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_28
Snippet: Page 5 of 27 All Rights Reserved at an earlier time will expose more currently susceptible population to the epidemic, since they will falsely believe that they are safe from the disease after the advent of the ineffective therapeutic. On the other hand, the loss function also penalizes correct approval decisions made at later stages of an epidemic via to the cumulative infected and death terms, and . A correct but delayed approval decision for t.....
Document: Page 5 of 27 All Rights Reserved at an earlier time will expose more currently susceptible population to the epidemic, since they will falsely believe that they are safe from the disease after the advent of the ineffective therapeutic. On the other hand, the loss function also penalizes correct approval decisions made at later stages of an epidemic via to the cumulative infected and death terms, and . A correct but delayed approval decision for the therapeutic is less valuable since it will save fewer susceptible people from infection and death. The Bayesian decision model considers the null hypothesis 0 that the anti-infective therapeutic (or vaccine) has no clinical effect, against the alternative hypothesis that it has positive clinical effect with signal-to-noise ratio . We use and to denote the Bayesian prior probabilities of 0 and 1, respectively.
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