Journal
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
Volume 23, Issue 11, Pages 710-717Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10255842.2020.1759560
Keywords
Coronavirus; COVID-19; epidemiology; SEIR model; outbreak dynamics; outbreak control
Funding
- Stanford Bio-X IIP seed grant
- DAAD Fellowship
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For the first time in history, on March 17, 2020, the European Union closed all its external borders in an attempt to contain the spreading of the coronavirus 2019, COVID-19. Throughout two past months, governments around the world have implemented massive travel restrictions and border control to mitigate the outbreak of this global pandemic. However, the precise effects of travel restrictions on the outbreak dynamics of COVID-19 remain unknown. Here we combine a global network mobility model with a local epidemiology model to simulate and predict the outbreak dynamics and outbreak control of COVID-19 across Europe. We correlate our mobility model to passenger air travel statistics and calibrate our epidemiology model using the number of reported COVID-19 cases for each country. Our simulations show that mobility networks of air travel can predict the emerging global diffusion pattern of a pandemic at the early stages of the outbreak. Our results suggest that an unconstrained mobility would have significantly accelerated the spreading of COVID-19, especially in Central Europe, Spain, and France. Ultimately, our network epidemiology model can inform political decision making and help identify exit strategies from current travel restrictions and total lockdown.
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