A model and predictions for COVID-19 considering population behavior and vaccination

Abstract The effect of vaccination coupled with the behavioral response of the population is not well understood. Our model incorporates two important dynamically varying population behaviors: level of caution and sense of safety. Level of caution increases with infectious cases, while an increasing...

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Autores principales:	Thomas Usherwood, Zachary LaJoie, Vikas Srivastava
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/006a05c00db84b62b55d5ac071ecd6ea
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spelling	oai:doaj.org-article:006a05c00db84b62b55d5ac071ecd6ea2021-12-02T17:30:54ZA model and predictions for COVID-19 considering population behavior and vaccination10.1038/s41598-021-91514-72045-2322https://doaj.org/article/006a05c00db84b62b55d5ac071ecd6ea2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-91514-7https://doaj.org/toc/2045-2322Abstract The effect of vaccination coupled with the behavioral response of the population is not well understood. Our model incorporates two important dynamically varying population behaviors: level of caution and sense of safety. Level of caution increases with infectious cases, while an increasing sense of safety with increased vaccination lowers precautions. Our model accurately reproduces the complete time history of COVID-19 infections for various regions of the United States. We propose a parameter $$d_I$$ d I as a direct measure of a population’s caution against an infectious disease that can be obtained from the infectious cases. The model provides quantitative measures of highest disease transmission rate, effective transmission rate, and cautionary behavior. We predict future COVID-19 trends in the United States accounting for vaccine rollout and behavior. Although a high rate of vaccination is critical to quickly ending the pandemic, a return towards pre-pandemic social behavior due to increased sense of safety during vaccine deployment can cause an alarming surge in infections. Our results predict that at the current rate of vaccination, the new infection cases for COVID-19 in the United States will approach zero by August 2021. This model can be used for other regions and for future epidemics and pandemics.Thomas UsherwoodZachary LaJoieVikas SrivastavaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Thomas Usherwood Zachary LaJoie Vikas Srivastava A model and predictions for COVID-19 considering population behavior and vaccination
description	Abstract The effect of vaccination coupled with the behavioral response of the population is not well understood. Our model incorporates two important dynamically varying population behaviors: level of caution and sense of safety. Level of caution increases with infectious cases, while an increasing sense of safety with increased vaccination lowers precautions. Our model accurately reproduces the complete time history of COVID-19 infections for various regions of the United States. We propose a parameter $$d_I$$ d I as a direct measure of a population’s caution against an infectious disease that can be obtained from the infectious cases. The model provides quantitative measures of highest disease transmission rate, effective transmission rate, and cautionary behavior. We predict future COVID-19 trends in the United States accounting for vaccine rollout and behavior. Although a high rate of vaccination is critical to quickly ending the pandemic, a return towards pre-pandemic social behavior due to increased sense of safety during vaccine deployment can cause an alarming surge in infections. Our results predict that at the current rate of vaccination, the new infection cases for COVID-19 in the United States will approach zero by August 2021. This model can be used for other regions and for future epidemics and pandemics.
format	article
author	Thomas Usherwood Zachary LaJoie Vikas Srivastava
author_facet	Thomas Usherwood Zachary LaJoie Vikas Srivastava
author_sort	Thomas Usherwood
title	A model and predictions for COVID-19 considering population behavior and vaccination
title_short	A model and predictions for COVID-19 considering population behavior and vaccination
title_full	A model and predictions for COVID-19 considering population behavior and vaccination
title_fullStr	A model and predictions for COVID-19 considering population behavior and vaccination
title_full_unstemmed	A model and predictions for COVID-19 considering population behavior and vaccination
title_sort	model and predictions for covid-19 considering population behavior and vaccination
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/006a05c00db84b62b55d5ac071ecd6ea
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A model and predictions for COVID-19 considering population behavior and vaccination

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