Abstract
ObjectivesRestricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different non-pharmaceutical countermeasures in the earlier stages of the pandemic is not well-understood.DesignTrends were evaluated using Citymapper’s mobility index covering 2nd to 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings.Setting41 cities worldwide.Main outcome measuresCitymapper’s mobility index.ResultsMobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r = − 0.75, p < 0.001). After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36 to 15.7%), 15.0% for workplace closures (95% CI: 10.2 to 19.8%), 7.09% for cancelling public events (95% CI: 1.98 to 12.2%), 18.0% for closing public transport (95% CI: 6.74 to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85 to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment.ConclusionsUnderstanding the effect of public policy on mobility in the early stages is crucial to slowing and reducing COVID-19 transmission. By using Citymapper’s mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful.
Highlights
Even before the advent of germ theory, authorities employed measures to restrict movement to reduce the spread of disease, exemplified by the introduction of quarantine by the Venetian Republic
After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures, 15.0% for workplace closures, 7.09% for cancelling public events, 18.0% for closing public transport, 13.3% for restricting internal movements and 5.30% for international travel controls
By using Citymapper’s mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are impactful
Summary
Even before the advent of germ theory, authorities employed measures to restrict movement to reduce the spread of disease, exemplified by the introduction of quarantine by the Venetian Republic. The spread of mobile phones, of which the world’s 7.8 billion people own an estimated 14 billion [1], has generated a wealth of information about those who are moving. The data collected from mobile phones can include whom users call and users’ location. At first, this was obtained by triangulating data from phone masts, but this has been supplemented by data from the geographical positioning system (GPS) chips included in smartphones [2]. The volunteered geographic information generated is increasingly used by transport planners to develop routes and timetables [3]
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