Author: Xiaolin Zhu; Aiyin Zhang; Shuai Xu; Pengfei Jia; Xiaoyue Tan; Jiaqi Tian; Tao Wei; Zhenxian Quan; Jiali Yu
Title: Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China Document date: 2020_2_11
ID: 6u9q0ox9_25
Snippet: Our modeling work has several limitations. First, due to the limited prior knowledge for this sudden 2019-nCoV outbreak, the infection rate and recovery rate in this study are regarded as the same for different age groups, which may result in errors of predication for cities with different age structures. Second, the model parameters were estimated using the reported confirmed cases that may be lower than the actual number of infections, so param.....
Document: Our modeling work has several limitations. First, due to the limited prior knowledge for this sudden 2019-nCoV outbreak, the infection rate and recovery rate in this study are regarded as the same for different age groups, which may result in errors of predication for cities with different age structures. Second, the model parameters were estimated using the reported confirmed cases that may be lower than the actual number of infections, so parameter estimation may not represent the real situation. Third, besides transmission between Wuhan and other cities, we do not consider other inter-city transmissions. Although the Chinese government strictly controlled the traffic between cities, the inter-city transmission may contribute to the epidemic dynamics in future days, especially during days of work resuming.
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