10.5281/zenodo.4675731
https://zenodo.org/records/4675731
oai:zenodo.org:4675731
Thomine, Olivier
Olivier
Thomine
LIS UMR 7020 CNRS, Aix Marseille University, France
Alizon, Samuel
Samuel
Alizon
MIVEGEC, CNRS, IRD, Montpellier University, France
Barthelemy, Marc
Marc
Barthelemy
Institut de Physique Théorique, CEA, CNRS-URA 2306, F-91191, Gif-sur-Yvette, France
Boenec, Corentin
Corentin
Boenec
MIVEGEC, CNRS, IRD, Montpellier University, France
Sofonea, Mircea T.
Mircea T.
Sofonea
MIVEGEC, CNRS, IRD, Montpellier University, France
Emerging dynamics from high-resolution spatial numerical epidemics
Zenodo
2021
multiagent covid-19 epidemics simulation geographic
2021-04-09
eng
10.5281/zenodo.4675730
https://zenodo.org/communities/covid-19
Creative Commons Attribution 4.0 International
Simulating nationwide realistic individual movements with a detailed geographical structure is urgently needed to optimize public health policies. However, existing tools have limited resolution or can only account for a limited number of agents. We introduce Epidemap, a new framework that can capture the daily movement of more than 60 million people in a country at a building-level resolution in a realistic and computational-efficient way. By applying it to the case of an infectious disease spreading in France, we uncover hitherto neglected effects, such as the emergence of two distinct peaks in the daily number of cases or the importance of local density in the timing of arrival of the epidemic. Finally, we show that the importance of super-spreading events strongly varies over time.