Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept

Geospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and populat...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Susanne F. Awad, Godfrey Musuka, Zindoga Mukandavire, Dillon Froass, Neil J. MacKinnon, Diego F. Cuadros
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
R
Acceso en línea:https://doaj.org/article/fb897a655e5e409da0c85f5fd550a2dd
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:fb897a655e5e409da0c85f5fd550a2dd
record_format dspace
spelling oai:doaj.org-article:fb897a655e5e409da0c85f5fd550a2dd2021-11-25T19:10:26ZImplementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept10.3390/vaccines91112422076-393Xhttps://doaj.org/article/fb897a655e5e409da0c85f5fd550a2dd2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-393X/9/11/1242https://doaj.org/toc/2076-393XGeospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and population-level risk assessment. For proof of concept, we adapted a spatially explicit COVID-19 model to investigate a hypothetical geospatial targeting of COVID-19 vaccine rollout in Ohio, United States, at the early phase of COVID-19 pandemic. The population-level deterministic compartmental model, incorporating spatial-geographic components at the county level, was formulated using a set of differential equations stratifying the population according to vaccination status and disease epidemiological characteristics. Three different hypothetical scenarios focusing on geographical subpopulation targeting (areas with high versus low infection intensity) were investigated. Our results suggest that a vaccine program that distributes vaccines equally across the entire state effectively averts infections and hospitalizations (2954 and 165 cases, respectively). However, in a context with equitable vaccine allocation, the number of COVID-19 cases in high infection intensity areas will remain high; the cumulative number of cases remained >30,000 cases. A vaccine program that initially targets high infection intensity areas has the most significant impact in reducing new COVID-19 cases and infection-related hospitalizations (3756 and 213 infections, respectively). Our approach demonstrates the importance of factoring geospatial attributes to the design and implementation of vaccination programs in a context with limited resources during the early stage of the vaccine rollout.Susanne F. AwadGodfrey MusukaZindoga MukandavireDillon FroassNeil J. MacKinnonDiego F. CuadrosMDPI AGarticlevaccination programgeospatial attributesspatial epidemiologydisease mappingCOVID-19mathematical modelMedicineRENVaccines, Vol 9, Iss 1242, p 1242 (2021)
institution DOAJ
collection DOAJ
language EN
topic vaccination program
geospatial attributes
spatial epidemiology
disease mapping
COVID-19
mathematical model
Medicine
R
spellingShingle vaccination program
geospatial attributes
spatial epidemiology
disease mapping
COVID-19
mathematical model
Medicine
R
Susanne F. Awad
Godfrey Musuka
Zindoga Mukandavire
Dillon Froass
Neil J. MacKinnon
Diego F. Cuadros
Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
description Geospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and population-level risk assessment. For proof of concept, we adapted a spatially explicit COVID-19 model to investigate a hypothetical geospatial targeting of COVID-19 vaccine rollout in Ohio, United States, at the early phase of COVID-19 pandemic. The population-level deterministic compartmental model, incorporating spatial-geographic components at the county level, was formulated using a set of differential equations stratifying the population according to vaccination status and disease epidemiological characteristics. Three different hypothetical scenarios focusing on geographical subpopulation targeting (areas with high versus low infection intensity) were investigated. Our results suggest that a vaccine program that distributes vaccines equally across the entire state effectively averts infections and hospitalizations (2954 and 165 cases, respectively). However, in a context with equitable vaccine allocation, the number of COVID-19 cases in high infection intensity areas will remain high; the cumulative number of cases remained >30,000 cases. A vaccine program that initially targets high infection intensity areas has the most significant impact in reducing new COVID-19 cases and infection-related hospitalizations (3756 and 213 infections, respectively). Our approach demonstrates the importance of factoring geospatial attributes to the design and implementation of vaccination programs in a context with limited resources during the early stage of the vaccine rollout.
format article
author Susanne F. Awad
Godfrey Musuka
Zindoga Mukandavire
Dillon Froass
Neil J. MacKinnon
Diego F. Cuadros
author_facet Susanne F. Awad
Godfrey Musuka
Zindoga Mukandavire
Dillon Froass
Neil J. MacKinnon
Diego F. Cuadros
author_sort Susanne F. Awad
title Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
title_short Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
title_full Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
title_fullStr Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
title_full_unstemmed Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
title_sort implementation of a vaccination program based on epidemic geospatial attributes: covid-19 pandemic in ohio as a case study and proof of concept
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/fb897a655e5e409da0c85f5fd550a2dd
work_keys_str_mv AT susannefawad implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
AT godfreymusuka implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
AT zindogamukandavire implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
AT dillonfroass implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
AT neiljmackinnon implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
AT diegofcuadros implementationofavaccinationprogrambasedonepidemicgeospatialattributescovid19pandemicinohioasacasestudyandproofofconcept
_version_ 1718410256183197696