A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating R 0 and social distancing behaviour.

Autor: Luisa Vissat L; Department of Environmental Science, Policy, and Management, UC Berkeley, CA 94720, USA., Horvitz N; Department of Environmental Science, Policy, and Management, UC Berkeley, CA 94720, USA., Phillips RV; Division Environmental Health Sciences, UC Berkeley, CA 94720, USA., Miao Z; Department of Environmental Science, Policy, and Management, UC Berkeley, CA 94720, USA., Mgbara W; Department of Environmental Science, Policy, and Management, UC Berkeley, CA 94720, USA., You Y; Division Environmental Health Sciences, UC Berkeley, CA 94720, USA., Salter R; Computer Science Department, Oberlin College, Oberlin, Ohio, OH 44074, USA., Hubbard AE; Division Environmental Health Sciences, UC Berkeley, CA 94720, USA., Getz WM; Department of Environmental Science, Policy, and Management, UC Berkeley, CA 94720, USA; Division Environmental Health Sciences, UC Berkeley, CA 94720, USA; School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban 4000, South Africa. Electronic address: wgetz@berkeley.edu.
Jazyk: angličtina
Zdroj: Epidemics [Epidemics] 2022 Dec; Vol. 41, pp. 100640. Date of Electronic Publication: 2022 Oct 10.
DOI: 10.1016/j.epidem.2022.100640
Abstrakt: We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R 0 for each CSA. Values of R 0 ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index c flatten . Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found c flatten to be more influential in the clustering process than R 0 . Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R 0 itself.
Competing Interests: Declaration of Competing Interest Wayne M. Getz and Richard Salter are two of three owners of Numerus Inc., which is responsible for developing and maintaining the SCLAIV+D web app used in our exponential curving fitting and social-behaviour-driven curve-flattening analyses.
(Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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