Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States
| العنوان: | Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States |
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| المؤلفون: | Jacob Neumann, William S. Hlavacek, Abhishek Mallela, Ely F. Miller, Ye Chen, Yen Ting Lin, Richard G. Posner |
| المصدر: | Viruses; Volume 14; Issue 1; Pages: 157 Viruses medRxiv Viruses, Vol 14, Iss 157, p 157 (2022) |
| بيانات النشر: | Multidisciplinary Digital Publishing Institute, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Immunity, Herd, Population, Bayesian inference, Biology, Microbiology, Article, Herd immunity, basic reproduction number, Virology, Statistics, Maximum a posteriori estimation, Seroprevalence, Humans, herd immunity, Fraction (mathematics), education, Epidemics, education.field_of_study, SARS-CoV-2, Uncertainty, COVID-19, Bayes Theorem, QR1-502, United States, Vaccination, Infectious Diseases, coronavirus disease 2019 (COVID-19), Epidemiological Models, Basic reproduction number, mathematical model |
| الوصف: | 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 ℛ0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ0 relates to a herd immunity threshold (HIT), which is given by 1 − 1/ℛ0. 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 ℛ0 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. ℛ0 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 ℛ0 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 ℛ0, which relates to a herd immunity threshold (HIT), given by 1 − 1/ℛ0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely. Here, we report state-level ℛ0 estimates indicating that disease transmission varies considerably across states. Our ℛ0 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. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1999-4915 |
| DOI: | 10.3390/v14010157 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8736dcacd1910672a475e9eb02461a9c |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....8736dcacd1910672a475e9eb02461a9c |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19994915 |
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| DOI: | 10.3390/v14010157 |