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_3
Snippet: To model the updated fine-scale epidemic dynamics of all individual cities in mainland China, we proposed a spatially explicit approach. We first used mobile phone data to obtain the number of people who traveled from Wuhan to each individual city. Then we developed a new epidemiological model based the classic Susceptible-Infectious-Recovered (SIR) model to fit the dynamics of 2019-nCoV at the city level. Finally, we used this model to predict t.....
Document: To model the updated fine-scale epidemic dynamics of all individual cities in mainland China, we proposed a spatially explicit approach. We first used mobile phone data to obtain the number of people who traveled from Wuhan to each individual city. Then we developed a new epidemiological model based the classic Susceptible-Infectious-Recovered (SIR) model to fit the dynamics of 2019-nCoV at the city level. Finally, we used this model to predict the trend under three possible scenarios: the current trend maintained, control efforts expanded, and person-toperson contact increased due to work/school resuming.
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