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Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets.
Boyaci, Asli Çalis; Sisman, Aziz.
  • Boyaci AÇ; Department of Industrial Engineering, Ondokuz Mayis University, 55139, Samsun, Turkey. asli.calis@omu.edu.tr.
  • Sisman A; Department of Geomatics Engineering, Ondokuz Mayis University, 55139, Samsun, Turkey.
Environ Sci Pollut Res Int ; 29(2): 1985-1997, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1345177
ABSTRACT
COVID-19 poses many challenges for hospitals around the world. Each country attempts to solve the problems in its hospitals using different methods. In Turkey, two pandemic hospitals were built in Istanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals. This study focuses on the methods used for site selection for a pandemic hospital in Atakum, a district of Samsun City, Turkey. As a solution to the problem, initially, spatial analysis was performed using GIS to produce maps based on seven criteria obtained from the insight of an expert team. Analytic hierarchy process (AHP) augmented by interval-valued Pythagorean fuzzy numbers (PFNs) was then used to determine weights for the criteria. Distance to transportation network was the most important criterion influencing the selection process and the least significant one was the distance to fire stations. Based on the criteria weights, and five rules specified by the expert team, 13 suitable locations for a pandemic hospital were determined using GIS. The technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the final ranking of 13 alternative locations (A1-A13). A10 was identified as the most appropriate site and A11 as the least appropriate site for a pandemic hospital. Finally, sensitivity analysis was performed to investigate how changes in weight values of the criteria affect the ranking of the alternatives.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Refuse Disposal / COVID-19 / Mobile Health Units Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Sci Pollut Res Int Journal subject: Environmental Health / Toxicology Year: 2022 Document Type: Article Affiliation country: S11356-021-15703-7

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Refuse Disposal / COVID-19 / Mobile Health Units Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Sci Pollut Res Int Journal subject: Environmental Health / Toxicology Year: 2022 Document Type: Article Affiliation country: S11356-021-15703-7