Abstract
The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed, and unnecessary costs may come into play. In this study, a decision support framework using a fuzzy analytic hierarchy process (FAHP) and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital, and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19. A case study is performed for Ho Chi Minh City using the proposed decision-making framework. The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic. The results of the study can be used to assist decision-makers, such as government authorities and infectious disease experts, in dealing with the current pandemic as well as other diseases in the future. With the entire world facing the global pandemic of COVID-19, many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic. As the number of cases increases exponentially, it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria. As such, the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries.
Highlights
COVID-19 first emerged in Wuhan, China, in December 2019
A decision support framework using fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS) model is proposed for selecting the location of a temporary hospital for COVID-19 patients and for the prioritization of preventive measures
To lessen the strain of the pandemic on existing healthcare infrastructures, two approaches have been adopted by many countries: building specialized temporary hospitals and promoting preventive measures
Summary
COVID-19 first emerged in Wuhan, China, in December 2019. Since the virus has become a global health crisis causing dire social and economic consequences [1]. Several organizations, including the World Health Organization (WHO) and the U.S Centers for Disease Control and Prevention (CDC), as well as national and federal governments, have provided warnings and guidelines to prevent the spread of COVID-19 [4] These guidelines range from basic personal hygiene measures such as frequent washing and sanitizing of one’s hands and promoting the use of face masks, to societal measures such as social distancing and shutting down public spaces [5]. While different countries have different approaches to limiting the spread of COVID-19, it is important to identify the main way that COVID-19 spreads and to evaluate the available tools in order to prioritize effective preventive measures This is a multicriteria decision-making problem, and to solve it requires the use of Multiple Criteria Decision-Making (MCDM) models. The incorporation of fuzzy theory allows an MCDM model to solve decision-making problems in uncertain environments
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