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Mobile phone data reveal spatiotemporal dynamics of Omicron infections in Beijing after relaxing zero-COVID policy

Authors :
Yan, Xiaorui
Song, Ci
Pei, Tao
Ge, Erjia
Liu, Le
Wang, Xi
Jiang, Linfeng
Publication Year :
2023

Abstract

The swift relaxation of the zero-COVID policy in December 2022 led to an unprecedented surge in Omicron variant infections in China. With the suspension of mandatory testing, tracking this epidemic outbreak was challenging because infections were often underrepresented in survey and testing results, which only involved partial populations. We used large-scale mobile phone data to estimate daily infections in Beijing from November 2022 to January 2023. We demonstrated that an individual's location records of mobile phone could be used to infer his or her infectious status. Then, the derived status of millions of individuals could be summed to reconstruct the citywide spatiotemporal dynamics of infections. We found that the infection incidence peaked on 21 December, and 80.1% of populations had been infected by 14 January 2023 in Beijing. Furthermore, infection dynamics exhibited significant demographic and spatiotemporal disparities. Our work provides a ubiquitous and high-coverage data source for monitoring epidemic outbreaks.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2307.05500
Document Type :
Working Paper