Selected article for: "death lead and mortality rate"
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_43
    Snippet: Finally, when the mortality rate increases from the level of COVID-19 (Onder et al. 2020; World Health Organization, 2020) , to the level of SARS (World Health Organization, 2003) , and further to the level MERS (World Health Organization, 2019), the optimal sample sizes for both non-adaptive and adaptive Bayesian models decrease and the optimal Type I error rates increase (Rows 7 to 12 of Table 3 ). When the epidemic is more lethal, the Bayesian.....
    Document: Finally, when the mortality rate increases from the level of COVID-19 (Onder et al. 2020; World Health Organization, 2020) , to the level of SARS (World Health Organization, 2003) , and further to the level MERS (World Health Organization, 2019), the optimal sample sizes for both non-adaptive and adaptive Bayesian models decrease and the optimal Type I error rates increase (Rows 7 to 12 of Table 3 ). When the epidemic is more lethal, the Bayesian adaptive model requires fewer subjects in the RCT, since both Type I and Type II errors will lead to greater losses due to death by infection. The higher death tolls provides significantly more incentive in the Bayesian adaptive framework to approve the therapeutic in the hopes of saving more people from future infection and death.

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