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

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.

Genome Sequence of an Early Imported Case of SARS-CoV-2 Delta Variant (B.1.617.2 AY.122) in Iraq in April 2021.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant was first reported in India. Thereafter, the Delta variant became the most prevalent variant globally. Here, we report the complete genome sequence of an early imported case of a SARS-CoV-2 B.1.617.2 AY.122 strain in Iraq. The strain was obtained from a flight passenger from India to Iraq on 20 April 2021.

Integration of FDOSM and FWZIC Under Homogeneous Fermatean Fuzzy Environment: A Prioritization of COVID-19 Patients for Mesenchymal Stem Cell Transfusion

Mesenchymal stem cell (MSC) transfusion has shown promising results in treating COVID-19 cases despite the limited availability of these MSCs. The task of prioritizing COVID-19 patients for MSC transfusion based on multiple criteria is considered a multi-attribute decision-analysis (MADA) problem. Although literature reviews have assessed the prioritization of COVID-19 patients for MSCs, issues arising from imprecise, unclear and ambiguous information remain unresolved. Compared with the existing MADA methods, the robustness of the fuzzy decision by opinion score method (FDOSM) and fuzzy-weighted zero inconsistency (FWZIC) is proven. This study adopts and integrates FDOSM and FWZIC in a homogeneous Fermatean fuzzy environment for criterion weighting followed by the prioritization of the most eligible COVID-19 patients for MSC transfusion. The research methodology had two phases. The decision matrices of three COVID-19 emergency levels (moderate, severe, and critical) were adopted based on an augmented dataset of 60 patients and discussed in the first phase. The second phase was divided into two subsections. The first section developed Fermatean FWZIC (F-FWZIC) to weigh criteria across each emergency level of COVID-19 patients. These weights were fed to the second section on adopting Fermatean FDOSM (F-FDOSM) for the purpose of prioritizing COVID-19 patients who are the most eligible to receive MSCs. Three methods were used in evaluating the proposed works, and the results included systematic ranking, sensitivity analysis, and benchmarking checklist.

High prevalence of an alpha variant lineage with a premature stop codon in ORF7a in Iraq, winter 2020-2021.

Since the first reported case of coronavirus disease 2019 (COVID-19) in China, SARS-CoV-2 has been spreading worldwide. Genomic surveillance of SARS-CoV-2 has had a critical role in tracking the emergence, introduction, and spread of new variants, which may affect transmissibility, pathogenicity, and escape from infection or vaccine-induced immunity. As anticipated, the rapid increase in COVID-19 infections in Iraq in February 2021 is due to the introduction of variants of concern during the second wave of the COVID-19 pandemic. To understand the molecular epidemiology of SARS-CoV-2 during the second wave in Iraq (2021), we sequenced 76 complete SARS-CoV-2 genomes using NGS technology and identified genomic mutations and proportions of circulating variants among these. Also, we performed an in silico study to predict the effect of the truncation of NS7a protein (ORF7a) on its function. We detected nine different lineages of SARS-CoV-2. The B.1.1.7 lineage was predominant (80.20%) from February to May 2021, while only one B.1.351 strain was detected. Interestingly, the phylogenetic analysis showed that multiple strains of the B.1.1.7 lineage clustered closely with those from European countries. A notable frequency (43.33%) of stop codon mutation (NS7a Q62stop) was detected among the B.1.1.7 lineage sequences. In silico analysis of NS7a with Q62stop found that this stop codon had no considerable effect on the function of NS7a. This work provides molecular epidemiological insights into the spread variants of SARS-CoV-2 in Iraq, which are most likely imported from Europe.

Genome Sequencing of a Novel Coronavirus SARS-CoV-2 Isolate from Iraq.

The coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain isolated from an Iraqi patient was sequenced for the first-time using Illumina MiSeq technology. There was a D614G mutation in the spike protein-coding sequence. This report is valuable for better understanding the spread of the virus in Iraq.