A mass vaccination site selection problem: An application of GIS and entropy-based MAUT approach

Basit Öğe Kaydı
dc.authoridCetinkaya, Cihan/0000-0002-5899-8438
dc.authoridOzceylan, Eren/0000-0002-5213-6335
dc.contributor.authorCetinkaya, Cihan
dc.contributor.authorErbas, Mehmet
dc.contributor.authorKabak, Mehmet
dc.contributor.authorOzceylan, Eren
dc.date.accessioned2025-01-06T17:37:15Z
dc.date.available2025-01-06T17:37:15Z
dc.date.issued2023
dc.description.abstractCoronavirus disease (COVID-19) was recognized in December 2019 and spread very severely throughout the world. In 2022 May, the total death numbers reached 6.28 million people worldwide. During the pandemic, some alternative vaccines were discovered in the middle of 2020. Today, many countries are struggling to supply vaccines and vaccinate their citizens. Besides the difficulties of vaccine supply, mass vaccination is a challenging but mandatory task for the countries. Within this context, determining the mass vaccination site is very important for recovering, thus a five-step approach is generated in this paper to solve this real-life problem. Firstly the mass vaccination site selection criteria are determined, and secondly, the spatial data are collected and mapped by using Geographical Information System (GIS) software. Then, the entropy weighting method (EWM) is used for determining the relative importance levels of criteria and fourthly, the multiple attribute utility theory (MAUT) approach is used for ranking the potential mass vaccination sites. Lastly, ranked alternative sites are analyzed using network analyst tool of GIS in terms of covered population. A case study is conducted in Gaziantep city which is the ninth most population and having above-average COVID-19 patients in Turkey. As a result, the fourth alternative (around the S,ehitkamil Monument) is chosen as the best mass vaccination site for the city. It is believed that the outcomes of the paper could be used by city planners and decision-makers.
dc.identifier.doi10.1016/j.seps.2022.101376
dc.identifier.issn0038-0121
dc.identifier.issn1873-6041
dc.identifier.pmid35755637
dc.identifier.scopus2-s2.0-85132956398
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.seps.2022.101376
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2166
dc.identifier.volume85
dc.identifier.wosWOS:000925386900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofSocio-Economic Planning Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectCOVID-19
dc.subjectEntropy
dc.subjectGIS
dc.subjectMass vaccination
dc.subjectMAUT
dc.subjectSite selection
dc.titleA mass vaccination site selection problem: An application of GIS and entropy-based MAUT approach
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu