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Detecting Suspected Epidemic Cases Using Trajectory Big Data
CSIAM Transaction on Applied Mathematics
Emerging infectious diseases are existential threats to human health and global stability. The recent outbreaks of the novel coronavirus COVID-19 have rapidly formed a global pandemic, causing hundreds of thousands of infections and huge economic loss. The WHO declares that more precise measures to track, detect and isolate infected people are among the most effective means to quickly contain the outbreak. Based on trajectory provided by the big data and the mean field theory, we establish andoi:10.4208/csam.2020-0006 fatcat:5llrsfk3hrgpzljruge7655ria