Emerging dynamics from high-resolution spatial numerical epidemics
Abstract
Simulating nationwide realistic individual movements with a detailed geographical structure can help 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 computationally 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.
Data availability
The raw data associated with the 100 simulations performed and the Rscripts used to generate the figures are available from theZenodo repository at https://zenodo.org/record/5542171 ( results.zip ).
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Emerging dynamics from high-resolution spatial numerical epidemicsZenodo, doi:10.5281/zenodo.5542171.
Article and author information
Author details
Funding
Région Occitanie Pyrénées-Méditerranée
- Samuel Alizon
Agence Nationale de la Recherche (PhyEpi project)
- Samuel Alizon
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Thomine et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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