Daniel O Erim1, Gbemisola A Oke2, Akinyele O Adisa3, Oluwakemi Odukoya4, Olalekan A Ayo-Yusuf5, Theodora Nawa Erim6, Tina N Tsafa7, Martin M Meremikwu8, Israel T Agaku9. 1. Parexel International, Durham, North Carolina. 2. Department of Periodontology and Community Dentistry, University of Ibadan, Nigeria. 3. Department of Oral Pathology, University of Ibadan, Nigeria. 4. Department of Community Health and Primary Care, University of Lagos, Nigeria. 5. Sefako Makgatho Health Sciences University, Ga-Rankuwa, South Africa. 6. Holly Hill Hospital, Raleigh, North Carolina. 7. Benue State University, Makurdi, Nigeria. 8. Department of Paediatrics, University of Calabar Teaching Hospital, Calabar, Nigeria. 9. Department of Oral Epidemiology, Harvard Dental School, Boston, Massachusetts.
Abstract
Importance: To prepare for future coronavirus disease 2019 (COVID-19) waves, Nigerian policy makers need insights into community spread of COVID-19 and changes in rates of infection associated with government-mandated closures and restrictions. Objectives: To measure the association of closures and restrictions with aggregate mobility and the association of mobility with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and to characterize community spread of COVID-19. Design, Setting, and Participants: This cross-sectional study used aggregated anonymized mobility data from smartphone users in Nigeria who opted to provide location history (from a pool of up to 40 million individuals) collected between February 27 and July 21, 2020. The analyzed data included daily counts of confirmed SARS-CoV-2 infections and daily changes in aggregate mobility across 6 categories: retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential. Closures and restrictions were initiated on March 30, 2020, and partially eased on May 4, 2020. Main Outcomes and Measures: Interrupted time series were used to measure associations of closures and restrictions with aggregate mobility. Negative binomial regression was used to evaluate associations between confirmed SARS-CoV-2 infections and mobility categories. Averted infections were estimated by subtracting cumulative confirmed infections from estimated infections assuming no closures and restrictions. Results: Closures and restrictions had negative associations with mean change in daily aggregate mobility in retail and recreation (-46.87 [95% CI, -55.98 to -37.76] percentage points; P < .001), grocery and pharmacy (-28.95 [95% CI, -40.12 to -17.77] percentage points; P < .001), parks (-43.59 [95% CI, -49.89 to -37.30] percentage points; P < .001), transit stations (-47.44 [95% CI, -56.70 to -38.19] percentage points; P < .001), and workplaces (-53.07 [95% CI, -67.75 to -38.39] percentage points; P < .001) and a positive association with mobility in residential areas (24.10 [95% CI, 19.14 to 29.05] percentage points; P < .001). Most of these changes reversed after closures and restrictions were partially eased (retail and recreation: 14.63 [95% CI, 10.95 to 18.30] percentage points; P < .001; grocery and pharmacy: 15.29 [95% CI, 10.90 to 19.67] percentage points; P < .001; parks: 6.48 [95% CI, 3.98 to 8.99] percentage points; P < .001; transit stations: 17.93 [95% CI, 14.03 to 21.83] percentage points; P < .001; residential: -5.59 [95% CI, -9.08 to -2.09] percentage points; P = .002). Additionally, every percentage point increase in aggregate mobility was associated with higher incidences of SARS-CoV-2 infection in residential areas (incidence rate ratio [IRR], 1.03 [95% CI, 1.00 to 1.07]; P = .04), transit stations (IRR, 1.02 [95% CI, 1.00 to 1.03]; P = .008), and workplaces (IRR, 1.01 [95% CI, 1.00 to 1.02]; P = .04). Lastly, closures and restrictions may have been associated with averting up to 5.8 million SARS-CoV-2 infections over the study period. Conclusions and Relevance: In this cross-sectional study, closures and restrictions had significant associations with aggregate mobility and were associated with decreased SARS-CoV-2 infections. These findings suggest that future anticontagion measures need better infection control and contact tracing in residential areas, transit stations, and workplaces.
Importance: To prepare for future coronavirus disease 2019 (COVID-19) waves, Nigerian policy makers need insights into community spread of COVID-19 and changes in rates of infection associated with government-mandated closures and restrictions. Objectives: To measure the association of closures and restrictions with aggregate mobility and the association of mobility with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and to characterize community spread of COVID-19. Design, Setting, and Participants: This cross-sectional study used aggregated anonymized mobility data from smartphone users in Nigeria who opted to provide location history (from a pool of up to 40 million individuals) collected between February 27 and July 21, 2020. The analyzed data included daily counts of confirmed SARS-CoV-2 infections and daily changes in aggregate mobility across 6 categories: retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential. Closures and restrictions were initiated on March 30, 2020, and partially eased on May 4, 2020. Main Outcomes and Measures: Interrupted time series were used to measure associations of closures and restrictions with aggregate mobility. Negative binomial regression was used to evaluate associations between confirmed SARS-CoV-2 infections and mobility categories. Averted infections were estimated by subtracting cumulative confirmed infections from estimated infections assuming no closures and restrictions. Results: Closures and restrictions had negative associations with mean change in daily aggregate mobility in retail and recreation (-46.87 [95% CI, -55.98 to -37.76] percentage points; P < .001), grocery and pharmacy (-28.95 [95% CI, -40.12 to -17.77] percentage points; P < .001), parks (-43.59 [95% CI, -49.89 to -37.30] percentage points; P < .001), transit stations (-47.44 [95% CI, -56.70 to -38.19] percentage points; P < .001), and workplaces (-53.07 [95% CI, -67.75 to -38.39] percentage points; P < .001) and a positive association with mobility in residential areas (24.10 [95% CI, 19.14 to 29.05] percentage points; P < .001). Most of these changes reversed after closures and restrictions were partially eased (retail and recreation: 14.63 [95% CI, 10.95 to 18.30] percentage points; P < .001; grocery and pharmacy: 15.29 [95% CI, 10.90 to 19.67] percentage points; P < .001; parks: 6.48 [95% CI, 3.98 to 8.99] percentage points; P < .001; transit stations: 17.93 [95% CI, 14.03 to 21.83] percentage points; P < .001; residential: -5.59 [95% CI, -9.08 to -2.09] percentage points; P = .002). Additionally, every percentage point increase in aggregate mobility was associated with higher incidences of SARS-CoV-2 infection in residential areas (incidence rate ratio [IRR], 1.03 [95% CI, 1.00 to 1.07]; P = .04), transit stations (IRR, 1.02 [95% CI, 1.00 to 1.03]; P = .008), and workplaces (IRR, 1.01 [95% CI, 1.00 to 1.02]; P = .04). Lastly, closures and restrictions may have been associated with averting up to 5.8 million SARS-CoV-2 infections over the study period. Conclusions and Relevance: In this cross-sectional study, closures and restrictions had significant associations with aggregate mobility and were associated with decreased SARS-CoV-2 infections. These findings suggest that future anticontagion measures need better infection control and contact tracing in residential areas, transit stations, and workplaces.
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