Multinational patterns of seasonal asymmetry in human movement influence infectious disease dynamics

Amy Wesolowski (), Elisabeth zu Erbach-Schoenberg, Andrew J. Tatem, Christopher Lourenço, Cecile Viboud, Vivek Charu, Nathan Eagle, Kenth Engø-Monsen, Taimur Qureshi, Caroline O. Buckee and C. J. E. Metcalf
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Amy Wesolowski: Johns Hopkins Bloomberg School of Public Health
Elisabeth zu Erbach-Schoenberg: University of Southampton
Andrew J. Tatem: University of Southampton
Christopher Lourenço: University of Southampton
Cecile Viboud: Fogarty International Center, National Institutes of Health
Vivek Charu: Fogarty International Center, National Institutes of Health
Nathan Eagle: Harvard T.H. Chan School of Public Health
Kenth Engø-Monsen: Telenor Research
Taimur Qureshi: Telenor Research
Caroline O. Buckee: Harvard T.H. Chan School of Public Health
C. J. E. Metcalf: Princeton University

Nature Communications, 2017, vol. 8, issue 1, 1-9

Abstract: Abstract Seasonal variation in human mobility is globally ubiquitous and affects the spatial spread of infectious diseases, but the ability to measure seasonality in human movement has been limited by data availability. Here, we use mobile phone data to quantify seasonal travel and directional asymmetries in Kenya, Namibia, and Pakistan, across a spectrum from rural nomadic populations to highly urbanized communities. We then model how the geographic spread of several acute pathogens with varying life histories could depend on country-wide connectivity fluctuations through the year. In all three countries, major national holidays are associated with shifts in the scope of travel. Within this broader pattern, the relative importance of particular routes also fluctuates over the course of the year, with increased travel from rural to urban communities after national holidays, for example. These changes in travel impact how fast communities are likely to be reached by an introduced pathogen.

Date: 2017
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DOI: 10.1038/s41467-017-02064-4

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