the same time, the F4:N method calculates the average duration of the γ-rays and neutrons that are emitted by simulated γ/neutron radiation sources. To protect the generated detector, collimators, source, and specimens under investigation, a lead outer shield was used. An Intel Core i5 was utilized in order to carry out the calculations. Multiple NPS (11 7 ) attempts were carried out for every single file in order to guarantee that the random statistical errors remained below 1%. There were approximately thirteen minutes of total runtime for each of the calculations that involved a total of one hundred forty input files.

The energetic view of the radiation attenuation simulation used for the prepared GMN-concrete samples.

Phy-X software

To confirm the accuracy of the MCS model 55 , 64 , the Phy-X/PSD program was utilized. To determine the discrepancies (ϓ., %), the PhyX values for the concrete samples were compared with the MCS results.

Results and discussion

Samples characterization.

XRF analysis was used to determine the chemical composition of MD and GD, and the results are presented in Table 1 . On the other hand, the elemental composition that was determined through EDX analysis is shown in Table 2 . The EDX technique is a method of analysis that allows for the chemical characterization and elemental analysis of various materials. EDX mappings were performed, and the results showed that the elemental distribution on the surface of materials was revealed. An EDX analysis with mapping was performed on the samples that were chosen, and the EDX patterns that were obtained are depicted in Figs.  4 and 5 respectively. GD is primarily composed of silicon dioxide SiO 2 and aluminum oxide (Al 2 O 3 ), whereas MD is primarily composed of calcium carbonates (CaCO 3 ), as demonstrated by the results of the two techniques. In order to further characterize the waste materials that were utilized, techniques such as XRD, TEM, and SEM were utilized. These techniques were utilized to investigate the mineralogical composition, crystal structure, particle size, and microstructure of the dust. A comprehensive description of the marble and granite dust can be found in Figs.  6 , 7 , 8 and 9 , which contains all of the relevant information. The XRF, XRD, SEM, and TEM techniques were utilized in order to investigate the chemical composition, mineralogical composition, crystalline structure, and microstructure of NA. The results of these analyses are presented in Table 1 and Figs. 10 and 11 . Both the mix design of the investigated mixes and the elemental composition that was obtained through the EDX analysis of each mix are displayed in Tables 3 , 4 , and Fig.  12 , respectively.

EDX analysis for MD.

EDX analysis for GD.

X-ray diffraction pattern for MD.

X-ray diffraction pattern for GD.

SEM images for ( a ) MD and ( b ) GD.

TEM images for ( a ) MD and ( b ) GD.

X-ray diffraction pattern of the used Nano alumina.

SEM and TEM of the used Nano alumina.

EDX patterns for ( a ) CO, ( b ) MD 6%, ( c ) GD 6%, ( d ) NA 1%, ( e ) MD6% + NA1% and ( f ) GD6% + NA1%.

Radiation shielding performance

This study's concrete samples serve as the attenuator, and the attenuation factor measures the fraction of γ-ray photons passing through them. Table 5 displays the experimental and theoretical µ values of the prepared Concrete samples, as determined by using the MCS and PhyX software. The values computed by Phy and the simulated values of µ are very similar, with a maximum relative discrepancy of 4.168% 65 , 66 . This study's concrete samples serve as the attenuator, and the attenuation factor measures the fraction of γ-ray photons passing through them. Table 5 displays the experimental and theoretical µ values of the produced Concrete samples, as determined by the MCS and Phy software. The decrease in the µ value occurs when the γ-energy levels increase, which is a trend that is consistently observed in all materials. This trend is particularly evident for the data where µ drops from 37.527 to 0.057 cm −1 for CO, from 34.796 to 0.060 cm −1 for MD, from 30.247 to 0.058 cm −1 for GD, and from 30.397 to 0.056 cm −1 for NA, from 38.866 to 0.063 cm −1 for MD + NA, and from 32.149 to 0.061 cm −1 for GD + NA at 0.015 ≤ Pγ ≤ 15 in MeVs.

As realized in Fig.  13 a, there is a substantial decrease in the µ for the synthetic GMN-concrete samples due to the PEE, which σ α \({1/P}_{\gamma }^{4:5}\) . The enrichment of Pγ led to a decrease in the σ of interactions, which in turn led to a decrease in the γ-electron interactions and values. The enhancement of the Pγ at in MeVs; 0.015 ≤ Pγ ≤ 0.200 causes a solid exponential decreasing trend from 37.527 to 0.307 cm −1 for CO, from 34.796 to 0.331 cm −1 for MD, from 30.247 to 0.332 cm −1 for GD, and from 30.397 to 0.316 cm −1 for NA, from 38.866 to 0.342 cm −1 for MD + NA, and from 32.149 to 0.342 cm −1 for GD + NA concrete sample.

Influence of γ-ray energy on linear attenuation of ( a ) photoelectric, ( b ) Compton scattering processes of the prepared MGN-concretes.

Moreover, as shown in Fig.  13 b, the values of Pγ at energies ranging from 0.300 to 15 MeV show an exponential decline as the energy exceeds 0.200 MeV. The interaction between COMSE and variations in σ α 1/Pγ 67 , 68 , 69 . Is responsible for the exponential drop. Higher Pγ interacting with the atoms of the material is less likely due to their incredibly high velocity, which explains this phenomenon. Therefore, the likelihood of γ-absorption diminishes and the likelihood of γ-scattering increases as Pγ increases. As the number of γ-electron interactions decreased, the σ gradually decreased as well, and the µ values gradually fell after the Pγ values increased. The reduction in the µ values was from 0.259 to 0.057 cm −1 for CO, from 0.281 to 0.060 cm −1 for MD, from 0.283 to 0.058 cm −1 for GD, and from 0.269 to 0.056 cm −1 for NA, from 0.289 to 0.063 cm −1 for MD + NA, and from 0.291 to 0.061 cm −1 for GD + NA at in MeVs 0.300 ≤ Pγ ≤ 15.

