Author: Qingyang Xu; Shomesh Chaudhuri; Danying Xiao; Andrew W Lo
Title: Bayesian Adaptive Clinical Trials for Anti-Infective Therapeutics during Epidemic Outbreaks Document date: 2020_4_14
ID: 20hk99h4_16
Snippet: Here and denote the infection rates in the initial and final stages of the epidemic (with ), respectively, denotes the half-life of the decay in infection rate, and the length of the time window when this decay occurred. A larger difference corresponds to more significant reduction of epidemic transmission, a smaller value of corresponds to a speedier decision to enforce the NPI, and a smaller value of corresponds to more strict enforcement of th.....
Document: Here and denote the infection rates in the initial and final stages of the epidemic (with ), respectively, denotes the half-life of the decay in infection rate, and the length of the time window when this decay occurred. A larger difference corresponds to more significant reduction of epidemic transmission, a smaller value of corresponds to a speedier decision to enforce the NPI, and a smaller value of corresponds to more strict enforcement of the NPI since decays more rapidly. We calibrate the values 3 and 1.5 based on the estimates of the dynamic transmission rate of COVID-19 in Wuhan, China from December 2019 to February 2020 (Kucharski et al., 2020) . We consider different values of and to reflect the variability in timing and stringency of NPIs enforced by governments around the globe.
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