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

Author

Listed:
  • Amy Wesolowski

    (Johns Hopkins Bloomberg School of Public Health)

  • Elisabeth zu Erbach-Schoenberg

    (University of Southampton
    Flowminder Foundation)

  • Andrew J. Tatem

    (University of Southampton
    Flowminder Foundation)

  • Christopher Lourenço

    (University of Southampton
    Clinton Health Access Initiative)

  • 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
    Harvard T.H. Chan School of Public Health)

  • C. J. E. Metcalf

    (Princeton University
    Princeton University)

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.

Suggested Citation

  • 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 & C. J. , 2017. "Multinational patterns of seasonal asymmetry in human movement influence infectious disease dynamics," Nature Communications, Nature, vol. 8(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-02064-4
    DOI: 10.1038/s41467-017-02064-4
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    Cited by:

    1. Constanze Ciavarella & Neil M Ferguson, 2021. "Deriving fine-scale models of human mobility from aggregated origin-destination flow data," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-18, February.
    2. Seungwon Jung & Jaeuk Moon & Eenjun Hwang, 2020. "Cluster-Based Analysis of Infectious Disease Occurrences Using Tensor Decomposition: A Case Study of South Korea," IJERPH, MDPI, vol. 17(13), pages 1-19, July.
    3. Nathan H. Schumaker & Sydney M. Watkins, 2021. "Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA," Land, MDPI, vol. 10(4), pages 1-13, April.
    4. Richard Bluhm & Maxim Pinkovskiy, 2021. "The spread of COVID-19 and the BCG vaccine: A natural experiment in reunified Germany," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 353-376.
    5. Jessica E. Steele & Carla Pezzulo & Maximilian Albert & Christopher J. Brooks & Elisabeth zu Erbach-Schoenberg & Siobhán B. O’Connor & Pål R. Sundsøy & Kenth Engø-Monsen & Kristine Nilsen & Bonita Gra, 2021. "Mobility and phone call behavior explain patterns in poverty at high-resolution across multiple settings," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    6. Xia, Nan & Cheng, Liang & Chen, Song & Wei, XiaoYan & Zong, WenWen & Li, ManChun, 2018. "Accessibility based on Gravity-Radiation model and Google Maps API: A case study in Australia," Journal of Transport Geography, Elsevier, vol. 72(C), pages 178-190.
    7. Yanxin Wang & Jian Li & Xi Zhao & Gengzhong Feng & Xin (Robert) Luo, 2020. "Using Mobile Phone Data for Emergency Management: a Systematic Literature Review," Information Systems Frontiers, Springer, vol. 22(6), pages 1539-1559, December.
    8. Shengjie Lai & Elisabeth zu Erbach-Schoenberg & Carla Pezzulo & Nick W. Ruktanonchai & Alessandro Sorichetta & Jessica Steele & Tracey Li & Claire A. Dooley & Andrew J. Tatem, 2019. "Exploring the use of mobile phone data for national migration statistics," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-10, December.

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