title: Modeling human mobility responses to the large-scale spreading of infectious diseases.
abstract: Current modeling of infectious diseases allows for the study of realistic scenarios that include population heterogeneity, social structures, and mobility processes down to the individual level. The advances in the realism of epidemic description call for the explicit modeling of individual behavioral responses to the presence of disease within modeling frameworks. Here we formulate and analyze a metapopulation model that incorporates several scenarios of self-initiated behavioral changes into the mobility patterns of individuals. We find that prevalence-based travel limitations do not alter the epidemic invasion threshold. Strikingly, we observe in both synthetic and data-driven numerical simulations that when travelers decide to avoid locations with high levels of prevalence, this self-initiated behavioral change may enhance disease spreading. Our results point out that the real-time availability of information on the disease and the ensuing behavioral changes in the population may produce a negative impact on disease containment and mitigation.
authors.affiliation: Department of Informatics and Automation, University of Rome ”Roma Tre”, Via della Vasca Navale, 79 Rome 00146, Italy.
authors.forename: Sandro
authors.initials: S
authors.lastname: Meloni
authors.forename: Nicola
authors.initials: N
authors.lastname: Perra
authors.forename: Alex
authors.initials: A
authors.lastname: Arenas
authors.forename: Sergio
authors.initials: S
authors.lastname: Gómez
authors.forename: Yamir
authors.initials: Y
authors.lastname: Moreno
authors.forename: Alessandro
authors.initials: A
authors.lastname: Vespignani
mesh_terms: D001519:Behavior; D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission*; D004196:Disease Outbreaks; D063426:Human Migration; D006801:Humans; D008962:Models, Theoretical; D014481:United States / Q000453:epidemiology