We explored the viability of using air quality as an alternative to aggregated location data from mobile phones in the two most populated cities in Uganda. We accessed air quality and Google mobility data collected from 15th February 2020 to 10th June 2021 and augmented them with mobility restrictions implemented during the COVID-19 lockdown. We determined whether air quality data depicted similar patterns to mobility data before, during, and after the lockdown and determined associations between air quality and mobility by computing Pearson correlation coefficients ([Formula: see text]), conducting multivariable regression with associated confidence intervals (CIs), and visualized the relationships using scatter plots. Residential mobility increased with the stringency of restrictions while both non-residential mobility and air pollution decreased with the stringency of restrictions. In Kampala, PM2.5 was positively correlated with non-residential mobility and negatively correlated with residential mobility. Only correlations between PM2.5 and movement in work and residential places were statistically significant in Wakiso. After controlling for stringency in restrictions, air quality in Kampala was independently correlated with movement in retail and recreation (- 0.55; 95% CI = - 1.01- - 0.10), parks (0.29; 95% CI = 0.03-0.54), transit stations (0.29; 95% CI = 0.16-0.42), work (- 0.25; 95% CI = - 0.43- - 0.08), and residential places (- 1.02; 95% CI = - 1.4- - 0.64). For Wakiso, only the correlation between air quality and residential mobility was statistically significant (- 0.99; 95% CI = - 1.34- - 0.65). These findings suggest that air quality is linked to mobility and thus could be used by public health programs in monitoring movement patterns and the spread of infectious diseases without compromising on individuals' privacy.
Keywords: Air quality; COVID-19; Human mobility; Infectious diseases; Particulate matter; Transmission.
© 2022. The Author(s).