Selected article for: "dynamic model and epidemic evolution"
Author: Yuan Zhang; Chong You; Zhenghao Cai; Jiarui Sun; Wenjie Hu; Xiao-Hua Zhou
Title: Prediction of the COVID-19 outbreak based on a realistic stochastic model
  • Document date: 2020_3_13
    • ID: 0xzsa21a_95
    Snippet: Based on the estimated parameters, future trajectories of the epidemic are simulated using the proposed stochastic dynamic model. For each region, 1000 simulations are conducted to produce the 95% confidence interval for the epidemic evolution of some key populations. In this section, the predictions of populations of states, the containment time of the outbreak, the controlled reproduction number R c , and a test on the effectiveness of the curr.....
    Document: Based on the estimated parameters, future trajectories of the epidemic are simulated using the proposed stochastic dynamic model. For each region, 1000 simulations are conducted to produce the 95% confidence interval for the epidemic evolution of some key populations. In this section, the predictions of populations of states, the containment time of the outbreak, the controlled reproduction number R c , and a test on the effectiveness of the current medical tracking policy are reported. Figure 4 plots the 95% confidence interval of:

    Search related documents:
    Co phrase search for related documents
    • dynamic model and future trajectory: 1
    • dynamic model and key population: 1
    • dynamic model and medical tracking: 1, 2
    • dynamic model and propose stochastic dynamic model: 1, 2, 3
    • dynamic model and state population: 1, 2, 3, 4, 5, 6, 7, 8
    • dynamic model and stochastic dynamic model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56
    • epidemic evolution and estimate parameter: 1, 2, 3
    • epidemic evolution and key population: 1, 2, 3
    • epidemic evolution and propose stochastic dynamic model: 1, 2
    • epidemic evolution and state population: 1, 2, 3
    • epidemic evolution and stochastic dynamic model: 1, 2, 3
    • epidemic future trajectory and future trajectory: 1, 2, 3, 4, 5, 6
    • estimate parameter and future trajectory: 1
    • future trajectory and key population: 1
    • key population and state population: 1
    • medical tracking and outbreak containment time: 1
    • medical tracking and stochastic dynamic model: 1, 2
    • medical tracking policy and outbreak containment time: 1
    • propose stochastic dynamic model and stochastic dynamic model: 1, 2, 3