Author: Lison, A.; Persson, J.; Banholzer, N.; Feuerriegel, S.
Title: Estimating the effect of mobility on SARS-CoV-2 transmission during the first and second wave of the COVID-19 epidemic in Switzerland: a population-based study Cord-id: fkdr80c9 Document date: 2021_4_20
ID: fkdr80c9
Snippet: The effect of mobility and its value for surveillance in different waves of the COVID-19 epidemic is still unclear. In this study, we compared the role of mobility during the first and second epidemic wave in Switzerland by analysing the link between daily travel distances and the effective reproduction number Rt of SARS-CoV-2. Here we used aggregated mobile phone data from a representative panel survey of the Swiss population to measure human mobility. We estimated the effects of reductions in
Document: The effect of mobility and its value for surveillance in different waves of the COVID-19 epidemic is still unclear. In this study, we compared the role of mobility during the first and second epidemic wave in Switzerland by analysing the link between daily travel distances and the effective reproduction number Rt of SARS-CoV-2. Here we used aggregated mobile phone data from a representative panel survey of the Swiss population to measure human mobility. We estimated the effects of reductions in daily travel distance on Rt via a regression model. We compared mobility effects between the first wave (March 2-April 7, 2020) and the second wave (October 1-December 10, 2020) across mode of transport, travel purpose, sociodemographic subgroup and movement radius. We found that human mobility was associated with the effective reproduction number of SARS-CoV-2 during both the first and second epidemic wave in Switzerland. The estimated relative effects of mobility were similar in both waves for all modes of transport, travel purposes, and sociodemographic subgroups but differed by movement radius. Moreover, smaller mobility reductions in the second wave translated into smaller overall reductions of Rt. Mobility data from mobile phones have a continued potential to support real-time surveillance of COVID-19 during epidemic waves.
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