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Explaining the Bomb-Like Dynamics of COVID-19 with Modeling and the Implications for Policy
Lin Gary.
Strauss Alexandra T.
Pinz Maxwell.
Martinez Diego A.
Tseng Katie K.
Schueller Emily.
Gatalo Oliver.
Yang Yupeng.
Levin Simon A.
Klein Eili Y.
For the CDC MInD-Healthcare Program.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/2020.04.05.20054338
Using a Bayesian approach to epidemiological compartmental modeling, we demonstrate the bomb-like behavior of exponential growth in COVID-19 cases can be explained by transmission of asymptomatic and mild cases that are typically unreported at the beginning of pandemic events due to lower prevalence of testing. We studied the exponential phase of the pandemic in Italy, Spain, and South Korea, and found the R0 to be 2.56 (95% CrI, 2.41-2.71), 3.23 (95% CrI, 3.06-3.4), and 2.36 (95% CrI, 2.22-2.5) if we use Bayesian priors that assume a large portion of cases are not detected. Weaker priors regarding the detection rate resulted in R0 values of 9.22 (95% CrI, 9.01-9.43), 9.14 (95% CrI, 8.99-9.29), and 8.06 (95% CrI, 7.82-8.3) and assumes nearly 90% of infected patients are identified. Given the mounting evidence that potentially large fractions of the population are asymptomatic, the weaker priors that generate the high R0 values to fit the data required assumptions about the epidemiology of COVID-19 that do not fit with the biology, particularly regarding the timeframe that people remain infectious. Our results suggest that models of transmission assuming a relatively lower R0 value that do not consider a large number of asymptomatic cases can result in misunderstanding of the underlying dynamics, leading to poor policy decisions and outcomes.
www.medrxiv.org
2020
Artículo
https://www.medrxiv.org/content/medrxiv/early/2020/04/07/2020.04.05.20054338.full.pdf
Inglés
VIRUS RESPIRATORIOS
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