Nationwide mobile phone data tracking aggregated movements of people in China can accurately predict the geographical and temporal spread of COVID-19 infections up to two weeks ahead of time, according to a study in Nature. The study analysed the distribution of population outflows from Wuhan, China, during the early stages of the COVID-19 outbreak in January 2020.
Large-scale population movements can contribute to localized outbreaks of a disease becoming widespread epidemics. However, monitoring such aggregated population flows, such as the chunyun period of mass travel in China in the run-up to the Chinese Lunar New Year’s Eve on 24 January 2020, can prove challenging.
Nicholas Christakis and colleagues studied anonymized mobile phone data from a major national carrier in China to analyse the movements of more than 11 million people who spent at least 2 hours in Wuhan between 1 and 24 January 2020, when the quarantine was imposed. They linked these data to COVID-19 infection rates until 19 February from 296 prefectures in 31 provinces and regions throughout China.
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