Due to the high densities of the GD + NA and MD + NA (2.720 and 2.690 kg m −3 ), the high sufficient atomic number of the elements of Si, Al, Fe, etc., and the nano-alumina doping (1% wt.), GD + NA and MD + NA often exhibit the most excellent µ values compared to the other concrete samples.

Figure  14 a displays a comparison of the µ m between samples of GMN-concrete, commercial concrete, and a few glasses. We will be comparing energies of 0.5, 5, and 10 MeV 70 . In comparison to the concrete and glass samples, as well as the TZNNd9 glass sample, the µ values of the GMN-concrete samples are higher. As can be observed in Fig.  14 b, the comparison with respect to the µ yields identical results.

( a ) The mass attenuation (µm, cm 2  g −1 ), and ( b ) The linear attenuation (µ, cm −1 ) for the MGN-concrete samples with reference concert and glass samples.

The half-value layer thickness (H 1/2 ), the tenth-value layer thickness (T 1/10 ), and the mean free path (MFp) are three common methods that are utilized to quantify the effectiveness of radiation shielding 71 , 72 , 73 , 74 , 75 . This demonstrates the thickness of the shielding material as well as whether or not it is able to block radiation. By decreasing either value, the radiation shielding performance is improved for a given photon energy. This is because radiation is attenuated through a narrower zone when the value is decreased. The H 1/2 of the synthesized Concrete samples increased as the µ decreased . The H 1/2 values grew from 0.018 to 12.199 cm for CO, from 0.020 to 11.634 cm for MD, from 0.023 to 11.863 cm for GD, and from 0.023 to 12.382 cm for NA, from 0.018 to 11.044 cm for MD + NA, and from 0.022 to 11.404 cm for GD + NA sample with raising at 0.015 ≥ Pγ ≥ 15 MeV (Fig.  15 a ) . The values of the T 1/10 follow the same pattern as the H 1/2 as demonstrated in Fig.  15 b. Figure  15 c represents the MFp of the examined Concrete samples as it varies with energy. The MFp values were found from 0.027 to 17.600 cm for CO, from 0.029 to 16.785 cm for MD, from 0.033 to 17.114 cm for GD, and from 0.033 to 17.863 cm for NA, from 0.026 to 15.933 cm for MD + NA, and from 0.031 to 16.453 cm for GD + NA sample.

( a ) The half value layer (H 1/2 ), ( b ) The Tenth value layer (T 1/10 ), and the mean free path (MFp) for the prepared GMN-concretes versus the γ-energy.

The effects of γ-ray energy and the concentration doping of Waste Granite, Marble, and Nano-Alumina on the GMN TF and GMN RPE for the tested concrete are shown in Figs. 16 and 17 , respectively. These figures clearly show it. At 0.015 MeV, which is the shallow γ-ray energy, the RPE values are almost 100%. A considerable drop in GMN RPE levels was seen as a result of an increase in both the γ-energy and the penetrating strength of the supplied γs. Hence, γ-electron interactions inside the produced concretes are reduced as the γ-energy is increased. Reducing the γ-electron interaction leads to an increase in the quantity of scattered γs, which negatively impacts the GMN RPE for the GMN concrete samples.

The transfer factor (GMN TF ) for the prepared GMN concrete samples against photon energy.

The radiation protection efficiency (GMN RPE ) for the prepared GMN concrete samples versus photon energy.

For, the GMN RPE values dropped from ≈ 100 at 0.015 MeV for all GMN concrete samples to 14.240%, 15.248%, 15.297%, 14.609%, 15.704%, and 15.732%, respectively, for CO, MD, GD, NA, MD+NA, and GD+NA samples at γ-ray energy of 0.200 MeV. The results confirm a great shielding capacity for the GMN concrete samples from 0.015 ≤ γ-energy ≤ 0.200 MeV.

Figure 18 shows graphs of the adequate atomic number for the GMN-concrete samples (GMN zeff ) vs γ-energy ranging from 0.015 ≥ Pγ ≥ 15 MeV for the examined glasses. Higher MGN zeff values imply a more favorable radiation interaction, particularly in the COMSE zone. To shield from high- Pγ energy, materials with higher GMN zeff value might be better 76 . For the studied materials, the GMN zeff values decrease as the MeVs increase. The range of GMN zeff for the glasses varied for the energy spectra of interest, having a range of from 18.376 to 12.523 cm for CO, from 17.900 to 11.526 cm for MD, from 17.372 to 10.725 cm for GD, and from 17.560 to 11.008 cm for NA, from 17.947 to 12.362 cm for MD+NA, and from 17.287 to 11.224 cm for GD+NA concrete sample. In light of this, it is possible to draw the conclusion that the radiation shielding efficiency of materials shifts in accordance with the energy of the radiation; it is possible that one substance functions more effectively at higher or lower MeVs than another.

The effective atomic number (GMN Zeff ) for the prepared GMN-concrete samples vs. photon energy.

The results show that the fast neutron removal cross-section (GMN FNRCS ) for the GMN-concrete samples were 0.078 cm −1 , 0.089 cm −1 , 0.094 cm −1 , 0.088 cm −1 , 0.088 cm −1 , and 0.094 cm −1 for CO, MD, GD, NA, MD+NA, and GD+NA correspondingly. The GD+NA had the most efficient GMN FNRCS , primarily because of its elevated concentration of light elements (oxygen) and its high density (2.720) (Fig. 19 ). The GMN HVLFNRCS and GMNλ FNRCS values for the synthetic concrete samples are likewise displayed (Fig. 20 ) 70 . The HVL FNRCS and λ FNRCS values for the GD+NA sample were the lowest, according to the simulated GMN FNRCS values. The GMN FNRCS values of the synthesized GD+NA samples were higher than those prepared. Therefore, we can conclude that the six GMN-concrete systems under investigation have good neutron shielding properties.

