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

PLoS One. 2021 Apr 15;16(4):e0249726. doi: 10.1371/journal.pone.0249726. eCollection 2021.

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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • COVID-19 / epidemiology*
  • Cell Phone*
  • Contact Tracing*
  • Humans
  • Physical Distancing
  • SARS-CoV-2 / isolation & purification

Grants and funding

Research was supported by the DOE Office of Science through the National Virtual Biotechnology Laboratory (https://science.osti.gov/nvbl), a consortium of DOE national laboratories focused on response to COVID-19, with funding provided by the Coronavirus CARES Act. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.