Mobile Phone Data To Predict COVID-19 Spread Out Two Weeks In Advance
According to a study, tracking the aggregated activities of people using their mobile phone data may assist predict the geographical and temporal spread of COVID-19 infections as much as two weeks beforehand. The research study is published in the journal Nature. The study evaluated the distribution of populace outflows from Wuhan, China in January 2020, during the onset of the COVID-19 outbreak.
Massive populace motions can contribute to local outbreaks of diseases becoming widespread epidemics, according to the researchers, including Nicholas Christakis, Yale University in the United States.
The research study evaluated anonymized mobile phone data from a major nationwide service provider in China to evaluate the movements of more than 11 million individuals who spent at least 2 hrs in Wuhan between 1-24 January 2020, when the quarantine was imposed.
The scientists linked the data to the rate of COVID-19 infection from 296 prefectures in 31 provinces and regions throughout China until 19 February 2020.
Quarantine restrictions were extremely effective at significantly reducing movement of people, with 52% dropping in populace outflow from 22-23 January 2020, and on 24 January 2020, it further reduced by 94%.
The
research also revealed that the distribution of populace outflows might accurately predict the frequency as well as geographical locations of COVID-19 infections in China as much as two weeks prior.The scientists said, “The model could additionally identify potential high-transmission risk cities at an early phase of the outbreak. This could be used to assess the future COVID-19 community transmission threat in time in different areas“.
