A new fuzzy FUCOM-QFD approach for evaluating strategies to enhance the resilience of the healthcare sector to combat the COVID-19 pandemic

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Purpose

The coronavirus disease 2019 (COVID-19) pandemic has subjected a considerable strain on the healthcare (HC) systems around the world. The most affected countries are developing countries because of their weak HC infrastructure and meagre resources. Hence, building the resilience of the HC system of such countries becomes essential. Therefore, this study aims to build a resilience-based model on the HC sector of Pakistan to combat the COVID-19 and future pandemics in the country.

Design/methodology/approach

The study uses a novel hybrid approach to formulate a model based on resilient attributes (RAs) and resilient strategies (RSs). In the first step, the multi-criteria decision-making (MCDM) technique, i.e. full consistency method (FUCOM) is used to prioritize the RAs. Whereas, the fuzzy quality function deployment (QFD) is used to rank the RSs.

Findings

The findings suggest “leadership and governance capacity” to be the topmost RA. Whereas “building the operational capacity of the management”, “resilience education” and “Strengthening laboratories and diagnostic systems” are ranked to be the top three RSs, respectively.

Practical implications

The model developed in this study and the prioritization RAs and RSs will help build resilience in the HC sector of Pakistan. The policymakers and the government can take help from the prioritized RAs and RSs developed in this study to help make the current HC system more resilient towards the current COVID-19 and future pandemics in the country.

Originality/value

A new model has been developed to present a sound mathematical model for building resilience in the HC sector consisting of FUCOM and fuzzy QFD methods. The main contribution of the paper is the presentation of a comprehensive and more robust model that will help to make the current HC system of Pakistan more resilient.

Related collections

Most cited references 103

Record: found
Abstract: found
Article: not found

Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

Roujian Lu, Xiang Zhao, Juan Li … (2021)

Summary Background In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. Methods We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. Findings The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. Interpretation 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. Funding National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.

0 comments Cited 5801 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Fuzzy sets

L.A. Zadeh (1965)

0 comments Cited 4881 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Strategies for mitigating an influenza pandemic

Neil M Ferguson, Derek A. T. Cummings, Christophe Fraser … (2006)

Pandemic flu: talking tactics Numerical models of the epidemiology of a potential flu pandemic show there is no single magic bullet which can control the outbreak, but that a combination of approaches could reduce transmission and save many lives. Border restrictions are unlikely to have much effect and travel restrictions within one country would make very little difference to the spread of a pandemic within that country. The models predict that a pandemic in the United Kingdom would peak within two to three months of the first case, and be over within 4 months. It also shows that vaccines need to be available within two months of the start of a pandemic to have a big effect in reducing infection rates. That means that vaccines would need to be stockpiled in advance to be effective. Supplementary information The online version of this article (doi:10.1038/nature04795) contains supplementary material, which is available to authorized users.