2007/12/10 by Aurelien Gautreau, Aurélien Gautreau, Alain Barrat +2
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #COVID-19 epidemiological studies #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #cond-mat.stat-mech #q-bio.PE
paper · pdf · doi:10.1016/j.jtbi.2007.12.001
published as Journal of Theoretical Biology 251 (2008) 509-522 · J. Theor. Biol., in press
openalex publication_date 2007/12/10 · arxiv created 2008/01/11 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study metapopulation models for the spread of epidemics in which different subpopulations (cities) are connected by fluxes of individuals (travelers). This framework allows to describe the spread of a disease on a large scale and we focus here on the computation of the arrival time of a disease as a function of the properties of the seed of the epidemics and of the characteristics of the network connecting the various subpopulations. Using analytical and numerical arguments, we introduce an easily computable quantity which approximates this average arrival time. We show on the example of a disease spread on the world-wide airport network that this quantity predicts with a good accuracy the order of arrival of the disease in the various subpopulations in each realization of epidemic scenario, and not only for an average over realizations. Finally, this quantity might be useful in the identification of the dominant paths of the disease spread.