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Analysis of mobility data to build contact networks for COVID-19

Author

Listed:
  • Katherine Klise
  • Walt Beyeler
  • Patrick Finley
  • Monear Makvandi

Abstract

As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.

Suggested Citation

  • Katherine Klise & Walt Beyeler & Patrick Finley & Monear Makvandi, 2021. "Analysis of mobility data to build contact networks for COVID-19," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
  • Handle: RePEc:plo:pone00:0249726
    DOI: 10.1371/journal.pone.0249726
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    Cited by:

    1. Wenbin Yao & Youwei Hu & Congcong Bai & Sheng Jin & Chengcheng Yang, 2024. "Exploring Impact of COVID-19 on Travel Behavior," Networks and Spatial Economics, Springer, vol. 24(1), pages 165-197, March.
    2. Michele Bellingeri & Daniele Bevacqua & Francesco Scotognella & Davide Cassi, 2024. "The Critical Role of Networks to Describe Disease Spreading Dynamics in Social Systems: A Perspective," Mathematics, MDPI, vol. 12(6), pages 1-11, March.

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