Author: Glenn F Webb; Pierre Magal; Zhihua Liu; Ousmane Seydi
Title: A model to predict COVID-19 epidemics with applications to South Korea, Italy, and Spain Document date: 2020_4_10
ID: c95lntyp_46
Snippet: We have applied a method developed in [1] , [2] , [3] to predict the evolution of a COVID-19 epidemic in a geographical region, based on reported case data in that region. Our model focuses on unreported cases, asymptomatic infectious cases, and the division of the epidemic evolution through a succession of phases. Our method can be predictive, when the epidemic is growing exponentially in Phase II. In [1] we demonstrated a method to identify the.....
Document: We have applied a method developed in [1] , [2] , [3] to predict the evolution of a COVID-19 epidemic in a geographical region, based on reported case data in that region. Our model focuses on unreported cases, asymptomatic infectious cases, and the division of the epidemic evolution through a succession of phases. Our method can be predictive, when the epidemic is growing exponentially in Phase II. In [1] we demonstrated a method to identify the Phase II exponentially increasing rate of cumulative reported cases. When public measures are begun in Phase II, to ameliorate the epidemic, we model these measures with a time-dependent exponentially decreasing transmission rate. These measures result in a subsequent reduction in daily reported cases, which we call Phase III. We determine the transition from Phase II to Phase III, which may require more than a week, in the model simulations.
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