The fast neutron removal cross-section (GMN FNRCS ) for the prepared GMN-concretes.

The prepared GMN-concrete samples' fast neutron removal cross-section (GMN FNRCS ), half-value layer (GMN HVLFNRCS ), and relaxation length (GMN λFNRCS ).

This work examines the γ-ray and neutron shielding properties of six mixes of waste Granite, Marble, and Nano-Alumina additives on ordinary concretes (GMN-concrete). The \({\text{GMN}}\mu\) order is CO < MD < GD < NA < MD + NA < GD + NA. The MD + NA and GD + NA samples have the lowest H 1/2, T 1 / 10 , and MFp. Within the investigated Pγ, GMN zeff changes: from 18.376 to 12.523 for CO, from 17.900 to 11.526 for MD, from 17.372 to 10.725 for GD, and from 17.560 to 11.008 for NA, from 17.947 to 12.362 for MD + NA, and from 17.287 to 11.224 for GD + NA concrete sample. The GMN FNRCS of the GMN-concrete samples have values ranging from 0.076 to 0.094 cm −1 for the CO, MD, GD, NA, MD + NA, and GD + NA concretes. In light of this, it can be concluded that the GMN-concrete samples that were studied offer the maximum level of protection against γ-rays and fast neutrons. The exceptional performance of combinations of waste marble, granite, and nano-Alumina on conventional concretes has made it possible for radiation shielding in nuclear and medical facilities to become a reality. This is the last but not the least of the potential achievements.

Ethical approval

This article doesn't contain any studies involving animals performed by any authors. Also, this article does not contain any studies involving human participants performed by authors.

Consent to participate

All Authors agree to participate in the published version of the manuscript.

Data availability

All data generated or analyzed during this study are included in this published article.

Phase, B. Health risks from exposure to low levels of ionizing radiation (The British Institute of Radiology, 2006).

Google Scholar  

Nabil, I. M., El-Samrah, M. G., Sayed, A. F. E., Shazly, A. & Omar, A. Radionuclides distribution and radiation hazards assessment of black sand separation plant’s minerals: A case study. Sci. Rep. 14 , 5241. https://doi.org/10.1038/s41598-024-55633-1 (2024).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Kayahan, S. H., Nuray, K. & Gunay, O. Radiation dose levels in submandibular and sublingual gland regions during C-Arm scopy. Int. J. Comput. Exp. Sci. Eng. https://doi.org/10.22399/ijcesen.320 (2024).

Article   Google Scholar  

El-Rehim, A. F. A., Zahran, H. Y., Yahia, I. S., Makhlouf, S. A. & Shaaban, K. S. Radiation, crystallization, and physical properties of cadmium borate glasses. Silicon 13 , 2289–2307. https://doi.org/10.1007/s12633-020-00798-3 (2020).

Al-Buriahi, M. S. & Tonguc, B. T. Mass attenuation coefficients, effective atomic numbers and electron densities of some contrast agents for computed tomography. Radiat. Phys. Chem. 166 , 108507 (2020).

Al-Qabandi, M. & Alshammary, J. The Pathophysiologic Basis of Nuclear Medicine 11–37 (Springer, 2022).

Book   Google Scholar  

Shahzad, K. et al. Views on radiation shielding efficiency of polymeric composites/nanocomposites and multi-layered materials: current state and advancements. Radiation 3 , 1–20 (2023).

Al-Buriahi, M. et al. Structure, optical, gamma-ray and neutron shielding properties of NiO doped B 2 O 3 –BaCO 3 –Li 2 O 3 glass systems. Ceram. Int. 46 , 1711–1721 (2020).

Zakaly, H. M. et al. Structure, Mössbauer, electrical, and γ-ray attenuation-properties of magnesium zinc ferrite synthesized co-precipitation method. Sci. Rep. 12 , 15495 (2022).

Al-Saleh, W. M., Almutairi, H. M., Sayyed, M. & Elsafi, M. Multilayer radiation shielding system with advanced composites containing heavy metal oxide nanoparticles: A free-lead solution. Sci. Rep. 13 , 18429 (2023).

Alsaif, N. A. M. et al. Influence of WO 3 replacement for CaO on physical, optical, and γ-ray protection properties of borotellurite glasses: A comparative study. Ceram. Int. https://doi.org/10.1016/j.ceramint.2024.06.076 (2024).

Wang, J. Focuses of material science development in recent years. Sci. China Technol. Sci. 54 , 1645–1648. https://doi.org/10.1007/s11431-011-4383-3 (2011).

Article   ADS   Google Scholar  

Rammah, Y., Al-Buriahi, M. & Abouhaswa, A. B 2 O 3 –BaCO 3 –Li2O 3 glass system doped with Co 3 O 4 : Structure, optical, and radiation shielding properties. Phys. B Condens. Matter 576 , 411717 (2020).

Saleh, A., El-Feky, M. G., Hafiz, M. S. & Kawady, N. A. Experimental and theoretical investigation on physical, structure and protection features of TeO 2 –B 2 O 3 glass doped with PbO in terms of gamma, neutron, proton and alpha particles. Radiat. Phys. Chem. 202 , 110586. https://doi.org/10.1016/j.radphyschem.2022.110586 (2023).

Abou Hussein, E. M. & El-Alaily, N. A. Study on the effect of gamma radiation on some spectroscopic and electrical properties of lithium borate glasses. J. of Inorg. Organomet. Polym. Mater. 28 (3), 1214–1225 (2018).

Al-Saleh, W. M., Almutairi, H. M., Alsafi, K., Nabil, I. M. & Elsafi, M. Gamma-ray shielding investigation of nano- and microstructures of SnO on polyester resin composites: Experimental and theoretical study. e-Polymers https://doi.org/10.1515/epoly-2024-0039 (2024).

