Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey

COVID-19 created an unprecedented global public health crisis during 2020–2021. The severity of the fast-spreading infection, combined with uncertainties regarding the physical and biological processes affecting transmission of SARS-CoV-2, posed enormous challenges to healthcare systems. Pandemic dy...

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Autores principales:	Xiang Ren, Clifford P. Weisel, Panos G. Georgopoulos
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 SARS-CoV-2 stochastic SEIR (Susceptible Exposed Infected Recovered) model Medicine R
Acceso en línea:	https://doaj.org/article/26c2355910d64e45a4433138061bcf61
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id	oai:doaj.org-article:26c2355910d64e45a4433138061bcf61
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spelling	oai:doaj.org-article:26c2355910d64e45a4433138061bcf612021-11-25T17:49:44ZModeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey10.3390/ijerph1822119501660-46011661-7827https://doaj.org/article/26c2355910d64e45a4433138061bcf612021-11-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/22/11950https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601COVID-19 created an unprecedented global public health crisis during 2020–2021. The severity of the fast-spreading infection, combined with uncertainties regarding the physical and biological processes affecting transmission of SARS-CoV-2, posed enormous challenges to healthcare systems. Pandemic dynamics exhibited complex spatial heterogeneities across multiple scales, as local demographic, socioeconomic, behavioral and environmental factors were modulating population exposures and susceptibilities. Before effective pharmacological interventions became available, controlling exposures to SARS-CoV-2 was the only public health option for mitigating the disease; therefore, models quantifying the impacts of heterogeneities and alternative exposure interventions on COVID-19 outcomes became essential tools informing policy development. This study used a stochastic SEIR framework, modeling each of the 21 New Jersey counties, to capture important heterogeneities of COVID-19 outcomes across the State. The models were calibrated using confirmed daily deaths and SQMC optimization and subsequently applied in predictive and exploratory modes. The predictions achieved good agreement between modeled and reported death data; counterfactual analysis was performed to assess the effectiveness of layered interventions on reducing exposures to SARS-CoV-2 and thereby fatality of COVID-19. The modeling analysis of the reduction in exposures to SARS-CoV-2 achieved through concurrent social distancing and face-mask wearing estimated that 357 [IQR (290, 429)] deaths per 100,000 people were averted.Xiang RenClifford P. WeiselPanos G. GeorgopoulosMDPI AGarticleCOVID-19SARS-CoV-2stochastic SEIR (SusceptibleExposedInfectedRecovered) modelMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11950, p 11950 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 SARS-CoV-2 stochastic SEIR (Susceptible Exposed Infected Recovered) model Medicine R
spellingShingle	COVID-19 SARS-CoV-2 stochastic SEIR (Susceptible Exposed Infected Recovered) model Medicine R Xiang Ren Clifford P. Weisel Panos G. Georgopoulos Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
description	COVID-19 created an unprecedented global public health crisis during 2020–2021. The severity of the fast-spreading infection, combined with uncertainties regarding the physical and biological processes affecting transmission of SARS-CoV-2, posed enormous challenges to healthcare systems. Pandemic dynamics exhibited complex spatial heterogeneities across multiple scales, as local demographic, socioeconomic, behavioral and environmental factors were modulating population exposures and susceptibilities. Before effective pharmacological interventions became available, controlling exposures to SARS-CoV-2 was the only public health option for mitigating the disease; therefore, models quantifying the impacts of heterogeneities and alternative exposure interventions on COVID-19 outcomes became essential tools informing policy development. This study used a stochastic SEIR framework, modeling each of the 21 New Jersey counties, to capture important heterogeneities of COVID-19 outcomes across the State. The models were calibrated using confirmed daily deaths and SQMC optimization and subsequently applied in predictive and exploratory modes. The predictions achieved good agreement between modeled and reported death data; counterfactual analysis was performed to assess the effectiveness of layered interventions on reducing exposures to SARS-CoV-2 and thereby fatality of COVID-19. The modeling analysis of the reduction in exposures to SARS-CoV-2 achieved through concurrent social distancing and face-mask wearing estimated that 357 [IQR (290, 429)] deaths per 100,000 people were averted.
format	article
author	Xiang Ren Clifford P. Weisel Panos G. Georgopoulos
author_facet	Xiang Ren Clifford P. Weisel Panos G. Georgopoulos
author_sort	Xiang Ren
title	Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
title_short	Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
title_full	Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
title_fullStr	Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
title_full_unstemmed	Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey
title_sort	modeling effects of spatial heterogeneities and layered exposure interventions on the spread of covid-19 across new jersey
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/26c2355910d64e45a4433138061bcf61
work_keys_str_mv	AT xiangren modelingeffectsofspatialheterogeneitiesandlayeredexposureinterventionsonthespreadofcovid19acrossnewjersey AT cliffordpweisel modelingeffectsofspatialheterogeneitiesandlayeredexposureinterventionsonthespreadofcovid19acrossnewjersey AT panosggeorgopoulos modelingeffectsofspatialheterogeneitiesandlayeredexposureinterventionsonthespreadofcovid19acrossnewjersey
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Modeling Effects of Spatial Heterogeneities and Layered Exposure Interventions on the Spread of COVID-19 across New Jersey

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