Selected article for: "complete set and epidemic model"
Author: Hongzhe Zhang; Xiaohang Zhao; Kexin Yin; Yiren Yan; Wei Qian; Bintong Chen; Xiao Fang
Title: Dynamic Estimation of Epidemiological Parameters of COVID-19 Outbreak and Effects of Interventions on Its Spread
  • Document date: 2020_4_6
    • ID: ff4937mj_47
    Snippet: Since the Chinese government responds with evolving containment and mitigation actions towards the development of COVID-19, to obtain updated information on the parameters Θ, we adopt a rolling window approach to estimate Θ for each short time period [t, t+1, ..., t+T ], where the window size is T days and t = 1, 2, 3, · · · . In this study, we use a 10-day time window, i.e., T = 10; also the first day with t = 1 in our analysis corresponds .....
    Document: Since the Chinese government responds with evolving containment and mitigation actions towards the development of COVID-19, to obtain updated information on the parameters Θ, we adopt a rolling window approach to estimate Θ for each short time period [t, t+1, ..., t+T ], where the window size is T days and t = 1, 2, 3, · · · . In this study, we use a 10-day time window, i.e., T = 10; also the first day with t = 1 in our analysis corresponds to January 18, 2020. For each time period starting at t, we denote Θ t = Θ as the parameters of interests. Besides, noting that to complete our Bayesian estimation scheme, we need to set initial values for the epidemic model. Correspondingly, for t = 1, we set (Q 1 , R 1 ) as Q 1 = Q e 1 = 1 a 1 Q o 1 and R 1 = R e 1 = 1 b 1 R o 1 , which implies that

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