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Estimating the effect of physical distancing on the COVID-19 pandemic using an urban mobility index

Our take —

This paper is available as a pre-print and therefore not yet peer-reviewed. Reduced movement was observed across cities in 23 countries across the world after the introduction of social distancing measures. Although authors estimated reductions in epidemic growth and transmissibility associated with reduced mobility patterns, strong assumptions were made about representativeness of the data and delays from infection to case report across 41 cities which may have biased the results.

Study design


Study population and setting

The Citymapper Mobility Index (CMI) which measures the relative frequency of planned trips (compared to an internal reference point from late 2019 or early 2020) using the Citymapper application was used as a proxy measure of adherence to social distancing measures implemented across 41 cities in 23 countries from March 2, 2020. Using reported cumulative case numbers over time, authors estimated how fast the total case numbers were growing in each of these 41 cities over 3 weeks beginning March 23 to April 6, 2020. Transmissibility as estimated by the instantaneous reproduction number was estimated for the weeks of March 23, March 30, and April 6, 2020 using the incidence of reported cases between March 8 to April 12, 2020. The authors then assumed a 14 day delay between infection and date of report to estimate the association between CMI and the mean daily growth rate and the reproduction number.

Summary of Main Findings

Authors found that declines in mobility (relative frequency of planned trips) corresponded with a decline in epidemic growth in 41 cities. The majority of cities saw a substantial reduction in mobility, as measured by the CMI, from a mean of 97.6% on March 2 to 12.7% on March 29, 2020. Similar patterns of reduced mobility were observed across cities in Europe, the Americas, and Australia corresponding to the implementation of national or subnational social distancing measures and mandatory closures e.g. of non-essential retail. A 10% reduction in mobility was associated with a decrease in the daily growth rate of 14.6% and a 0.061 reduction in the reproduction number 14 days later.

Study Strengths

Authors used automatically collected app-based data to measure changes in mobility due to social distancing measures. Such data may be more accurate than self-reported behavioural changes. Authors checked whether their findings were affected by the timing of the epidemic and their assumption about the average delay between infection and case report.


Whilst the mobility data are only available at the city-level, for some countries COVID-19 case counts were only available at national or sub-national level. Therefore the reduction in mobility in certain urban cities will not necessarily be representative of the whole country. The mobility data only applies to Citymapper app users which is not representative of the whole city, nor covers any journeys by car. The mobility metric also only captures the decline in the relative frequency of trips planned, and does not capture other indicators such as changes in the types of trips planned. Authors assumed a crude 14 day delay between infection and case report, which was the same for all countries considered. In reality this delay will differ significantly between settings due to healthcare capacity and testing policies, and may bias estimates. This bias may also apply to the reproduction number estimate which was based on cases by date of report rather than date of symptom onset. Finally, reduction in mobility does not necessarily equate to a reduction in social and physical contact that could lead to decreased transmission.

Value added

Findings are not novel, but similar to previous studies demonstrates the utility of mobility data to assess the potential impact of social distancing interventions.

This review was posted on: 14 August 2020