Association between mobility, non-pharmaceutical interventions, and COVID-19 transmission in Ghana: a modelling study using mobile phone data

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Abstract Background Governments around the world have implemented non-pharmaceutical interventions to limit the transmission of COVID-19. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of how NPI measures are reflected in indicators of human mobility. Further, there is a lack of understanding about how findings from high-income settings correspond to low and middle-income contexts. Methods In this study, we assess the relationship between indicators of human mobility, NPIs, and estimates of R t , a real-time measure of the intensity of COVID-19 transmission. We construct a multilevel generalised linear mixed model, combining local disease surveillance data from subnational districts of Ghana with the timing of NPIs and indicators of human mobility from Google and Vodafone Ghana. Findings We observe a relationship between reductions in human mobility and decreases in R t during the early stages of the COVID-19 epidemic in Ghana. We find that the strength of this relationship varies through time, decreasing after the most stringent period of interventions in the early epidemic. Interpretation Our findings demonstrate how the association of NPI and mobility indicators with COVID-19 transmission may vary through time. Further, we demonstrate the utility of combining local disease surveillance data with large scale human mobility data to augment existing surveillance capacity and monitor the impact of NPI policies. Research in Context Evidence before this study We searched PubMed and preprint archives for articles published in English that contained information about the COVID-19 pandemic published up to Nov 1, 2021, using the search terms “coronavirus”, “CoV”, “COVID-19”, “mobility”, “movement”, and “flow”. The data thus far suggests that NPI measures including physical distancing, reduction of travel, and use of personal protective equipment have been demonstrated to reduce COVID-19 transmission. Much of the existing research focuses on comparisons of NPI stringency with COVID-19 transmission among different high-income countries, or on high-income countries, leaving critical questions about the applicability of these findings to low- and middle-income settings. Added value of this study We used a detailed COVID-19 surveillance dataset from Ghana, and unique high resolution spatial data on human mobility from Vodafone Ghana as well as Google smartphone GPS location data. We show how human mobility and NPI stringency were associated with changes in the effective reproduction number (R t ). We further demonstrate how this association was strongest in the early COVID-19 outbreak in Ghana, decreasing after the relaxation of national restrictions. Implications of all the available evidence The change in association between human mobility, NPI stringency, and R t may reflect a “decoupling” of NPI stringency and human mobility from disease transmission in Ghana as the COVID-19 epidemic progressed. This finding provides public health decision makers with important insights for the understanding of the utility of mobility data for predicting the spread of COVID-19.

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