Zhang, H. et al. Effects of vapor hydration and radiation on the leaching behavior of nuclear glass. J. Nucl. Mater. 578 , 154368 (2023).

Al-Saleh, W. M., Elsafi, M., Almutairi, H. M., Nabil, I. M. & El-Nahal, M. A. A comprehensive study of the shielding ability from ionizing radiation of different mortars using iron filings and bismuth oxide. Sci. Rep. 14 , 10014. https://doi.org/10.1038/s41598-024-60188-2 (2024).

Al-Obaidi, S., Akyıldırım, H., Gunoglu, K. & Akkurt, I. Neutron shielding calculation for barite-boron-water. Acta Phys. Pol. A 137 , 551 (2020).

Sahani, R. & Dixit, A. A comprehensive review on zinc oxide bulk and nano-structured materials for ionizing radiation detection and measurement applications. Mater. Sci. Semicond. Process. 151 , 107040 (2022).

Mourad, M., Abdou, Y., Berber, M. R. & Elhussiny, F. Using nano tungsten oxide polymer composite as a gamma radiation shielding. Delta J. Sci. 43 , 126–132 (2021).

Fathy, I. N. et al. Enhancing mechanical and radiation shielding properties of concrete with lead monoxide and granodiorite: Individual and synergistic effects at micro and nano particle scales. Struct. Concrete n/a https://doi.org/10.1002/suco.202400454 (2024).

Baykal, D. Ş. A novel approach for Technetium-99m radioisotope transportation and storage in lead-free glass containers: A comprehensive assessment through Monte Carlo simulation technique. Int. J. Comput. Exp. Sci. Eng. https://doi.org/10.22399/ijcesen.304 (2024).

Fathy, I. N., El-Sayed, A. A. & Sufe, W. H. Predicting gamma ray linear attenuation coefficient for different nano-concrete types using artificial intelligence. Fayoum Univ. J. Eng. 4 , 176–190 (2021).

Asadpour, N. et al. Shielding performance of multi-metal nanoparticle composites for diagnostic radiology: An MCNPX and Geant4 study. Radiol. Phys. Technol. 16 , 57–68. https://doi.org/10.1007/s12194-022-00690-2 (2023).

Article   PubMed   Google Scholar  

El-Samrah, M., Zamora, M. A., Novog, D. & Chidiac, S. Radiation shielding properties of modified concrete mixes and their suitability in dry storage cask. Progr. Nuclear Energy 148 , 104195 (2022).

Nuray, K. Gamma ray shielding properties of the 57.6 TeO 2 –38.4 ZnO-4NiO system. Int. J. Comput. Exp. Sci. Eng. https://doi.org/10.22399/ijcesen.310 (2024).

Naseri, H., Jahanbakhsh, H., Khezri, K. & Shirzadi Javid, A. A. Toward sustainability in optimizing the fly ash concrete mixture ingredients by introducing a new prediction algorithm. Environ. Dev. Sustain. 24 , 2767–2803 (2022).

Garside, M. Cement Production Worldwide from 1995 to 2022. Accessed 25, 2023; https://www.statista.com/statistics/1087115/global-cement-production-volume (2023).

Ng, S. & Engelsen, C. J. Waste and Supplementary Cementitious Materials in Concrete 229–255 (Elsevier, 2018).

Skibsted, J. & Snellings, R. Reactivity of supplementary cementitious materials (SCMs) in cement blends. Cement Concrete Res. 124 , 105799 (2019).

Abouelnour, M. A. et al. Recycling of marble and granite waste in concrete by incorporating nano alumina. Const. Build. Mater. 411 , 134456 (2024).

El-Sayed, A. A., Fathy, I. N., Tayeh, B. A. & Almeshal, I. Using artificial neural networks for predicting mechanical and radiation shielding properties of different nano-concretes exposed to elevated temperature. Constr. Build. Mater. 324 , 126663 (2022).

El-Sadany, R. A., Sallam, H.E.-D.M. & Al-Tersawy, S. H. Effect of hybrid nanoparticles additions to normal weight concrete on its microstructures and mechanical properties before and after exposure to gamma-rays. Constr. Build. Mater. 376 , 131037 (2023).

Binici, H., Aksogan, O., Sevinc, A. H. & Cinpolat, E. Mechanical and radioactivity shielding performances of mortars made with cement, sand and egg shells. Constr. Build. Mater. 93 , 1145–1150 (2015).

Khalaf, M. A. et al. Engineering and gamma-ray attenuation properties of steel furnace slag heavyweight concrete with nano calcium carbonate and silica. Constr. Build. Mater. 267 , 120878 (2021).

ASTM, C. ASTM C150: Standard specification for Portland cement (American Society for Testing and Materials, 2001).

International, A. Standard specification for mixing water used in the production of hydraulic cement concrete (ASTM Intenational, 2022).

Al-Ghamdi, H. et al. Strontium oxide-reinforced borotellurite glasses: synthesis, structure, and optical characteristics and γ-ray and neutron attenuation capability. J. Electron. Mater. https://doi.org/10.1007/s11664-024-11201-x (2024).

Boodaghi Malidarre, R., Akkurt, I., Ekmekci, I., Zakaly, H. M. & Mohammed, H. The role of La 2 O 3 rare earth (RE) material in the enhancement of the radiation shielding, physical, mechanical and acoustic properties of the tellurite glasses. Radiat. Eff. Defects Solids 178 , 195–207 (2023).

Kurtulus, R. et al. A comprehensive study on novel alumino-borosilicate glass reinforced with Bi 2 O 3 for radiation shielding applications: synthesis, spectrometer, XCOM, and MCNP-X works. J. Mater. Sci. Mater. Electron. 32 , 13882–13896 (2021).

Nabil, I. M. et al. Lithium magnesium borosilicate glass: The impact of alternate doping with nano copper oxide and nano hematite on its structural, optical, and nuclear radiation shielding characteristics. J. Mater. Sci. Mater. Electron. 35 , 826. https://doi.org/10.1007/s10854-024-12554-z (2024).

