Health disparities in past influenza pandemics: A scoping review of the literature.

Objective: The COVID-19 pandemic has exacerbated existing health disparities. To provide a historical perspective on health disparities for pandemic acute respiratory viruses, we conducted a scoping review of the public health literature of health disparities in influenza outcomes during the 1918, 1957, 1968, and 2009 influenza pandemics. Methods: We searched for articles examining socioeconomic or racial/ethnic disparities in any population, examining any influenza-related outcome (e.g., incidence, hospitalizations, mortality), during the 1918, 1957, 1968, and 2009 influenza pandemics. We conducted a structured search of English-written articles in PubMed supplemented by a snowball of articles meeting inclusion criteria. Results: A total of 29 articles met inclusion criteria, all but one focusing exclusively on the 1918 or 2009 pandemics. Individuals of low socioeconomic status, or living in low socioeconomic status areas, experienced higher incidence, hospitalizations, and mortality in the 1918 and 2009 pandemics. There were conflicting results regarding racial/ethnic disparities during the 1918 pandemic, with differences in magnitude and direction by outcome, potentially due to issues in data quality by race/ethnicity. Racial/ethnic minorities had generally higher incidence, mortality, and hospitalization rates in the 1957 and 2009 pandemics. Conclusion: Individuals of low socioeconomic status and racial/ethnic minorities have historically experienced worse influenza outcomes during pandemics. These historical patterns can inform current research to understand disparities in the ongoing COVID-19 pandemic and future pandemics.

Higher COVID-19 Vaccination And Narrower Disparities In US Cities With Paid Sick Leave Compared To Those Without.

Paid sick leave provides workers with paid time off to receive COVID-19 vaccines and to recover from potential vaccine adverse effects. We hypothesized that US cities with paid sick leave would have higher COVID-19 vaccination coverage and narrower coverage disparities than those without such policies. Using county-level vaccination data and paid sick leave data from thirty-seven large US cities in 2021, we estimated the association between city-level paid sick leave policies and vaccination coverage in the working-age population and repeated the analysis using coverage in the population ages sixty-five and older as a negative control. We also examined associations by neighborhood social vulnerability. Cities with a paid sick leave policy had 17 percent higher vaccination coverage than cities without such a policy. We found stronger associations between paid sick leave and vaccination in the most socially vulnerable neighborhoods compared with the least socially vulnerable ones, and no association in the population ages sixty-five and older. Paid sick leave policies are associated with higher COVID-19 vaccination coverage and narrower coverage disparities. Increasing access to these policies may help increase vaccination and reduce inequities in coverage.

Inequities in spatial accessibility to COVID-19 testing in 30 large US cities.

Testing for SARS-CoV-2 infection has been a key strategy to mitigate and control the COVID-19 pandemic. Wide spatial and racial/ethnic disparities in COVID-19 outcomes have emerged in US cities. Previous research has highlighted the role of unequal access to testing as a potential driver of these disparities. We described inequities in spatial accessibility to COVID-19 testing locations in 30 large US cities. We used location data from Castlight Health Inc corresponding to October 2021. We created an accessibility metric at the level of the census block group (CBG) based on the number of sites per population in a 15-minute walkshed around the centroid of each CBG. We also calculated spatial accessibility using only testing sites without restrictions, i.e., no requirement for an appointment or a physician order prior to testing. We measured the association between the social vulnerability index (SVI) and spatial accessibility using a multilevel negative binomial model with random city intercepts and random SVI slopes. Among the 27,195 CBG analyzed, 53% had at least one testing site within a 15-minute walkshed, and 36% had at least one site without restrictions. On average, a 1-decile increase in the SVI was associated with a 3% (95% Confidence Interval: 2% - 4%) lower accessibility. Spatial inequities were similar across various components of the SVI and for sites with no restrictions. Despite this general pattern, several cities had inverted inequity, i.e., better accessibility in more vulnerable areas, which indicates that some cities may be on the right track when it comes to promoting equity in COVID-19 testing. Testing is a key component of the strategy to mitigate transmission of SARS-CoV-2 and efforts should be made to improve accessibility to testing, particularly as new and more contagious variants become dominant.

Urban Scaling of Health Outcomes: a Scoping Review.

Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. We found several historical studies that examined the dynamic relationships between city size and mortality occurring during the nineteenth and early twentieth centuries. In more recent years, we documented heterogeneity in the relation between city size and health. Measles and influenza are influenced by city size in conjunction with other factors like geographic proximity, while STIs, HIV, and dengue tend to occur more frequently in larger cities. NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.

Heterogeneity in Spatial Inequities in COVID-19 Vaccination Across 16 Large US Cities.

Differences in vaccination coverage can perpetuate coronavirus disease 2019 (COVID-19) disparities. We explored the association between neighborhood-level social vulnerability and COVID-19 vaccination coverage in 16 large US cities from the beginning of the vaccination campaign in December 2020 through September 2021. We calculated the proportion of fully vaccinated adults in 866 zip code tabulation areas (ZCTAs) of 16 large US cities: Long Beach, Los Angeles, Oakland, San Diego, San Francisco, and San Jose, all in California; Chicago, Illinois; Indianapolis, Indiana; Minneapolis, Minnesota; New York, New York; Philadelphia, Pennsylvania; and Austin, Dallas, Fort Worth, Houston, and San Antonio, all in Texas. We computed absolute and relative total and Social Vulnerability Index-related inequities by city. COVID-19 vaccination coverage was 0.75 times (95% confidence interval: 0.69, 0.81) or 16 percentage points (95% confidence interval: 12.1, 20.3) lower in neighborhoods with the highest social vulnerability as compared with those with the lowest. These inequities were heterogeneous, with cities in the West generally displaying narrower inequities in both the absolute and relative scales. The Social Vulnerability Index domains of socioeconomic status and of household composition and disability showed the strongest associations with vaccination coverage. Inequities in COVID-19 vaccinations hamper efforts to achieve health equity, as they mirror and could lead to even wider inequities in other COVID-19 outcomes.

Tracking COVID-19 Inequities Across Jurisdictions Represented in the Big Cities Health Coalition (BCHC): The COVID-19 Health Inequities in BCHC Cities Dashboard.

Objectives. To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of the Big Cities Health Coalition (BCHC). Methods. We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities. Results. We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities. Conclusions. This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. (Am J Public Health. 2022;112(6):904-912. https://doi.org/10.2105/AJPH.2021.306708).

The Impact of Keeping Indoor Dining Closed on COVID-19 Rates Among Large US Cities: A Quasi-Experimental Design.

BACKGROUND: Indoor dining is one of the potential drivers of COVID-19 transmission. We used the heterogeneity among 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 or state reopening dates from March to October 2020 in 11 US cities. We categorized cities as treatment cities that were allowed by the state to reopen but kept indoor dining closed or comparison cities that would have kept indoor dining closed but that were preempted by their state and had to reopen indoor dining. We modeled associations using a difference-in-difference approach and an event study specification. We ran negative binomial regression models, with city-day as the unit of analysis, city population as an offset, and controlling for time-varying nonpharmaceutical interventions, as well as city and time fixed effects in sensitivity analysis and the event study specification. RESULTS: Keeping indoor dining closed was associated with a 55% (IRR = 0.45; 95% confidence intervals = 0.21, 0.99) decline in the new COVID-19 case rate over 6 weeks compared with cities that reopened indoor dining, and these results were consistent after testing alternative modeling strategies. CONCLUSIONS: Keeping indoor dining closed may be directly or indirectly associated with reductions in COVID-19 spread. Evidence of the relationship between indoor dining and COVID-19 case rates can inform policies to restrict indoor dining as a tailored strategy to reduce COVID-19 incidence. See video abstract at, http://links.lww.com/EDE/B902.

Scaling of mortality in 742 metropolitan areas of the Americas.

We explored how mortality scales with city population size using vital registration and population data from 742 cities in 10 Latin American countries and the United States. We found that more populated cities had lower mortality (sublinear scaling), driven by a sublinear pattern in U.S. cities, while Latin American cities had similar mortality across city sizes. Sexually transmitted infections and homicides showed higher rates in larger cities (superlinear scaling). Tuberculosis mortality behaved sublinearly in U.S. and Mexican cities and superlinearly in other Latin American cities. Other communicable, maternal, neonatal, and nutritional deaths, and deaths due to noncommunicable diseases were generally sublinear in the United States and linear or superlinear in Latin America. Our findings reveal distinct patterns across the Americas, suggesting no universal relation between city size and mortality, pointing to the importance of understanding the processes that explain heterogeneity in scaling behavior or mortality to further advance urban health policies.

The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data.

BACKGROUND: Little is known about the effect of changes in mobility at the subcity level on subsequent COVID-19 incidence, which is particularly relevant in Latin America, where substantial barriers prevent COVID-19 vaccine access and non-pharmaceutical interventions are essential to mitigation efforts. We aimed to examine the longitudinal associations between population mobility and COVID-19 incidence at the subcity level across a large number of Latin American cities. METHODS: In this longitudinal ecological study, we compiled aggregated mobile phone location data, daily confirmed COVID-19 cases, and features of urban and social environments to analyse population mobility and COVID-19 incidence at the subcity level among cities with more than 100 000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico, from March 2 to Aug 29, 2020. Spatially aggregated mobile phone data were provided by the UN Development Programme in Latin America and the Caribbean and Grandata; confirmed COVID-19 cases were from national government reports and population and socioeconomic factors were from the latest national census in each country. We used mixed-effects negative binomial regression for a time-series analysis, to examine longitudinal associations between weekly mobility changes from baseline (prepandemic week of March 2-9, 2020) and subsequent COVID-19 incidence (lagged by 1-6 weeks) at the subcity level, adjusting for urban environmental and socioeconomic factors (time-invariant educational attainment, residential overcrowding, population density [all at the subcity level], and country). FINDINGS: We included 1031 subcity areas, representing 314 Latin American cities, in Argentina (107 subcity areas), Brazil (416), Colombia (82), Guatemala (20), and Mexico (406). In the main adjusted model, we observed an incidence rate ratio (IRR) of 2·35 (95% CI 2·12-2·60) for COVID-19 incidence per log unit increase in the mobility ratio (vs baseline) during the previous week. Thus, 10% lower weekly mobility was associated with 8·6% (95% CI 7·6-9·6) lower incidence of COVID-19 in the following week. This association gradually weakened as the lag between mobility and COVID-19 incidence increased and was not different from null at a 6-week lag. INTERPRETATION: Reduced population movement within a subcity area is associated with a subsequent decrease in COVID-19 incidence among residents of that subcity area. Policies that reduce population mobility at the subcity level might be an effective COVID-19 mitigation strategy, although they should be combined with strategies that mitigate any adverse social and economic consequences of reduced mobility for the most vulnerable groups. FUNDING: Wellcome Trust. TRANSLATION: For the Spanish translation of the abstract see Supplementary Materials section.

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study.

BACKGROUND: Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States. OBJECTIVE: To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic. DESIGN: Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020. SETTING: Chicago, New York, and Philadelphia. PARTICIPANTS: All populated ZCTAs in the 3 cities. MEASUREMENTS: Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models. RESULTS: Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates. LIMITATIONS: The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete. CONCLUSION: Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities. PRIMARY FUNDING SOURCE: National Institutes of Health.

The Regeneración Urbana, Calidad de Vida y Salud - RUCAS project: a Chilean multi-methods study to evaluate the impact of urban regeneration on resident health and wellbeing.

