Abstract

Human mobility and social structure are at the basis of disease spreading. Disease containment strategies are usually devised from coarse-grained assumptions about human mobility. Cellular networks data, however, provides finer-grained information, not only about how people move, but also about how they communicate. In this paper we analyze the behavior of a large number of individuals in Ivory Coast using cellular network data. We model mobility and communication between individuals by means of an interconnected multiplex structure where each node represents the population in a geographic area (i.e., a sous-préfecture, a third-level administrative region). We present a model that describes how diseases circulate around the country as people move between regions. We extend the model with a concurrent process of relevant information spreading. This process corresponds to people disseminating disease prevention information, e.g., hygiene practices, vaccination campaign notices and other, within their social network. Thus, this process interferes with the epidemic. We then evaluate how restricting the mobility or using preventive information spreading process affects the epidemic. We find that restricting mobility does not delay the occurrence of an endemic state and that an information campaign might be an effective countermeasure.

Highlights

  • Human mobility and social structure are at the basis of disease spreading

  • The multiplex structure is used to model the interactions between the mobility layer, which represents movement of users between regions, and the communication layer, which captures calls between regions and, information spreading across the country

  • In this paper we have presented a model that describes the spreading of disease in a population where individuals move between geographic areas

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Summary

Introduction

Human mobility and social structure are at the basis of disease spreading. Disease containment strategies are usually devised from coarse-grained assumptions about human mobility. We extend the model with a concurrent process of relevant information spreading This process corresponds to people disseminating disease prevention information, e.g., hygiene practices, vaccination campaign notices and other, within their social network. It can provide invaluable support to decision-making, especially in critical situations For this reason, many public and private organizations are increasingly adopting a data-centric approach in their decisional process[6]. We use movement data extracted from the registration patterns in a cellular network to evaluate the influence of human mobility on the spreading of diseases in a geographic area. Information received by people who are socially close can have a higher chance of leading to an actual action

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