Abouhaswa, A. et al. The impact of B 2 O 3 /Al 2 O 3 substitution on physical properties and γ-ray shielding competence of aluminum-borate glasses: Comparative study. J. Mater. Sci. Mater. Electron. 35 , 1–13. https://doi.org/10.1007/s10854-024-12629-x (2024).

Alharshan, G. A. et al. Effect of lanthanum oxide on the radiation-shielding, dielectric, and physical properties of lithium zinc phosphate glasses. Radiati. Phys. Chem. 224 , 112053. https://doi.org/10.1016/j.radphyschem.2024.112053 (2024).

Nuray, K. Neutron shielding properties of cellulose acetate CdO-ZnO polymer composites. Int. J. Comput. Exp. Sci. Eng. https://doi.org/10.22399/ijcesen.322 (2024).

Hassanpour, M. et al. The application of graphene/h-BN metamaterial in medical linear accelerators for reducing neutron leakage in the treatment room. Phys. Eng. Sci. Med. 46 , 1023–1032 (2023).

Malidarre, R. B., Akkurt, I., Gunoglu, K. & Akyildirim, H. Fast neutrons shielding properties for HAP-Fe 2 O 3 composite materials. Int. J. Comput. Exp. Sci. Eng. 7 , 143–145 (2021).

Didi, A., Dadouch, A., Bencheikh, M. & Jai, O. Monte Carlo simulation of thermal neutron flux of americium–beryllium source used in neutron activation analysis. Moscow Univ. Phys. Bull. 72 , 460–464 (2017).

Hassanpour, M., Faruque, M. R. I., Hassanpour, M., Khandaker, M. U. & Al-mugren, K. Evaluation of the impact of PL/hBN and PL/B4C on the neutron leakage generated by the LINAC in the treatment room. Alex. Eng. J. 105 , 98–104 (2024).

Didi, A., Dadouch, A. & Jai, O. Modelisation and distribution of neutron flux in radium–beryllium source (226 Ra–Be). Moscow Univ. Phys. Bull. 72 , 465–469 (2017).

Kilic, G., Kavaz, E., Ilik, E., ALMisned, G. & Tekin, H. O. CdO-rich quaternary tellurite glasses for nuclear safety purposes: Synthesis and experimental gamma-ray and neutron radiation assessment of high-density and transparent samples. Opt. Mater. 129 , 112512 (2022).

Kurtuluş, R. et al. Study on recycled Er-incorporated waste CRT glasses for photon and neutron shielding. Ceram. Int. 47 , 26335–26349 (2021).

Hassanpour, M. et al. Introduction of graphene/h-BN metamaterial as neutron radiation shielding by implementing Monte Carlo simulation. Materials 15 , 6667 (2022).

Al-Ghamdi, H., Alsaif, N. A. M., Alfryyan, N., Rammah, Y. S. & Nabil, I. M. Investigation of gamma-ray and neutron protection competence of oxyfluoride aluminosilicate glasses reinforced with TbF3: Comparative study. Radiat. Phys. Chem. https://doi.org/10.1016/j.radphyschem.2024.112105 (2024).

Nabil, I. M. et al. Evaluation of the effect of low additive V 2 O 5 /ZnO on the structural, physical, and radiation attenuation performance of borate glasses. J. Mater. Sci. Mater. Electron. 35 , 1532. https://doi.org/10.1007/s10854-024-13244-6 (2024).

Alfryyan, N. et al. SiO2/Ag 2 O substitution of borosilicate glasses: preparation, structure, physical features and γ-ray protection capability. Silicon https://doi.org/10.1007/s12633-024-03059-9 (2024).

Nabil, I. M. et al. Influence of low copper oxide additives on B 2 O 3 -Li 2 O-Na 2 O-CaO-SrO-As 2 O 3 glasses: A physical, structural, and radiological study. J. Mater. Sci. Mater. Electron. 35 , 1329. https://doi.org/10.1007/s10854-024-12891-z (2024).

Ghozza, M. H. et al. Evaluation of radiation energy attenuation parameters of gamma rays and neutrons for La 0.7 Sr 0.3 MO 3 (M= Fe, Mn, Co) nano perovskite compounds: a simulation study. Int. J. Power Energy Conv. 15 , 166–191. https://doi.org/10.1504/IJPEC.2024.138006 (2024).

Alsaif, N. A. M. et al. Linear/non-linear optical properties, γ-ray and neutron shielding competence of borosilicate glasses reinforced with Ag 2 O. J. Mater. Sci. Mater. Electron. 35 , 1604. https://doi.org/10.1007/s10854-024-13344-3 (2024).

Al-Saleh, W. M., Almutairi, H. M., Alsafi, K., Nabil, I. M. & Elsafi, M. Gamma-ray shielding investigation of nano-and microstructures of SnO on polyester resin composites: Experimental and theoretical study. e-Polymers 24 , 20240039 (2024).

Team, M. C. MCNP–a General Monte Carlo N-Particle Transport Code (X-5 Monte Carlo Team, Version 5). Vol. I: Overview and Theory. Los Alamos, NM: Los Alamos National Laboratory. (LA-UR-03-1987, 2003).

Briesmeister, J. F. MCNPTM-A general Monte Carlo N-particle transport code. Version 4C, LA-13709-M Los Alamos National Laboratory 2 (2000).

Gunha, J. V. et al. High thermal stability molybdenum-boosted lithium tellurite glass for radiation shielding. Ceram. Int. https://doi.org/10.1016/j.ceramint.2024.07.271 (2024).

Gunoglu, K., Özkavak, H. V. & Akkurt, İ. Evaluation of gamma ray attenuation properties of boron carbide (B4C) doped AISI 316 stainless steel: Experimental, XCOM and Phy-X/PSD database software. Mater. Today Commun. 29 , 102793 (2021).

