Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan.

ABSTRACT: Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas

SUBMITTER: Chang MC 

PROVIDER: S-EPMC7430617 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature