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PeerJ . Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic

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  • PeerJ . Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic

    PeerJ


    . 2024 May 31:12:e17455.
    doi: 10.7717/peerj.17455. eCollection 2024. Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic

    Jean-Paul R Soucy 1 , Shelby L Sturrock 1 , Isha Berry 1 , Duncan J Westwood 2 , Nick Daneman 2 3 4 , David Fisman 1 , Derek R MacFadden 5 , Kevin A Brown 1 4 6



    AffiliationsAbstract

    Background: The rapid global emergence of the COVID-19 pandemic in early 2020 created urgent demand for leading indicators to track the spread of the virus and assess the consequences of public health measures designed to limit transmission. Public transit mobility, which has been shown to be responsive to previous societal disruptions such as disease outbreaks and terrorist attacks, emerged as an early candidate.
    Methods: We conducted a longitudinal ecological study of the association between public transit mobility reductions and COVID-19 transmission using publicly available data from a public transit app in 40 global cities from March 16 to April 12, 2020. Multilevel linear regression models were used to estimate the association between COVID-19 transmission and the value of the mobility index 2 weeks prior using two different outcome measures: weekly case ratio and effective reproduction number.
    Results: Over the course of March 2020, median public transit mobility, measured by the volume of trips planned in the app, dropped from 100% (first quartile (Q1)-third quartile (Q3) = 94-108%) of typical usage to 10% (Q1-Q3 = 6-15%). Mobility was strongly associated with COVID-19 transmission 2 weeks later: a 10% decline in mobility was associated with a 12.3% decrease in the weekly case ratio (exp(β) = 0.877; 95% confidence interval (CI): [0.859-0.896]) and a decrease in the effective reproduction number (β = -0.058; 95% CI: [-0.068 to -0.048]). The mobility-only models explained nearly 60% of variance in the data for both outcomes. The adjustment for epidemic timing attenuated the associations between mobility and subsequent COVID-19 transmission but only slightly increased the variance explained by the models.
    Discussion: Our analysis demonstrated the value of public transit mobility as a leading indicator of COVID-19 transmission during the first wave of the pandemic in 40 global cities, at a time when few such indicators were available. Factors such as persistently depressed demand for public transit since the onset of the pandemic limit the ongoing utility of a mobility index based on public transit usage. This study illustrates an innovative use of "big data" from industry to inform the response to a global pandemic, providing support for future collaborations aimed at important public health challenges.

    Keywords: COVID-19; Human mobility; Infectious disease surveillance; Non-pharmaceutical interventions; Physical distancing; Public transit; SARS-CoV-2; Social distancing; Urban mobility.

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