Neighborhood disparities in COVID-19 outcomes in New York city over the first two waves of the outbreak

Assessing New York City's COVID-19 Vaccine Rollout Strategy: A Case for Risk-Informed Distribution

This study reviews the impact of eligibility policies in the early rollout of the COVID-19 vaccine on coverage and probable outcomes, with a focus on New York City. We conducted a retrospective ecological study assessing age  65+, area-level income, vaccination coverage, and COVID-19 mortality rates, using linked Census Bureau data and New York City Health administrative data aggregated at the level of modified zip code tabulation areas (MODZCTA). The population for this study was all individuals in 177 MODZCTA in New York City. Population data were obtained from Census Bureau and New York City Health administrative data. The total mortality rate was examined through an ordinary least squares (OLS) regression model, using area-level wealth, the proportion of the population aged 65 and above, and the vaccination rate among this age group as predictors. Low-income areas with high proportions of older people demonstrated lower coverage rates (mean vaccination rate 52.8%; maximum coverage 67.9%) than wealthier areas (mean vaccination rate 74.6%; maximum coverage 99% in the wealthiest quintile) in the first 3 months of vaccine rollout and higher mortality over the year. Despite vaccine shortages, many younger people accessed vaccines ahead of schedule, particularly in high-income areas (mean coverage rate 60% among those 45-64 years in the wealthiest quintile). A vaccine program that prioritized those at greatest risk of COVID-19-associated morbidity and mortality would have prevented more deaths than the strategy that was implemented. When rolling out a new vaccine, policymakers must account for local contexts and conditions of high-risk population groups. If New York had focused limited vaccine supply on low-income areas with high proportions of residents 65 or older, overall mortality might have been lower.

Visible minority status and occupation were associated with increased COVID-19 infection in Greater Vancouver British Columbia between June and November 2020: an ecological study

Background

The COVID-19 pandemic has highlighted health disparities, especially among specific population groups. This study examines the spatial relationship between the proportion of visible minorities (VM), occupation types and COVID-19 infection in the Greater Vancouver region of British Columbia, Canada.

Methods

Provincial COVID-19 case data between June 24, 2020, and November 7, 2020, were aggregated by census dissemination area and linked with sociodemographic data from the Canadian 2016 census. Bayesian spatial Poisson regression models were used to examine the association between proportion of visible minorities, occupation types and COVID-19 infection. Models were adjusted for COVID-19 testing rates and other sociodemographic factors. Relative risk (RR) and 95% Credible Intervals (95% CrI) were calculated.

Results

We found an inverse relationship between the proportion of the Chinese population and risk of COVID-19 infection (RR = 0.98 95% CrI = 0.96, 0.99), whereas an increased risk was observed for the proportions of the South Asian group (RR = 1.10, 95% CrI = 1.08, 1.12), and Other Visible Minority group (RR = 1.06, 95% CrI = 1.04, 1.08). Similarly, a higher proportion of frontline workers (RR = 1.05, 95% CrI = 1.04, 1.07) was associated with higher infection risk compared to non-frontline.

Conclusion

Despite adjustments for testing, housing, occupation, and other social economic status variables, there is still a substantial association between the proportion of visible minorities, occupation types, and the risk of acquiring COVID-19 infection in British Columbia. This ecological analysis highlights the existing disparities in the burden of diseases among different visible minority populations and occupation types.

Social determinants of health disparities in Staten Island compared with Manhattan, Queens, Brooklyn, and the Bronx: Contribution to COVID-19 outcomes

INTRODUCTION

Social determinants of health (SDH) negatively affected Coronavirus disease-2019 (COVID-19) outcomes within the five boroughs of New York City. The goal of this study was to determine whether differences in social demographics within the borough of Staten Island, compared with the other four boroughs, may have contributed to poor COVID-19 outcomes in Staten Island.

METHODS

Data were obtained from public data sources. Social demographics obtained included age, household income, poverty status, and education level. COVID-19 infection, hospitalization, and death rates reported from Staten Island were compared with rates from Manhattan, Queens, Brooklyn, and the Bronx (February 29, 2020-October 31, 2022). Mean differences in case rates of COVID-19 were higher in Staten Island compared to all four boroughs.

RESULTS

Mean differences in hospitalization and death rates were higher than Manhattan but similar to the other four boroughs. Within Staten Island, case rates were highest in zip codes 10306 and 10309. Hospitalization and death rates were highest in Staten Island zip code 10304. We found that the zip codes of Staten Island with poorer COVID-19 outcomes had more individuals with less than a high school degree, lower mean household income, higher proportion of households earning less than $25,000 a year, and a greater proportion of individuals using public transportation.

CONCLUSION

Differences in COVID-19 infection, hospitalization, and death rates exist between the five boroughs and between the 12 zip codes within Staten Island. These differences in COVID-19 outcomes can be attributed to different SDH.

