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# BackgroundThe rising COVID-19 crisis threatens to disproportionately hit African countries. As a result, most African governments have temporarily closed schools and non-essential businesses or banned social gatherings to contain the disease. It is therefore important to estimate the level of transmission reduction as a result of these measures. This study aimed at predicting COVID-19 cases in Africa based on COVID-19 community mobility report.# MethodsOur study focused on 26 African countries whose community mobility data were available online. The number of daily confirmed cases for the period of February 15th, 2020 to May 29th, 2020 for each country was obtained from European Center for Disease Prevention and Control (ECDC) COVID-19 cases geographic distribution data. Multiple linear regression was performed to investigate the relationship between COVID-19 community mobility and confirmed cases.# ResultsThe maximum public place mobility change was -38.15% with an average of -18.85% (±3.47); residential mobility was at 23.17% with an average of 11. 268% (±1.448). The number of confirmed cases had a significant negative correlation with residential mobility change (r = -0.878, _P_<0.01) and positive correlation with public place mobility change (r = 0.881, _P_<0.05). Both mobility changes in public spaces and residential are significant predictors of COVID-19 cases. More specifically, about 1% change in a public place and residential mobility would result in 167 less COVID-19 daily cases, while total lockdown would result in 581 fewer daily cases.# ConclusionsOur analysis shows that a COVID-19 containment strategy that focuses on increasing residential mobility and reducing public spaces mobility is effective. Therefore, the finding supports containment measures that aim to limit the movement of people.

Effects of increased residential mobility and reduced public spaces mobility in containing COVID-19 in Africa