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Mobile device data reveal the dynamics in a positive relationship between human mobility and COVID-19 infections
Author(s) -
Chenfeng Xiong,
Songhua Hu,
Mofeng Yang,
Weiyu Luo,
Lei Zhang
Publication year - 2020
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2010836117
Subject(s) - inflow , covid-19 , pandemic , transmission (telecommunications) , location data , aggregate data , geography , econometrics , computer science , business , environmental science , statistics , medicine , mathematics , meteorology , telecommunications , computer security , infectious disease (medical specialty) , disease , pathology
Accurately estimating human mobility and gauging its relationship with virus transmission is critical for the control of COVID-19 spreading. Using mobile device location data of over 100 million monthly active samples, we compute origin–destination travel demand and aggregate mobility inflow at each US county from March 1 to June 9, 2020. Then, we quantify the change of mobility inflow across the nation and statistically model the time-varying relationship between inflow and the infections. We find that external travel to other counties decreased by 35% soon after the nation entered the emergency situation, but recovered rapidly during the partial reopening phase. Moreover, our simultaneous equations analysis highlights the dynamics in a positive relationship between mobility inflow and the number of infections during the COVID-19 onset. This relationship is found to be increasingly stronger in partially reopened regions. Our study provides a quick reference and timely data availability for researchers and decision makers to understand the national mobility trends before and during the pandemic. The modeling results can be used to predict mobility and transmissions risks and integrated with epidemics models to further assess the public health outcomes.

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