BACKGROUND: The available evidence of the health effects of urban regeneration is scarce In Latin America, and there are no studies focused on formal housing that longitudinally evaluate the impact of housing and neighborhood interventions on health. The "Regeneración Urbana, Calidad de Vida y Salud" (Urban Regeneration, Quality of Life, and Health) or RUCAS project is a longitudinal, multi-method study that will evaluate the impact of an intervention focused on dwellings, built environment and community on the health and wellbeing of the population in two social housing neighborhoods in Chile. METHODS: RUCAS consists of a longitudinal study where inhabitants exposed and unexposed to the intervention will be compared over time within the study neighborhoods (cohorts), capitalizing on interventions as a natural experiment. Researchers have developed a specific conceptual framework and identified potential causal mechanisms. Proximal and more distal intervention effects will be measured with five instruments, implemented pre- and post-interventions between 2018 and 2021: a household survey, an observation tool to evaluate dwelling conditions, hygrochrons for measuring temperature and humidity inside dwellings, systematic observation of recreational areas, and qualitative interviews. Survey baseline data (956 households, 3130 individuals) is presented to describe sociodemographics, housing and health characteristics of both cohorts, noting that neighborhoods studied show worse conditions than the Chilean population. DISCUSSION: RUCAS' design allows for a comprehensive evaluation of the effects that the intervention could have on various dimensions of health and health determinants. RUCAS will face some challenges, like changes in the intervention process due to adjustments of the master plan, exogenous factors -including COVID-19 pandemic and associated lockdowns- and lost to follow-up. Given the stepped wedge design, that the study capitalizes on within household changes over time, the possibility of adjusting data collection process and complementarity of methods, RUCAS has the flexibility to adapt to these circumstances. Also, RUCAS' outreach and retention strategy has led to high retention rates. RUCAS will provide evidence to inform regeneration processes, highlighting the need to consider potential health effects of regeneration in designing such interventions and, more broadly, health as a key priority in urban and housing policies.

Linking Data on Constituent Health with Elected Officials' Opinions: Associations Between Urban Health Disparities and Mayoral Officials' Beliefs About Health Disparities in Their Cities.

Policy Points Mayoral officials' opinions about the existence and fairness of health disparities in their city are positively associated with the magnitude of income-based life expectancy disparity in their city. Associations between mayoral officials' opinions about health disparities in their city and the magnitude of life expectancy disparity in their city are not moderated by the social or fiscal ideology of mayoral officials or the ideology of their constituents. Highly visible and publicized information about mortality disparities, such as that related to COVID-19 disparities, has potential to elevate elected officials' perceptions of the severity of health disparities and influence their opinions about the issue. CONTEXT: A substantive body of research has explored what factors influence elected officials' opinions about health issues. However, no studies have assessed the potential influence of the health of an elected official's constituents. We assessed whether the magnitude of income-based life expectancy disparity within a city was associated with the opinions of that city's mayoral official (i.e., mayor or deputy mayor) about health disparities in their city. METHODS: The independent variable was the magnitude of income-based life expectancy disparity in US cities. The magnitude was determined by linking 2010-2015 estimates of life expectancy and median household income for 8,434 census tracts in 224 cities. The dependent variables were mayoral officials' opinions from a 2016 survey about the existence and fairness of health disparities in their city (n = 224, response rate 30.3%). Multivariable logistic regression was used to adjust for characteristics of mayoral officials (e.g., ideology) and city characteristics. FINDINGS: In cities in the highest income-based life expectancy disparity quartile, 50.0% of mayoral officials "strongly agreed" that health disparities existed and 52.7% believed health disparities were "very unfair." In comparison, among mayoral officials in cities in the lowest disparity quartile 33.9% "strongly agreed" that health disparities existed and 22.2% believed the disparities were "very unfair." A 1-year-larger income-based life expectancy disparity in a city was associated with 25% higher odds that the city's mayoral official would "strongly agree" that health disparities existed (odds ratio [OR] = 1.25; P = .04) and twice the odds that the city's mayoral official would believe that such disparities were "very unfair" (OR = 2.24; P <.001). CONCLUSIONS: Mayoral officials' opinions about health disparities in their jurisdictions are generally aligned with, and potentially influenced by, information about the magnitude of income-based life expectancy disparities among their constituents.