Author: Qinghe Liu; Zhicheng Liu; Deqiang Li; Zefei Gao; Junkai Zhu; Junyan Yang; Qiao Wang
Title: Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China Document date: 2020_2_11
ID: 5dd89gnm_26
Snippet: Return trend, school opens days are mostly concentrated in this stage. Our model will simulate stage 2, 3 and 4. Assume that in each stage, the recovery rates are relatively consistent, in terms of the natural recovery of self-recovered and medical treatment. But at each stage, the infection rate and the population can vary dramatically. For the first two stages, the spread of the virus satisfies the exponential distribution. For the third stage,.....
Document: Return trend, school opens days are mostly concentrated in this stage. Our model will simulate stage 2, 3 and 4. Assume that in each stage, the recovery rates are relatively consistent, in terms of the natural recovery of self-recovered and medical treatment. But at each stage, the infection rate and the population can vary dramatically. For the first two stages, the spread of the virus satisfies the exponential distribution. For the third stage, it is found that there is a large number of population flows in and out because of the transportation during Spring Festival. For the third stage, there are a large number of population flows out from Wuhan, because of the Spring Festival as well as the panic. In this case, F will increase sharply. After then, traffic blockage will make F decrease. Due to self-protection and quarantine, the quarantine factor ε increases, then ߚ decline. For the recovery rate parameters, we collected the empirical data related to pneumonia as the prior distributions.
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