Dataset Information

Parameter Scaling for Epidemic Size in a Spatial Epidemic Model with Mobile Individuals.

ABSTRACT: In recent years, serious infectious diseases tend to transcend national borders and widely spread in a global scale. The incidence and prevalence of epidemics are highly influenced not only by pathogen-dependent disease characteristics such as the force of infection, the latent period, and the infectious period, but also by human mobility and contact patterns. However, the effect of heterogeneous mobility of individuals on epidemic outcomes is not fully understood. Here, we aim to elucidate how spatial mobility of individuals contributes to the final epidemic size in a spatial susceptible-exposed-infectious-recovered (SEIR) model with mobile individuals in a square lattice. After illustrating the interplay between the mobility parameters and the other parameters on the spatial epidemic spreading, we propose an index as a function of system parameters, which largely governs the final epidemic size. The main contribution of this study is to show that the proposed index is useful for estimating how parameter scaling affects the final epidemic size. To demonstrate the effectiveness of the proposed index, we show that there is a positive correlation between the proposed index computed with the real data of human airline travels and the actual number of positive incident cases of influenza B in the entire world, implying that the growing incidence of influenza B is attributed to increased human mobility.

SUBMITTER: Urabe CT

PROVIDER: S-EPMC5156435 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Parameter Scaling for Epidemic Size in a Spatial Epidemic Model with Mobile Individuals.

Urabe Chiyori T CT Tanaka Gouhei G Aihara Kazuyuki K Mimura Masayasu M

PloS one 20161214 12

In recent years, serious infectious diseases tend to transcend national borders and widely spread in a global scale. The incidence and prevalence of epidemics are highly influenced not only by pathogen-dependent disease characteristics such as the force of infection, the latent period, and the infectious period, but also by human mobility and contact patterns. However, the effect of heterogeneous mobility of individuals on epidemic outcomes is not fully understood. Here, we aim to elucidate how ...[more]

PMID: 27973605

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Dataset Information

Parameter Scaling for Epidemic Size in a Spatial Epidemic Model with Mobile Individuals.

Publications

Parameter Scaling for Epidemic Size in a Spatial Epidemic Model with Mobile Individuals.

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