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Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States

Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States

来源:medRxiv_logomedRxiv
英文摘要

Abstract Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ?0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ?0 relates to a herd immunity threshold (HIT), which is given by 1 ? 1/?0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ?0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ?0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21-January-2020 to 21-June-2020. Our ?0 estimates characterize infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we find that no state has achieved herd immunity as of 20-September-2021. Significance StatementCOVID-19 will continue to threaten non-immune persons in the presence of ongoing disease transmission. We can estimate when sustained disease transmission will end by calculating the population-specific basic reproduction number ?0, which relates to a herd immunity threshold (HIT), given by 1 ? 1/?0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely. Here, we report state-level ?0 estimates indicating that disease transmission varies considerably across states. Our ?0 estimates can also be used to determine HITs for the Delta variant of COVID-19. On the basis of Delta-adjusted HITs, vaccination data, and serological survey results, we find that no state has yet achieved herd immunity.

Neumann Jacob、Lin Yen Ting、Miller Ely F.、Mallela Abhishek、Chen Ye、Hlavacek William S.、Posner Richard G.

Department of Biological Sciences, Northern Arizona UniversityComputer, Computational and Statistical Sciences Division, Los Alamos National LaboratoryDepartment of Biological Sciences, Northern Arizona UniversityDepartment of Mathematics, University of CaliforniaDepartment of Mathematics and Statistics, Northern Arizona UniversityTheoretical Division, Los Alamos National LaboratoryDepartment of Biological Sciences, Northern Arizona University

10.1101/2021.09.27.21264188

医药卫生理论医学研究方法预防医学

mathematical modelcoronavirus disease 2019 (COVID-19)basic reproduction numberherd immunityBayesian inference

Neumann Jacob,Lin Yen Ting,Miller Ely F.,Mallela Abhishek,Chen Ye,Hlavacek William S.,Posner Richard G..Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States[EB/OL].(2025-03-28)[2025-05-18].https://www.medrxiv.org/content/10.1101/2021.09.27.21264188.点此复制

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