In the absence of effective vaccines, non-pharmaceutical interventions, such as mobility restrictions, were globally adopted as critically important strategies for curbing the spread of COVID-19. However, such interventions come with immense social and economic costs and the relative effectiveness of different mobility restrictions are not well understood. This study analyzed uniquely comprehensive datasets for the entirety of a small country, consisting of serology data, telecoms data, and COVID-19 case reports, in order to examine the relationship between mobility and transmission of COVID-19.
Andorra is a small European country where tourism is a large part of the economy. Stringent mobility restrictions were put in place in Spring 2020. Additionally, 91% of the population participated in a voluntary COVID-19 serology testing programme and those data were made available for this study. Furthermore, high resolution telecoms data for the entire population were available for analysis of mobility and proximity patterns. A set of mobility metrics were developed to indicate levels of crowding, stay-at-home rates, trip-making and contact with tourists. Mobility metrics were compared to infection rates across communities and transmission rate over time.
Several of these metrics were highly correlated with transmission rate, with a lead time of approximately 18 days, with some metrics more highly correlated than others. There was a stronger correlation for measures of crowding and inter-community trip-making, and a weaker correlation for total trips (including intra-community trips) and stay-at-homes rates.