Modeling human mobility responses to the large-scale spreading of infectious diseases

By S. Meloni, Nicola Perra, Alex Arenas, Sergio Gómez, Yamir Moreno, Alessandro Vespignani. Scientific Reports, 2011

343 citations recorded by the source corpus.

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.

Subfields: Modeling and Simulation, Public Health, Environmental and Occupational Health, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/b5dc8ff2c9ea231561b0b4968d4d328196978a30

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Citations in the corpus

On the Use of Human Mobility Proxies for Modeling Epidemics (2013, result): “During this timeframe the value of the basic reproductive number is kept constant, and no change in behavior that could be self-initiated in response to the epidemic [47,48], or imposed by public health interventions is considered, for the sake of clarity in the comparison of the results.”
Predicting Personality Using Novel Mobile Phone-Based Metrics (2013, methodology): “These CDR (Call Data Record) have recently become widely use for computational social science research [2,19,20,21,22].”
Human mobility: Models and applications (2017, background): “Newer versions of such models factor in facets of human behavior, such as the tendency of people to restrict contacts and travel when made aware of the existence of a dangerous disease [374], as well as heterogeneity in the population (age, gender, socioeconomic indicators) and its effect on travel ”