Tekin, H. et al. Characterization of a broad range gamma-ray and neutron shielding properties of MgO-Al 2 O 3 -SiO 2 -B 2 O 3 and Na 2 O-Al 2 O 3 -SiO 2 glass systems. J. Non-Crystall. Solids 518 , 92–102 (2019).

Alharshan, G. A. et al. CeO 2 additive to bismo-borate glasses: Synthesis, structure, physical characteristics, and radiation protection competence. J. Mater. Sci. Mater. Electron. 35 , 862. https://doi.org/10.1007/s10854-024-12610-8 (2024).

Al-Ghamdi, H. et al. Sustainable wastewater sludge@bimetallic cadmium-MOFs and nano-copper oxide as a promising shielding composite for gamma rays: Experimental and simulation investigations. Mater. Sci. Eng. B 308 , 117609. https://doi.org/10.1016/j.mseb.2024.117609 (2024).

Alsaif, N. A. M. et al. Optical and gamma-ray attenuation of cobalt and lanthanum-doped sodium zinc lead borate glass. J. Mater. Sci. Mater. Electron. 35 , 1458. https://doi.org/10.1007/s10854-024-13168-1 (2024).

Almousa, N., Abouhaswa, A. S., Issa, S. A. M., Nabil, I. M. & Zakaly, H. M. H. Influence of titanium dioxide doping on the attenuation and optical characteristics of magnesium borate glass systems. Ceram. Int. https://doi.org/10.1016/j.ceramint.2024.04.147 (2024).

Bashter, I. Calculation of radiation attenuation coefficients for shielding concretes. Ann. Nuclear Energy 24 , 1389–1401 (1997).

Zakaly, H. M. et al. Optical and nuclear radiation shielding properties of zinc borate glasses doped with lanthanum oxide. J. Non Cryst. Solids 543 , 120151 (2020).

Kurtulus, R., Kurtulus, C. & Kavas, T. Physical, optical, thermal, mechanical, and photon shielding properties of Rb 2 O-reinforced SiO 2 –Na 2 O-CaO–MgO–Al 2 O 3 glass system. J. Mater. Sci. Mater. Electron. 32 , 7801–7814 (2021).

Sabry, N. & Yahia, I. Attenuation features of Ag2ZnSnS4, Ag2ZnSnSe4, ZnS, and Ag2S compounds against indirect ionizing radiation using Phy-X/PSD software. Phys. B Condens. Matter 650 , 414526 (2023).

Mansy, M. S., Lasheen, Y. F., Breky, M. M. & Selim, Y. Experimental and theoretical investigation of Pb–Sb alloys as a gamma-radiation shielding material. Radiat. Phys. Chem. 183 , 109416 (2021).

Elalaily, N. A., Abou-Hussien, E. M. & Saad, E. A. Bismuth silicate glass containing heavy metal oxide as a promising radiation shielding material. Radiat. Effects Defects Solids 171 , 840–854 (2016).

Karpuz, N. Effective atomic numbers of glass samples. Int. J. Comput. Exp. Sci. Eng. https://doi.org/10.22399/ijcesen.340 (2024).

Download references

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Author information

Authors and affiliations.

Civil Engineering Department, Faculty of Engineering, Fayoum University, Fayoum, Egypt

Alaa A. Mahmoud, Alaa A. El-Sayed, Islam N. Fathy & Mohamed A. Abouelnour

Construction and Building Engineering Department, October High Institute for Engineering & Technology, Giza, Egypt

Alaa A. Mahmoud & Islam N. Fathy

Construction and Building Engineering Department, Higher Institute of Engineering, Culture & Science City, Giza, Egypt

Ayman M. Aboraya

Physics Department, Faculty of Science, Fayoum University, Fayoum, Egypt

Islam M. Nabil

You can also search for this author in PubMed   Google Scholar

Contributions

Formal analysis and software: I.M.N., I.N.F.; Analysis review: I.M.N.; Supervision: I.M.N., I.N.F.; Writing-original draft: I.M.N., I.N.F.; Writing-review and editing: A. A. M., A. A. E. S., A.M.A., M.A.A., All Authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Islam M. Nabil .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Mahmoud, A.A., El-Sayed, A.A., Aboraya, A.M. et al. Influence of sustainable waste granite, marble and nano-alumina additives on ordinary concretes: a physical, structural, and radiological study. Sci Rep 14 , 22011 (2024). https://doi.org/10.1038/s41598-024-72222-4

Download citation

Received : 05 May 2024

Accepted : 04 September 2024

Published : 24 September 2024

DOI : https://doi.org/10.1038/s41598-024-72222-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Waste granite
• Physical/structural properties
• Radiation shielding

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• Entertainment
• Life & Style

To enjoy additional benefits

CONNECT WITH US

Journal ‘retracts’ controversial paper published by BHU on Covaxin safety

The editor and the publisher have decided that this article should be removed on public health grounds, says retraction notice.

Updated - September 25, 2024 11:06 pm IST - CHENNAI

Bharat Biotech wanted the journal to take down the “defamatory research study” and a “permanent injunction” against the authors and the editor from “further publishing defamatory and flawed studies” on Covaxin. File | Photo Credit: The Hindu

The journal ‘Drug Safety’ has “retracted” a paper published on May 13 by researchers of the Banaras Hindu University , on the safety of COVID-19 vaccine Covaxin.

The paper, “Long-term safety analysis of the BBV152 coronavirus vaccine in adolescents and adults: Findings from a 1-year prospective study in North India”, was based on a follow up of 635 adolescents and 291 adults one year after vaccination, to find the safety of Covaxin. It was a prospective observational study conducted from January 2022 to August 2023 where the recipients of the vaccine were interviewed over the telephone about the long-term adverse events of special interest (AESIs) one year after vaccination.