Racial differences in COVID-19 severity associated with history of substance use disorders and overdose: Findings from multi-site electronic health records in New York City

Substance use disorders (SUD) are associated with increased risk of worse COVID-19 outcomes. Likewise, racial/ethnic minority patients experience greater risk of severe COVID-19 disease compared to white patients. Providers should understand the role of race and ethnicity as an effect modifier on COVID-19 severity among individuals with SUD. This retrospective cohort study assessed patient race/ethnicity as an effect modifier of the risk of severe COVID-19 disease among patients with histories of SUD and overdose. We used merged electronic health record data from 116,471 adult patients with a COVID-19 encounter between March 2020 and February 2021 across five healthcare systems in New York City. Exposures were patient histories of SUD and overdose. Outcomes were risk of COVID-19 hospitalization and subsequent COVID-19-related ventilation, acute kidney failure, sepsis, and mortality. Risk factors included patient age, sex, and race/ethnicity, as well as medical comorbidities associated with COVID-19 severity. We tested for interaction between SUD and patient race/ethnicity on COVID-19 outcomes. Findings showed that Non-Hispanic Black, Hispanic/Latino, and Asian/Pacific Islander patients experienced a higher prevalence of all adverse COVID-19 outcomes compared to non-Hispanic white patients. Past-year alcohol (OR 1.24 [1.01-1.53]) and opioid use disorders (OR 1.91 [1.46-2.49]), as well as overdose history (OR 4.45 [3.62-5.46]), were predictive of COVID-19 mortality, as well as other adverse COVID-19 outcomes. Among patients with SUD, significant differences in outcome risk were detected between patients of different race/ethnicity groups. Findings indicate that providers should consider multiple dimensions of vulnerability to adequately manage COVID-19 disease among populations with SUDs.

Exploration of the COVID-19 pandemic at the neighborhood level in an intra-urban setting

The COVID-19 pandemic represents a worldwide threat to health. Since its onset in 2019, the pandemic has proceeded in different phases, which have been shaped by a complex set of influencing factors, including public health and social measures, the emergence of new virus variants, and seasonality. Understanding the development of COVID-19 incidence and its spatiotemporal patterns at a neighborhood level is crucial for local health authorities to identify high-risk areas and develop tailored mitigation strategies. However, analyses at the neighborhood level are scarce and mostly limited to specific phases of the pandemic. The aim of this study was to explore the development of COVID-19 incidence and spatiotemporal patterns of incidence at a neighborhood scale in an intra-urban setting over several pandemic phases (March 2020-December 2021). We used reported COVID-19 case data from the health department of the district Berlin-Neukölln, Germany, additional socio-demographic data, and text documents and materials on implemented public health and social measures. We examined incidence over time in the context of the measures and other influencing factors, with a particular focus on age groups. We used incidence maps and spatial scan statistics to reveal changing spatiotemporal patterns. Our results show that several factors may have influenced the development of COVID-19 incidence. In particular, the far-reaching measures for contact reduction showed a substantial impact on incidence in Neukölln. We observed several age group-specific effects: school closures had an effect on incidence in the younger population (< 18 years), whereas the start of the vaccination campaign had an impact primarily on incidence among the elderly (> 65  years). The spatial analysis revealed that high-risk areas were heterogeneously distributed across the district. The location of high-risk areas also changed across the pandemic phases. In this study, existing intra-urban studies were supplemented by our investigation of the course of the pandemic and the underlying processes at a small scale over a long period of time. Our findings provide new insights for public health authorities, community planners, and policymakers about the spatiotemporal development of the COVID-19 pandemic at the neighborhood level. These insights are crucial for guiding decision-makers in implementing mitigation strategies.

Disruption of Healthcare in New York City During the COVID-19 Pandemic: Findings From Residents Living in North and Central Brooklyn, the South Bronx, and East and Central Harlem

INTRODUCTION

The COVID-19 pandemic has disproportionately affected some New York City (NYC) neighborhoods that primarily consist of Black, Indigenous, and Latinx residents. In comparison to the rest of NYC, these neighborhoods experienced high hospitalization and COVID-related death rates, which has been attributed to a longstanding history of structural racism and disinvestment. While stay-at-home orders were implemented to reduce the spread of COVID-19, this may have also affected access and utilization of non-COVID related healthcare services. This study aims to assess the prevalence of and reasons for the disruption of non-COVID related healthcare services during the first 18 months of the pandemic.

METHODS

From September 30, 2021 to November 4, 2021, the NYC Health Department administered the COVID-19 Community Recovery Survey to a subset of residents who were part of the NYC Health Panel a probability-based survey panel. This cross-sectional survey, which included closed and open-ended questions, was either self-administered online or completed via CATI (Computer Assisted Telephone Interviewing) in English, Spanish, and Simplified Chinese. Descriptive statistics were used to summarize responses and unweighted, weighted, age-adjusted percentages, and 95% Confidence Intervals (CIs) were calculated.

RESULTS

With a response rate of 30.3% (N = 1358), more than half of participants (54%) reported disruption to either routine physical healthcare or mental health services. Concern about getting COVID-19 (61%), stay-at-home policies (40%), belief that care could safely be postponed (35%), and appointment challenges (34%) were among reasons for delaying routine healthcare. Concern about getting COVID-19 (38%) and reduced hours of service (36%) were primary reasons for delaying mental healthcare. Reported reasons for the sustained delay of care past 18 months involved COVID concerns, appointment, and insurance challenges.

CONCLUSIONS

Due to the pandemic, some disruption to healthcare was expected. However, most study participants either avoided or experienced a delay in healthcare. The delay of non-COVID related healthcare throughout the pandemic may result in the further widening of the health inequity gap among NYC residents dealing with a higher chronic disease burden before the start of the COVID-19 pandemic in March 2020. Findings from this study can support equitable COVID-19 recovery, and guide efforts with health promotion.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.