Validity of air quality as a measure of human mobility. The COVID-19 context.

Abstract

BackgroundMobility patterns are valuable in identifying transmission patterns for infectious diseases and in parametrizing mathematical models. Aggregated location data from mobile phones which have been the main means of measuring human mobility on a population level come with several limitations. MethodsWe explored the viability of using ground monitored air quality data as an alternative to aggregated location data from mobile phones in two cities in Uganda. We determined associations between air quality and human mobility and the effect of mobility restrictions on mobility and air quality using Pearson correlation (R), multivariable regression and visualized relationships using scatter plots. ResultsFine particulate matter (PM2.5) was negatively correlated with the government response stringency index for Kampala (R = -0.31, p<0.001) and Wakiso (R = -0.21, p<0.001). In Kampala, PM2.5 was positively associated with movement in grocery and pharmacy (R = 0.24, p<0.001), parks (R = 0.25, p<0.001), retail and recreation (R = 0.24, p<0.001), transit stations (R = 0.3, p<0.001) and work places (R = 0.2, p<0.001); and negatively correlated with movement in residential places (R = -0.3, p<0.001). Only associations between PM2.5 and movement in workplaces and residential places were statistically significant in Wakiso (R = 0.14, p<0.001 and R = -0.19, p = 0.003 respectively).ConclusionsThese findings suggest that air quality data are linked to human mobility data and could thus be used to monitor human movement patterns. This is a pioneer study to assess the value of air quality as a surrogate for human mobility.