Leveraging cellphone-derived mobility networks to assess Covid-19 travel risk
Justin J. Slater, Patrick E. Brown, Jeffrey S. Rosenthal, Jorge Mateu
The Annals of Applied Statistics · 2025 · Volume 19 · Issue 1
Abstract
Since the beginning of the Covid-19 pandemic, public health authorities across the globe have implemented policies, such as lockdowns, in an attempt to reduce population mobility and, consequently, person-to-person contacts. It is well known that lockdowns reduce mobility, but to what extent does this reduction in mobility lead to lower infection rates? In this paper we extend the endemic-epidemic modeling framework in a principled manner, incorporating temporally changing mobility network data and quantifying the risk associated with travelling throughout the first year of the pandemic in two Spanish communities.
Keywords
Cellphone mobility data, Covid-19, endemic-epidemic models, infectious diseases, Poisson network autoregressions, spatiotemporal statistics
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