Multiscale mobility networks and the large scale spreading of infectious diseases

TL;DR

This paper investigates how multiscale human mobility, including commuting and airline traffic, influences the global spread of infectious diseases, revealing that short-range mobility enhances local synchronization but has limited impact on overall epidemic patterns.

Contribution

It introduces a multiscale modeling framework combining commuting and airline data, with a gravity model for commuting, to improve epidemic spread simulations.

Findings

Commuting flows are on average ten times larger than airline flows.

Including commuting flows slightly alters epidemic synchronization and peripheral dynamics.

A layered multi-scale modeling approach is proposed for better epidemic prediction.

Abstract

Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. In order to study the interplay between small-scale commuting flows and long-range airline traffic in shaping the spatio-temporal pattern of a global epidemic we i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms; ii) integrate in a worldwide structured metapopulation epidemic model a time-scale separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short range mobility increases however the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multi-scale framework.