Cargando…

Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets

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 İstanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals....

Descripción completa

Detalles Bibliográficos
Autores principales: Boyacı, Aslı Çalış, Şişman, Aziz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342988/
https://www.ncbi.nlm.nih.gov/pubmed/34357491
http://dx.doi.org/10.1007/s11356-021-15703-7
_version_ 1783734181024497664
author Boyacı, Aslı Çalış
Şişman, Aziz
author_facet Boyacı, Aslı Çalış
Şişman, Aziz
author_sort Boyacı, Aslı Çalış
collection PubMed
description 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 İstanbul, 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.
format Online
Article
Text
id pubmed-8342988
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-83429882021-08-06 Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets Boyacı, Aslı Çalış Şişman, Aziz Environ Sci Pollut Res Int Research Article 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 İstanbul, 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. Springer Berlin Heidelberg 2021-08-06 2022 /pmc/articles/PMC8342988/ /pubmed/34357491 http://dx.doi.org/10.1007/s11356-021-15703-7 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Boyacı, Aslı Çalış
Şişman, Aziz
Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title_full Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title_fullStr Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title_full_unstemmed Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title_short Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets
title_sort pandemic hospital site selection: a gis-based mcdm approach employing pythagorean fuzzy sets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342988/
https://www.ncbi.nlm.nih.gov/pubmed/34357491
http://dx.doi.org/10.1007/s11356-021-15703-7
work_keys_str_mv AT boyacıaslıcalıs pandemichospitalsiteselectionagisbasedmcdmapproachemployingpythagoreanfuzzysets
AT sismanaziz pandemichospitalsiteselectionagisbasedmcdmapproachemployingpythagoreanfuzzysets