Quantifying COVID-19 importation risk in a dynamic network of domestic cities and international countries.

ABSTRACT: Since its outbreak in December 2019, the novel coronavirus 2019 (COVID-19) has spread to 191 countries and caused millions of deaths. Many countries have experienced multiple epidemic waves and faced containment pressures from both domestic and international transmission. In this study, we conduct a multiscale geographic analysis of the spread of COVID-19 in a policy-influenced dynamic network to quantify COVID-19 importation risk under different policy scenarios using evidence from China. Our spatial dynamic panel data (SDPD) model explicitly distinguishes the effects of travel flows from the effects of transmissibility within cities, across cities, and across national borders. We find that within-city transmission was the dominant transmission mechanism in China at the beginning of the o

SUBMITTER: Han X 

PROVIDER: S-EPMC8346799 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature