Evaluating the impact of keeping indoor dining closed on COVID-19 rates among large US cities: a quasi-experimental design (preprint)

Objective: Indoor 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. Methods: We 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. Results: Keeping 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. Conclusions: Keeping indoor dining closed contributes to reductions in COVID-19 spread. Policy Implications: Evidence 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.

Early Evidence of Disparities in COVID-19 Testing in US Cities (preprint)

Background: Preliminary evidence has shown wide inequities in COVID-19 related deaths in the US. We explored the emergence of spatial inequities in COVID-19 testing, positivity, and incidence in New York City, Philadelphia, and Chicago. Methods: We used zip code-level data on cumulative tests and confirmed cases by date for each city and computed testing, positivity, and incidence indicators. We linked these to 2014-2018 American Community Survey data on income, education, race/ethnicity, occupation, health insurance, and overcrowding, and computed a summary index. We computed associations between using Poisson models. We also examined clusters of high and low incidence using the G* statistic. Results: Through May 18th, there were wide inequities in positivity and incidence, with less advantaged neighborhoods having a higher incidence (RR=1.36 [95% CrI 1.18;1.57], 1.17 [1.11;1.23], and 1.10 [0.98;1.23], per 1 SD increase in the summary index in Chicago, NYC and Philadelphia, respectively). In all three cities inequities in incidence increased as the pandemic advanced, while inequities in positivity remained stable. In contrast the social patterning of testing changed over time: testing was inversely associated with disadvantage early in the pandemic but was either not associated or positively associated with disadvantage later in the pandemic. We also found clusters of high and low incidence, co-located with areas of high and low disadvantage. Conclusions: We found wide spatial inequities in COVID-19 positivity and incidence in three large metropolitan areas of the US. In health crises health inequities become magnified and reflect a longstanding history of racial and economic injustice.