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Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China
Science ( IF 56.9 ) Pub Date : 2020-04-08 , DOI: 10.1126/science.abb4557 Benjamin F Maier 1 , Dirk Brockmann 1, 2
Science ( IF 56.9 ) Pub Date : 2020-04-08 , DOI: 10.1126/science.abb4557 Benjamin F Maier 1 , Dirk Brockmann 1, 2
Affiliation
Containment works National governments have taken different approaches in response to the coronavirus disease 2019 (COVID-19) pandemic, ranging from draconian quarantines to laissez-faire mitigation strategies. In data from China collected in February 2020, Maier and Brockmann noticed that, unexpectedly, the epidemic did not take off exponentially. Nonexponential spread occurs when the supply of susceptible individuals is depleted on a time scale comparable to the infectious period of the virus. The results of the authors' modeling approach indicate that the public response to the epidemic plus containment policies were becoming effective despite the initial increase in confirmed cases. Science, this issue p. 742 Feedback between the epidemic process, the behavioral response to it, and nationwide containment policies can restrain COVID-19. The recent outbreak of coronavirus disease 2019 (COVID-19) in mainland China was characterized by a distinctive subexponential increase of confirmed cases during the early phase of the epidemic, contrasting with an initial exponential growth expected for an unconstrained outbreak. We show that this effect can be explained as a direct consequence of containment policies that effectively deplete the susceptible population. To this end, we introduce a parsimonious model that captures both quarantine of symptomatic infected individuals, as well as population-wide isolation practices in response to containment policies or behavioral changes, and show that the model captures the observed growth behavior accurately. The insights provided here may aid the careful implementation of containment strategies for ongoing secondary outbreaks of COVID-19 or similar future outbreaks of other emergent infectious diseases.
更新日期：2020-04-08
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