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- Title
Spatial Layout and Accessibility Evaluation of COVID-19 Vaccination Sites Based on Three Optimization Models: A Case Study of Tianhe District, Guangzhou.
- Authors
Wang, Danni; Liu, Peihua; Xu, Ziqian; Wang, Chongyang; Song, Yun; Zhang, Jinghong; Jiang, Kunneng; Zhu, Beiqing
- Abstract
The outbreak of COVID-19 poses a serious threat to global public health, and vaccination is an effective means of prevention. Studying the spatial layout and accessibility of COVID-19 vaccination sites is of great significance. The study analyzes the spatial distribution characteristics and accessibility of vaccination sites in the early stage of mass vaccination in Tianhe District, Guangzhou, based on GIS technology and combines three location allocation models: the p-median model, maximum covering location problem (MCLP) model, and location set covering problem (LSCP) model to identify candidate COVID-19 vaccination sites for the proposed public service facilities. The study found that only 47 COVID-19 vaccination sites exist in the early stage, with a small overall number, uneven spatial distribution, and trend of high accessibility in the central but low accessibility in the north and south; after the proposed addition of 31 vaccination sites, the overall distribution showed an even and dense distribution in the central and western regions, sporadic distribution in other regions, consistent with the distribution characteristics of residential communities. The areas where the accessibility of vaccination sites increased by more than 500 m accounted for 41% of the total area, and the area served by vaccination sites increased by 18%. Therefore, using the existing public service facilities to reasonably add the vaccination sites can improve the efficiency of vaccination and safeguard the establishment of a herd immunity barrier.
- Subjects
GUANGZHOU (China); COVID-19 vaccines; HERD immunity; COMMUNITIES; COVID-19 pandemic; GEOGRAPHIC information systems; MUNICIPAL services; SWARM intelligence
- Publication
Journal of Disaster Research, 2023, Vol 18, Issue 5, p531
- ISSN
1881-2473
- Publication type
Article
- DOI
10.20965/jdr.2023.p0531