Cargando…

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVI...

Descripción completa

Detalles Bibliográficos
Autores principales: Mollalo, Abolfazl, Tatar, Moosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467210/
https://www.ncbi.nlm.nih.gov/pubmed/34574416
http://dx.doi.org/10.3390/ijerph18189488
_version_ 1784573339041267712
author Mollalo, Abolfazl
Tatar, Moosa
author_facet Mollalo, Abolfazl
Tatar, Moosa
author_sort Mollalo, Abolfazl
collection PubMed
description Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.
format Online
Article
Text
id pubmed-8467210
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-84672102021-09-27 Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States Mollalo, Abolfazl Tatar, Moosa Int J Environ Res Public Health Article Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective. MDPI 2021-09-08 /pmc/articles/PMC8467210/ /pubmed/34574416 http://dx.doi.org/10.3390/ijerph18189488 Text en © 2021 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
Mollalo, Abolfazl
Tatar, Moosa
Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title_full Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title_fullStr Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title_full_unstemmed Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title_short Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States
title_sort spatial modeling of covid-19 vaccine hesitancy in the united states
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467210/
https://www.ncbi.nlm.nih.gov/pubmed/34574416
http://dx.doi.org/10.3390/ijerph18189488
work_keys_str_mv AT mollaloabolfazl spatialmodelingofcovid19vaccinehesitancyintheunitedstates
AT tatarmoosa spatialmodelingofcovid19vaccinehesitancyintheunitedstates