Understanding components of mobility during the COVID-19 pandemic

Research output: Contribution to journalJournal articlepeer-review

6 Downloads (Pure)

Abstract

Travel restrictions have proven to be an effective strategy to control the spread of the COVID-19 epidemics, in part because they help delay disease propagation across territories. The question, however, as to how different types of travel behaviour, from commuting to holiday-related travel, contribute to the spread of infectious diseases remains open. Here, we address this issue by using factorization techniques to decompose the temporal network describing mobility flows throughout 2020 into interpretable components. Our results are based on two mobility datasets: the first is gathered from Danish mobile network operators; the second originates from the Facebook Data-For-Good project. We find that mobility patterns can be described as the aggregation of three mobility network components roughly corresponding to travel during workdays, weekends and holidays, respectively. We show that, across datasets, in periods of strict travel restrictions the component corresponding to workday travel decreases dramatically. Instead, the weekend component, increases. Finally, we study how each type of mobility (workday, weekend and holiday) contributes to epidemics spreading, by measuring how the effective distance, which quantifies how quickly a disease can travel between any two municipalities, changes across network components. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
Original languageEnglish
Article number20210118
JournalPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences
Volume380
Issue number2214
Number of pages15
ISSN1364-503X
DOIs
Publication statusPublished - 2022

Keywords

  • COVID-19
  • Human mobility
  • Non-negative matrix factorization

Fingerprint

Dive into the research topics of 'Understanding components of mobility during the COVID-19 pandemic'. Together they form a unique fingerprint.

Cite this