Monitoring the evolving impacts of non-pharmaceutical intervention measures requires fine-grained estimation of transmission dynamics. We propose a framework to estimate instantaneous reproduction number R_t using Bayesian inference upon a renewal process, disentangling the R_t reduction into mitigation and suppression factors for quantifying their impacts at a finer granularity. Investigating the impacts of intervention measures of European countries, the United States and Wuhan with the framework, we reveal the effects of interventions in Europe and alert that 30 states in the United States are facing resurgence risks.

+More

framework estimation of transmission dynamics suppression factors mitigation bayesian inference instantaneous reproduction number rt

Li, Ling,Wang, Shuo, Guo, Yike, Huang, Yuan, Teng, Zhongzhao, Yang, Xian,.Monitoring the Impacts of Government Interventions to Contain COVID-19: A Quantitative Approach. (),.

Li, Ling, et al."Monitoring the Impacts of Government Interventions to Contain COVID-19: A Quantitative Approach"

Li, Ling,Wang, Shuo, Guo, Yike, Huang, Yuan, Teng, Zhongzhao, Yang, Xian,"Monitoring the Impacts of Government Interventions to Contain COVID-19: A Quantitative Approach"