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BackgroundLittle is known about the impact of changes in mobility at the sub-city level on subsequent COVID-19 incidence or the contribution of mobility to socioeconomic disparities in COVID-19 incidence. MethodsWe compiled aggregated mobile phone location data, COVID-19 confirmed cases, and features of the urban and social environments to analyze linkages between population mobility, COVID-19 incidence, and educational attainment at the sub-city level among cities with >100,000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico from March to August 2020. We used mixed effects negative binomial regression to examine longitudinal associations between changes in weekly mobility (lags 1-6 weeks) and subsequent COVID-19 incidence at the sub-city level, adjusting for urban environmental factors. FindingsAmong 1,031 sub-cities representing 314 cities in five Latin American countries, 10% higher weekly mobility was associated with 8.5% (95% CI 7.4% to 9.5%) higher weekly COVID-19 incidence the following week. This association gradually declined as the lag between mobility and COVID-19 incidence increased and was not different from the null at a six-week lag. We found evidence that suggests differences in mobility reductions are a driver of socioeconomic disparities in COVID-19 incidence. InterpretationLower population movement within a sub-city is associated with lower risk of subsequent COVID-19 incidence among residents of that sub-city. Implementing policies that reduce population mobility at the sub-city level may be an impactful COVID-19 mitigation strategy that takes equity into consideration and reduces economic and social disruption at the city or regional level. FundingWellcome Trust
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ObjectiveIndoor dining is one of the potential key drivers of COVID-19 transmission. We leverage the heterogeneity in state government preemption of city indoor dining closures, to estimate the impact of keeping indoor dining closed on COVID-19 incidence. MethodsWe obtained case rates and city/state re-opening dates from March to October 2020 in 11 U.S. cities. We categorized cities as (treatment) cities that were allowed by the state to reopen but kept indoor dining closed; and (comparison) cities that would have kept indoor dining closed but were preempted by their state and had to reopen indoor dining. ResultsKeeping indoor dining closed was associated with a 43% (IRR=0.57, 95% CI 0.46 to 0.69) decline in COVID-19 incidence over 4-weeks compared with cities that reopened indoor dining. These results were consistent after testing alternative modeling strategies. ConclusionsKeeping indoor dining closed contributes to reductions in COVID-19 spread. Policy ImplicationsEvidence of the relationship between indoor dining and COVID-19 incidence can inform state and local decisions to restrict indoor dining as a tailored strategy to reduce COVID-19 incidence.
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BackgroundPreliminary evidence has shown inequities in COVID-19 related cases and deaths in the US. ObjectiveWe explored the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York City, Philadelphia, and Chicago during the first six months of the pandemic. DesignEcological, observational study at the zip code tabulation area (ZCTA) level from March to September 2020. SettingChicago, New York City and Philadelphia. ParticipantsAll populated ZCTAs in the three cities. MeasuresOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September. Predictors were the CDC social vulnerability index and its four domains, obtained from the 2014-2018 American Community Survey. We examined the spatial autocorrelation of COVID-19 outcomes using global and local Morans I and estimated associations using spatial conditional autoregressive negative binomial models. ResultsWe found spatial clusters of high and low positivity, confirmed cases and mortality, co-located with clusters of low and high social vulnerability. We also found evidence for the existence of spatial inequities in testing, positivity, confirmed cases and mortality for the three cities. Specifically, neighborhoods with higher social vulnerability had lower testing rates, higher positivity ratios, confirmed case rates and mortality rates. LimitationsZCTAs are imperfect and heterogeneous geographical units of analysis. We rely on surveillance data, which may be incomplete. ConclusionWe found spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in three large cities of the US. RegistrationN/A Funding sourceNIH (DP5OD26429) and RWJF (77644)
