Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics

Background: The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. Methods: Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic...

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Autores principales:	Kevin C Ma, Tigist F Menkir, Stephen Kissler, Yonatan H Grad, Marc Lipsitch
Formato:	article
Lenguaje:	EN
Publicado:	eLife Sciences Publications Ltd 2021
Materias:	SARS-CoV-2 COVID-19 mathematical modeling Herd immunity Medicine R Science Q Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/362826aa0327484092c9edd88e32d3c8
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id	oai:doaj.org-article:362826aa0327484092c9edd88e32d3c8
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spelling	oai:doaj.org-article:362826aa0327484092c9edd88e32d3c82021-11-15T07:21:25ZModeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics10.7554/eLife.666012050-084Xe66601https://doaj.org/article/362826aa0327484092c9edd88e32d3c82021-05-01T00:00:00Zhttps://elifesciences.org/articles/66601https://doaj.org/toc/2050-084XBackground: The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. Methods: Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups. Results: A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. Conclusions: Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection. Funding: K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277.Kevin C MaTigist F MenkirStephen KisslerYonatan H GradMarc LipsitcheLife Sciences Publications LtdarticleSARS-CoV-2COVID-19mathematical modelingHerd immunityMedicineRScienceQBiology (General)QH301-705.5ENeLife, Vol 10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	SARS-CoV-2 COVID-19 mathematical modeling Herd immunity Medicine R Science Q Biology (General) QH301-705.5
spellingShingle	SARS-CoV-2 COVID-19 mathematical modeling Herd immunity Medicine R Science Q Biology (General) QH301-705.5 Kevin C Ma Tigist F Menkir Stephen Kissler Yonatan H Grad Marc Lipsitch Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
description	Background: The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. Methods: Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups. Results: A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. Conclusions: Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection. Funding: K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277.
format	article
author	Kevin C Ma Tigist F Menkir Stephen Kissler Yonatan H Grad Marc Lipsitch
author_facet	Kevin C Ma Tigist F Menkir Stephen Kissler Yonatan H Grad Marc Lipsitch
author_sort	Kevin C Ma
title	Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
title_short	Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
title_full	Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
title_fullStr	Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
title_full_unstemmed	Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics
title_sort	modeling the impact of racial and ethnic disparities on covid-19 epidemic dynamics
publisher	eLife Sciences Publications Ltd
publishDate	2021
url	https://doaj.org/article/362826aa0327484092c9edd88e32d3c8
work_keys_str_mv	AT kevincma modelingtheimpactofracialandethnicdisparitiesoncovid19epidemicdynamics AT tigistfmenkir modelingtheimpactofracialandethnicdisparitiesoncovid19epidemicdynamics AT stephenkissler modelingtheimpactofracialandethnicdisparitiesoncovid19epidemicdynamics AT yonatanhgrad modelingtheimpactofracialandethnicdisparitiesoncovid19epidemicdynamics AT marclipsitch modelingtheimpactofracialandethnicdisparitiesoncovid19epidemicdynamics
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Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics

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