Modelling and Prediction of the 2019 Coronavirus Disease Spreading in China Incorporating Human Migration Data
14 Pages Posted: 5 Mar 2020More...
This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China are collected from Baidu Migration, a mobile-app based human migration tracking data system. Historical data of infected, recovered and death cases from official source are used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimisation procedure is used for estimation of the dynamics of epidemic spreading in the coming months. Our results show that the number of infections in most cities in China will peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively. Moreover, for most cities outside and within Hubei Province (except Wuhan), the total number of infected individuals is expected to be less than 300 and 4000, respectively.
Funding Statement: This work was supported by National Science Foundation of China Project 61703355, Guangdong Youth University Innovative Talents Project 2016KQNCX223, and City University of Hong Kong under Special Fund 9380114.
Declaration of Interests: None.
Keywords: Epidemic spreading; COVID-19; new coronavirus; human migration; travel network
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