Also read | The right way to counter a poor Covaxin safety study 

The “retraction” notice put up on Tuesday (September 24, 2024) reads: “The Editor has retracted this article as he no longer has confidence in the conclusions as stated in the article. Post-publication review concluded that the reported adverse events of special interest (AESIs) were presented in a way that could lead to ambiguous or incorrect interpretations regarding the relationship with the BBV152 vaccine. Given these findings, the Editor and the publisher have decided that this article should be removed on public health grounds.”

While criticising the authors for the “poorly designed” study, the Indian Council of Medical Research (ICMR) on May 18 wrote to the editor to retract the paper that “implicitly makes conclusions about the vaccine safety that are not supported by evidence”. But the paper was not retracted as demanded by the ICMR. Besides criticising the study for its limitations, Bharat Biotech also filed a defamation case against the authors and the editor of the journal. In the prayer of the defamation notice, Bharat Biotech wanted the journal to take down the “defamatory research study” and a “permanent injunction” against the authors and the editor from “further publishing defamatory and flawed studies” on Covaxin. Bharat Biotech also wanted ₹5 crore for the “loss and injury caused by the defamatory research study”.

Contrary to the claim by the journal that the paper has been retracted — where the original paper is still available on the journal website with a retracted watermark appearing on each page of the paper, the original paper has been removed from the website with only the “retraction” notice mentioning the reasons available. “That the paper has been removed from the website instead of a retraction watermark being added to the original paper suggests that the removal of the paper was due to the defamation case and not due to scientific reasons as the notice mentions,” Amar Jesani, editor of the Indian Journal of Medical Ethics told The Hindu . “The journal has thrown the authors under the bus.”

In an open letter written to Bharat Biotech and the Director-General of ICMR, over 600 scientists, researchers, ethicists, doctors, patients, and civil society members had said that the defamation suit will lead to a “chilling effect on researchers, and is harmful for science and the trust people have on the institution of science”. The open letter further adds: “In our view, the actions of ICMR and BBIL are short-sighted and punitive. Scientific disagreements have to be articulated as counterpoints in scientific fora.”

Published - September 25, 2024 08:24 pm IST

Related Topics

vaccines / Coronavirus

Top News Today

• Access 10 free stories every month
• Save stories to read later
• Access to comment on every story
• Sign-up/manage your newsletter subscriptions with a single click
• Get notified by email for early access to discounts & offers on our products

Terms & conditions   |   Institutional Subscriber

Comments have to be in English, and in full sentences. They cannot be abusive or personal. Please abide by our community guidelines for posting your comments.

We have migrated to a new commenting platform. If you are already a registered user of The Hindu and logged in, you may continue to engage with our articles. If you do not have an account please register and login to post comments. Users can access their older comments by logging into their accounts on Vuukle.

Warning: The NCBI web site requires JavaScript to function. more...

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

InformedHealth.org [Internet]. Cologne, Germany: Institute for Quality and Efficiency in Health Care (IQWiG); 2006-.

InformedHealth.org [Internet].

In brief: what types of studies are there.

Last Update: September 8, 2016 ; Next update: 2024.

There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked.

When making decisions, patients and doctors need reliable answers to a number of questions. Depending on the medical condition and patient's personal situation, the following questions may be asked:

• What is the cause of the condition?
• What is the natural course of the disease if left untreated?
• What will change because of the treatment?
• How many other people have the same condition?
• How do other people cope with it?

Each of these questions can best be answered by a different type of study.

In order to get reliable results, a study has to be carefully planned right from the start. One thing that is especially important to consider is which type of study is best suited to the research question. A study protocol should be written and complete documentation of the study's process should also be done. This is vital in order for other scientists to be able to reproduce and check the results afterwards.

The main types of studies are randomized controlled trials (RCTs), cohort studies, case-control studies and qualitative studies.

• Randomized controlled trials

If you want to know how effective a treatment or diagnostic test is, randomized trials provide the most reliable answers. Because the effect of the treatment is often compared with "no treatment" (or a different treatment), they can also show what happens if you opt to not have the treatment or diagnostic test.

When planning this type of study, a research question is stipulated first. This involves deciding what exactly should be tested and in what group of people. In order to be able to reliably assess how effective the treatment is, the following things also need to be determined before the study is started:

• How long the study should last
• How many participants are needed
• How the effect of the treatment should be measured

For instance, a medication used to treat menopause symptoms needs to be tested on a different group of people than a flu medicine. And a study on treatment for a stuffy nose may be much shorter than a study on a drug taken to prevent strokes .

“Randomized” means divided into groups by chance. In RCTs participants are randomly assigned to one of two or more groups. Then one group receives the new drug A, for example, while the other group receives the conventional drug B or a placebo (dummy drug). Things like the appearance and taste of the drug and the placebo should be as similar as possible. Ideally, the assignment to the various groups is done "double blinded," meaning that neither the participants nor their doctors know who is in which group.

The assignment to groups has to be random in order to make sure that only the effects of the medications are compared, and no other factors influence the results. If doctors decided themselves which patients should receive which treatment, they might – for instance – give the more promising drug to patients who have better chances of recovery. This would distort the results. Random allocation ensures that differences between the results of the two groups at the end of the study are actually due to the treatment and not something else.

Randomized controlled trials provide the best results when trying to find out if there is a cause-and-effect relationship. RCTs can answer questions such as these:

• Is the new drug A better than the standard treatment for medical condition X?
• Does regular physical activity speed up recovery after a slipped disk when compared to passive waiting?
• Cohort studies

A cohort is a group of people who are observed frequently over a period of many years – for instance, to determine how often a certain disease occurs. In a cohort study, two (or more) groups that are exposed to different things are compared with each other: For example, one group might smoke while the other doesn't. Or one group may be exposed to a hazardous substance at work, while the comparison group isn't. The researchers then observe how the health of the people in both groups develops over the course of several years, whether they become ill, and how many of them pass away. Cohort studies often include people who are healthy at the start of the study. Cohort studies can have a prospective (forward-looking) design or a retrospective (backward-looking) design. In a prospective study, the result that the researchers are interested in (such as a specific illness) has not yet occurred by the time the study starts. But the outcomes that they want to measure and other possible influential factors can be precisely defined beforehand. In a retrospective study, the result (the illness) has already occurred before the study starts, and the researchers look at the patient's history to find risk factors.

