On the use of aggregated human mobility data to estimate the reproduction number

Sci Rep. 2021 Dec 2;11(1):23286. doi: 10.1038/s41598-021-02760-8.

Abstract

The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. We introduce a theoretical framework to explain and predict changes in the reproduction number of SARS-CoV-2 in terms of aggregated individual mobility and interpersonal proximity (alongside other epidemiological and environmental variables) during and after the lockdown period. We use an infection-age structured model described by a renewal equation. The model predicts the evolution of the reproduction number up to a week ahead of well-established estimates used in the literature. We show how lockdown policies, via reduction of proximity and mobility, reduce the impact of CoViD-19 and mitigate the risk of disease resurgence. We validate our theoretical framework using data from Google, Voxel51, Unacast, The CoViD-19 Mobility Data Network, and Analisi Distribuzione Aiuti.

Publication types

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

MeSH terms

  • Basic Reproduction Number / statistics & numerical data*
  • COVID-19 / epidemiology*
  • COVID-19 / transmission*
  • Contact Tracing
  • Humans
  • Italy / epidemiology
  • Models, Theoretical
  • Movement*
  • Physical Distancing
  • Quarantine
  • SARS-CoV-2
  • United States / epidemiology