Cargando…
Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida
The equitable allocation of COVID-19 vaccines is a critical challenge worldwide, given that the pandemic has been disproportionally affecting economically disadvantaged racial and ethnic groups. In the United States, the ongoing implementation efforts at different administrative levels and districts...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566030/ https://www.ncbi.nlm.nih.gov/pubmed/36231743 http://dx.doi.org/10.3390/ijerph191912443 |
_version_ | 1784809037414531072 |
---|---|
author | Chen, Yuzhou Tao, Ran Downs, Joni |
author_facet | Chen, Yuzhou Tao, Ran Downs, Joni |
author_sort | Chen, Yuzhou |
collection | PubMed |
description | The equitable allocation of COVID-19 vaccines is a critical challenge worldwide, given that the pandemic has been disproportionally affecting economically disadvantaged racial and ethnic groups. In the United States, the ongoing implementation efforts at different administrative levels and districts, to some extent, are standing in conflict with commitments to mitigate inequities. In this study, we developed a spatial optimization model to choose the best locations for vaccination sites. The model is a modified two-step maximal covering location problem (MCLP). It aims at maximizing the number of residents who can conveniently access the sites and mitigating inequity issues by prioritizing disadvantaged population groups who live in geographic areas identified through the CDC’s Social Vulnerability Index (SVI). We conducted our study using the case of Hillsborough County, Florida. We found that by reserving up to 30% of total vaccines for highly vulnerable communities, our model can optimize location choices for vaccination sites to provide effective coverage for residents at large while prioritizing disadvantaged groups of people. A series of sensitivity analyses have been performed to evaluate the impact of parameters such as site capacity and distance threshold. The model has the potential to guide the future allocation of critical medical resources in the U.S. and other countries. |
format | Online Article Text |
id | pubmed-9566030 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95660302022-10-15 Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida Chen, Yuzhou Tao, Ran Downs, Joni Int J Environ Res Public Health Article The equitable allocation of COVID-19 vaccines is a critical challenge worldwide, given that the pandemic has been disproportionally affecting economically disadvantaged racial and ethnic groups. In the United States, the ongoing implementation efforts at different administrative levels and districts, to some extent, are standing in conflict with commitments to mitigate inequities. In this study, we developed a spatial optimization model to choose the best locations for vaccination sites. The model is a modified two-step maximal covering location problem (MCLP). It aims at maximizing the number of residents who can conveniently access the sites and mitigating inequity issues by prioritizing disadvantaged population groups who live in geographic areas identified through the CDC’s Social Vulnerability Index (SVI). We conducted our study using the case of Hillsborough County, Florida. We found that by reserving up to 30% of total vaccines for highly vulnerable communities, our model can optimize location choices for vaccination sites to provide effective coverage for residents at large while prioritizing disadvantaged groups of people. A series of sensitivity analyses have been performed to evaluate the impact of parameters such as site capacity and distance threshold. The model has the potential to guide the future allocation of critical medical resources in the U.S. and other countries. MDPI 2022-09-29 /pmc/articles/PMC9566030/ /pubmed/36231743 http://dx.doi.org/10.3390/ijerph191912443 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Yuzhou Tao, Ran Downs, Joni Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title | Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title_full | Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title_fullStr | Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title_full_unstemmed | Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title_short | Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida |
title_sort | location optimization of covid-19 vaccination sites: case in hillsborough county, florida |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566030/ https://www.ncbi.nlm.nih.gov/pubmed/36231743 http://dx.doi.org/10.3390/ijerph191912443 |
work_keys_str_mv | AT chenyuzhou locationoptimizationofcovid19vaccinationsitescaseinhillsboroughcountyflorida AT taoran locationoptimizationofcovid19vaccinationsitescaseinhillsboroughcountyflorida AT downsjoni locationoptimizationofcovid19vaccinationsitescaseinhillsboroughcountyflorida |