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On the use of human mobility proxies for modeling epidemics

Abstract : The spatial dissemination of a directly transmitted infectious disease in a population is driven by population movements from one region to another allowing mixing and importation. Public health policy and planning may thus be more accurate if reliable descriptions of population movements can be considered in the epidemic evaluations. Next to census data, generally available in developed countries, alternative solutions can be found to describe population movements where official data is missing. These include mobility models, such as the radiation model, and the analysis of mobile phone activity records providing individual geo-temporal information. Here we explore to what extent mobility proxies, such as mobile phone data or mobility models, can effectively be used in epidemic models for influenza-like-illnesses and how they compare to official census data. By focusing on three European countries, we find that phone data matches the commuting patterns reported by census well but tends to overestimate the number of commuters, leading to a faster diffusion of simulated epidemics. The order of infection of newly infected locations is however well preserved, whereas the pattern of epidemic invasion is captured with higher accuracy by the radiation model for centrally seeded epidemics and by phone proxy for peripherally seeded epidemics.
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https://hal.inrae.fr/hal-02967133
Contributor : Guillaume Kon Kam King <>
Submitted on : Wednesday, October 14, 2020 - 4:50:45 PM
Last modification on : Tuesday, February 2, 2021 - 2:26:02 PM

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Michele Tizzoni, Paolo Bajardi, Adeline Decuyper, Guillaume Kon Kam King, Christian M. Schneider, et al.. On the use of human mobility proxies for modeling epidemics. PLoS Computational Biology, Public Library of Science, 2014, 10 (7), pp.1-15. ⟨10.1371/journal.pcbi.1003716⟩. ⟨hal-02967133⟩

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