Author: Meher K Prakash
Title: Community Memory of COVID-19 Infections Post Lockdown as a Surrogate for Incubation Time Document date: 2020_4_20
ID: 4iwyjk8n_5
Snippet: Eq (1) where µ(t+t; l,k) represents the distribution of the incubation period which we assume to be a Weibull distribution with parameters l and k, without loss of generality. Convoluting two functions such as in Eq. (1) is a standard approach in the linear response theory. We further assume that on any day prior to the lockdown the number of asymptomatic infections is proportional to the number of reported infections (A(-t) = a.I(-t) ). We perf.....
Document: Eq (1) where µ(t+t; l,k) represents the distribution of the incubation period which we assume to be a Weibull distribution with parameters l and k, without loss of generality. Convoluting two functions such as in Eq. (1) is a standard approach in the linear response theory. We further assume that on any day prior to the lockdown the number of asymptomatic infections is proportional to the number of reported infections (A(-t) = a.I(-t) ). We performed a linear regression analysis between the infections observed after lockdown I(t) and the predicted ones I*(t) for various choices of l and k ( Figures 1A,B,C) . The values of l and k for which the regression coefficient was the highest was considered the maximum likelihood estimate of the incubation period ( Figure 1D ).
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