Cohort studies are especially useful if you want to find out how common a medical condition is and which factors increase the risk of developing it. They can answer questions such as:

• How does high blood pressure affect heart health?
• Does smoking increase your risk of lung cancer?

For example, one famous long-term cohort study observed a group of 40,000 British doctors, many of whom smoked. It tracked how many doctors died over the years, and what they died of. The study showed that smoking caused a lot of deaths, and that people who smoked more were more likely to get ill and die.

• Case-control studies

Case-control studies compare people who have a certain medical condition with people who do not have the medical condition, but who are otherwise as similar as possible, for example in terms of their sex and age. Then the two groups are interviewed, or their medical files are analyzed, to find anything that might be risk factors for the disease. So case-control studies are generally retrospective.

Case-control studies are one way to gain knowledge about rare diseases. They are also not as expensive or time-consuming as RCTs or cohort studies. But it is often difficult to tell which people are the most similar to each other and should therefore be compared with each other. Because the researchers usually ask about past events, they are dependent on the participants’ memories. But the people they interview might no longer remember whether they were, for instance, exposed to certain risk factors in the past.

Still, case-control studies can help to investigate the causes of a specific disease, and answer questions like these:

• Do HPV infections increase the risk of cervical cancer ?
• Is the risk of sudden infant death syndrome (“cot death”) increased by parents smoking at home?

Cohort studies and case-control studies are types of "observational studies."

• Cross-sectional studies

Many people will be familiar with this kind of study. The classic type of cross-sectional study is the survey: A representative group of people – usually a random sample – are interviewed or examined in order to find out their opinions or facts. Because this data is collected only once, cross-sectional studies are relatively quick and inexpensive. They can provide information on things like the prevalence of a particular disease (how common it is). But they can't tell us anything about the cause of a disease or what the best treatment might be.

Cross-sectional studies can answer questions such as these:

• How tall are German men and women at age 20?
• How many people have cancer screening?
• Qualitative studies

This type of study helps us understand, for instance, what it is like for people to live with a certain disease. Unlike other kinds of research, qualitative research does not rely on numbers and data. Instead, it is based on information collected by talking to people who have a particular medical condition and people close to them. Written documents and observations are used too. The information that is obtained is then analyzed and interpreted using a number of methods.

Qualitative studies can answer questions such as these:

• How do women experience a Cesarean section?
• What aspects of treatment are especially important to men who have prostate cancer ?
• How reliable are the different types of studies?

Each type of study has its advantages and disadvantages. It is always important to find out the following: Did the researchers select a study type that will actually allow them to find the answers they are looking for? You can’t use a survey to find out what is causing a particular disease, for instance.

It is really only possible to draw reliable conclusions about cause and effect by using randomized controlled trials. Other types of studies usually only allow us to establish correlations (relationships where it isn’t clear whether one thing is causing the other). For instance, data from a cohort study may show that people who eat more red meat develop bowel cancer more often than people who don't. This might suggest that eating red meat can increase your risk of getting bowel cancer. But people who eat a lot of red meat might also smoke more, drink more alcohol, or tend to be overweight. The influence of these and other possible risk factors can only be determined by comparing two equal-sized groups made up of randomly assigned participants.

That is why randomized controlled trials are usually the only suitable way to find out how effective a treatment is. Systematic reviews, which summarize multiple RCTs , are even better. In order to be good-quality, though, all studies and systematic reviews need to be designed properly and eliminate as many potential sources of error as possible.

• German Network for Evidence-based Medicine. Glossar: Qualitative Forschung.  Berlin: DNEbM; 2011. 
• Greenhalgh T. Einführung in die Evidence-based Medicine: kritische Beurteilung klinischer Studien als Basis einer rationalen Medizin. Bern: Huber; 2003. 
• Institute for Quality and Efficiency in Health Care (IQWiG, Germany). General methods . Version 5.0. Cologne: IQWiG; 2017.
• Klug SJ, Bender R, Blettner M, Lange S. Wichtige epidemiologische Studientypen. Dtsch Med Wochenschr 2007; 132:e45-e47. [ PubMed : 17530597 ]
• Schäfer T. Kritische Bewertung von Studien zur Ätiologie. In: Kunz R, Ollenschläger G, Raspe H, Jonitz G, Donner-Banzhoff N (eds.). Lehrbuch evidenzbasierte Medizin in Klinik und Praxis. Cologne: Deutscher Ärzte-Verlag; 2007.

IQWiG health information is written with the aim of helping people understand the advantages and disadvantages of the main treatment options and health care services.

Because IQWiG is a German institute, some of the information provided here is specific to the German health care system. The suitability of any of the described options in an individual case can be determined by talking to a doctor. informedhealth.org can provide support for talks with doctors and other medical professionals, but cannot replace them. We do not offer individual consultations.

Our information is based on the results of good-quality studies. It is written by a team of health care professionals, scientists and editors, and reviewed by external experts. You can find a detailed description of how our health information is produced and updated in our methods.

• Cite this Page InformedHealth.org [Internet]. Cologne, Germany: Institute for Quality and Efficiency in Health Care (IQWiG); 2006-. In brief: What types of studies are there? [Updated 2016 Sep 8].

In this Page

Informed health links, related information.

• PubMed Links to PubMed

Recent Activity

• In brief: What types of studies are there? - InformedHealth.org In brief: What types of studies are there? - InformedHealth.org

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers