Socioeconomic Disparities in Subway Use and COVID-19 Outcomes in New York City.
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ABSTRACT:
SUBMITTER: Sy KTL
PROVIDER: S-EPMC7799254 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The COVID-19 pandemic has yielded disproportionate impacts on communities of color in New York City (NYC). Researchers have noted that social disadvantage may result in limited capacity to socially distance, and consequent disparities. We investigate the association between neighborhood social disadvantage and the ability to socially distance, infections, and mortality in Spring 2020. We combine Census Bureau and NYC open data with SARS-CoV-2 testing data using supervised dimensionality-reduction with Bayesian Weighted Quantile Sums regression. The result is a ZIP code-level index with weighted social factors associated with infection risk. We find a positive association between neighborhood social disadvantage and infections, adjusting for the number of tests administered. Neighborhood disadvantage is also associated with a proxy of the capacity to socially isolate, NYC subway usage data. Finally, our index is associated with COVID-19-related mortality.
| S-EPMC8211826 | biostudies-literature
Project description:INTRODUCTION:Existing socioeconomic and racial disparities in healthcare access in New York City have likely impacted the public health response to COVID-19. An ecological study was performed to determine the spatial distribution of COVID-19 testing by ZIP code Tabulation Area and investigate if testing was associated with race or SES. METHODS:Data were obtained from the New York City coronavirus data repository and 2018 American Community Survey 5-year estimates. A combined index of SES was created using principal component analysis and incorporated household income, gross rent, poverty, education, working class status, unemployment, and occupants per room. Multivariable Poisson regressions were performed to predict the number of total tests and the ratio of positive tests to total tests performed, using the SES index, racial composition, and Hispanic composition as predictors. RESULTS:The number of total tests significantly increased with the increasing proportion of white residents (?=0.004, SE=0.001, p=0.0032) but not with increasing Hispanic composition or SES index score. The ratio of positive tests to total tests significantly decreased with the increasing proportion of white residents in the ZIP code Tabulation Area (?= -0.003, SE=0.000 6, p<0.001) and with increasing SES index score (?= -0.001 6, SE=0.0007, p=0.0159). CONCLUSIONS:In New York City, COVID-19 testing has not been proportional to need; existing socioeconomic and racial disparities in healthcare access have likely impacted public health response. There is urgent need for widespread testing and public health outreach for the most vulnerable communities in New York City.
| S-EPMC7316038 | biostudies-literature
Project description:ObjectivesThere is limited evidence on how clinical outcomes differ by socioeconomic conditions among patients with coronavirus disease 2019 (COVID-19). Most studies focused on COVID-19 patients from a single hospital. Results based on patients from multiple health systems have not been reported. The objective of this study is to examine variation in patient characteristics, outcomes, and healthcare utilization by neighborhood social conditions among COVID-19 patients.MethodsWe extracted electronic health record data for 23,300 community dwelling COVID-19 patients in New York City between March 1st and June 11th, 2020 from all care settings, including hospitalized patients, patients who presented to the emergency department without hospitalization, and patients with ambulatory visits only. Zip Code Tabulation Area-level social conditions were measured by the Social Deprivation Index (SDI). Using logistic regressions and Cox proportional-hazards models, we examined the association between SDI quintiles and hospitalization and death, controlling for race, ethnicity, and other patient characteristics.ResultsAmong 23,300 community dwelling COVID-19 patients, 60.7% were from neighborhoods with disadvantaged social conditions (top SDI quintile), although these neighborhoods only account for 34% of overall population. Compared to socially advantaged patients (bottom SDI quintile), socially disadvantaged patients (top SDI quintile) were older (median age 55 vs. 53, P<0.001), more likely to be black (23.1% vs. 6.4%, P<0.001) or Hispanic (25.4% vs. 8.5%, P<0.001), and more likely to have chronic conditions (e.g., diabetes: 21.9% vs. 10.5%, P<0.001). Logistic and Cox regressions showed that patients with disadvantaged social conditions had higher risk for hospitalization (odds ratio: 1.68; 95% confidence interval [CI]: [1.46, 1.94]; P<0.001) and mortality (hazard ratio: 1.91; 95% CI: [1.35, 2.70]; P<0.001), adjusting for other patient characteristics.ConclusionSubstantial socioeconomic disparities in health outcomes exist among COVID-19 patients in NYC. Disadvantaged neighborhood social conditions were associated with higher risk for hospitalization, severity of disease, and death.
| S-EPMC8321227 | biostudies-literature
Project description:IntroductionThis study aims to determine whether subway ridership and built environmental factors, such as population density and points of interests, are linked to the per capita COVID-19 infection rate in New York City ZIP codes, after controlling for racial and socioeconomic characteristics.MethodsSpatial lag models were employed to model the cumulative COVID-19 per capita infection rate in New York City ZIP codes (N=177) as of April 1 and May 25, 2020, accounting for the spatial relationships among observations. Both direct and total effects (through spatial relationships) were reported.ResultsThis study distinguished between density and crowding. Crowding (and not density) was associated with the higher infection rate on April 1. Average household size was another significant crowding-related variable in both models. There was no evidence that subway ridership was related to the COVID-19 infection rate. Racial and socioeconomic compositions were among the most significant predictors of spatial variation in COVID-19 per capita infection rates in New York City, even more so than variables such as point-of-interest rates, density, and nursing home bed rates.ConclusionsPoint-of-interest destinations not only could facilitate the spread of virus to other parts of the city (through indirect effects) but also were significantly associated with the higher infection rate in their immediate neighborhoods during the early stages of the pandemic. Policymakers should pay particularly close attention to neighborhoods with a high proportion of crowded households and these destinations during the early stages of pandemics.
| S-EPMC7835098 | biostudies-literature
Project description:BackgroundExcessive environmental noise exposure and noise annoyance have been linked to adverse physical and mental health outcomes. Although socioeconomic disparities in acoustically measured and geospatially estimated noise have been established, less is known about disparities in noise complaints, one of the most common sources of distress reported to local municipalities. Furthermore, although some studies have posited urban quieting during the COVID-19 pandemic, little empirical work has probed this and probed noise complaints during the pandemic.ObjectivesUsing over 4 million noise complaints from the New York City (NYC) 311 database, we quantified census tract-level socioeconomic disparities in noise complaints since 2010 and examined how such disparities changed during the COVID-19 pandemic.MethodsUsing data from January 2010 through February 2020, we fit linear mixed-effects models, estimating monthly tract-level noise complaints by the proportion of residents who were low-income, time in months since January 2010, categorical month, their interactions, and potential confounds, such as total population and population density. To estimate COVID-19 pandemic effects, we included additional data from March 2020 through February 2021 and additional interactions between proportion low-income, month of year, and an indicator variable for COVID-19 pandemic onset in March 2020.ResultsCensus tracts with a higher proportion of low-income residents reported more monthly noise complaints and this increased over time (time × month × proportion low-income interaction p-values < .0001 for all months), particularly in warmer months. Socioeconomic disparities in noise complaints were exacerbated during the COVID-19 pandemic (month × proportion low-income × pandemic era interaction p-values < .0001 for March through November), also in a seasonal manner.DiscussionSince 2010, noise complaints have increased the most in the most economically distressed communities, particularly in warmer seasons. This disparity was particularly exacerbated during the COVID-19 pandemic, contrary to some theories of urban quieting. Community-based interventions to ameliorate noise and noise annoyance, both public health hazards, are needed in underserved communities.
| S-EPMC8838876 | biostudies-literature
Project description:Black and Hispanic communities in the U.S. have endured a disproportionate burden of COVID-19-related morbidity and mortality. Racial and ethnic health disparities such as these are frequently aggravated by inequitable access to healthcare resources in disadvantaged communities. Yet, no known studies have investigated disadvantaged communities' access to COVID-19-related healthcare resources. The current study accordingly examined racial and ethnic differences in (1) April 2020 COVID-19 total and positive viral test rates across 177 New York City (NYC) ZIP Code Tabulation Areas (ZCTA); and (2) November 2019-April 2020 licensed and intensive care unit (ICU) hospital bed access across 194 NYC ZCTAs. Pairwise analyses indicated higher COVID-19 total and positive test rates per 1000 persons in majority Black and Hispanic vs. majority White ZCTAs (CI [0.117, 4.55]; CI [2.53, 5.14]). Multiple linear regression analyses indicated that higher percentage of Black and Hispanic residents predicted more total COVID-19 tests per 1000 persons (p < 0.05). In contrast, majority Black and Hispanic ZCTAs had fewer licensed and ICU beds (CI [6.50, 124.25]; CI [0.69, 7.16]), with social disadvantage predicting lower licensed and ICU bed access per 1000 persons (p < 0.01). While news reports of inequitable access to COVID-19-related healthcare resources in ethnocultural minority communities have emerged, this is the first study to reveal that social disadvantage may be a major driver of hospital resource inequities in Black and Hispanic communities. Thus, it will be imperative to enact policies that ensure equitable allocation of healthcare resources to socially disadvantaged communities to address current and future public health crises.
| S-EPMC7536513 | biostudies-literature
Project description:PurposeTo assess the association of neighborhood demographic and socioeconomic characteristics with COVID-19 incidence and mortality in New York City (NYC) over the first two waves of outbreak.MethodsThis retrospective study used neighborhood-level data from 177 modified ZIP code tabulation areas in NYC between March 01, 2020 and April 30, 2021.ResultsNeighborhoods that were most severely impacted in wave 1 were also more affected in wave 2. Neighborhoods with a higher percentage of seniors (≥75 years), males, Black and Hispanic population, and large-size households had higher incidence rates of COVID-19 in wave 1 but not in wave 2. Neighborhoods with higher percentage of Black and Hispanic population and lower insurance coverage had higher death rate per capita and case fatality ratio in wave 1, and neighborhoods with higher percentage of Black and Asian population had elevated case fatality ratio in wave 2. Median household income was negatively associated with incidence rate and death rate per capita but not associated with case fatality ratio in both waves. Neighborhoods with more seniors had higher death rate and case fatality ratio in both waves.ConclusionsNeighborhood disparities in COVID-19 incidence and mortality across NYC neighborhoods were dynamic during the first two waves of outbreak.
| S-EPMC9042413 | biostudies-literature
Project description: Not available
| S-EPMC8025442 | biostudies-literature
Project description:BackgroundNew York City (NYC) is the epicenter of severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]) in the United States. Clinical characteristics and outcomes of vulnerable populations, such as those with gynecologic cancer who develop COVID-19 infections, is limited.MethodsPatients from 6 NYC-area hospital systems with known gynecologic cancer and a COVID-19 diagnosis were identified. Demographic and clinical outcome data were abstracted through a review of electronic medical records.ResultsRecords for 121 patients with gynecologic cancer and COVID-19 were abstracted; the median age at the COVID-19 diagnosis was 64.0 years (interquartile range, 51.0-73.0 years). Sixty-six of the 121 patients (54.5%) required hospitalization; among the hospitalized patients, 45 (68.2%) required respiratory intervention, 20 (30.3%) were admitted to the intensive care unit, and 9 (13.6%) underwent invasive mechanical ventilation. Seventeen patients (14.0%) died of COVID-19 complications. No patient requiring mechanical ventilation survived. On multivariable analysis, hospitalization was associated with an age ≥64 years (risk ratio [RR], 1.73; 95% confidence interval [CI], 1.18-2.51), African American race (RR, 1.56; 95% CI, 1.13-2.15), and 3 or more comorbidities (RR, 1.43; 95% CI, 1.03-1.98). Only recent immunotherapy use (RR, 3.49; 95% CI, 1.08-11.27) was associated with death due to COVID-19 on multivariable analysis; chemotherapy treatment and recent major surgery were not predictive of COVID-19 severity or mortality.ConclusionsThe case fatality rate among gynecologic oncology patients with a COVID-19 infection is 14.0%. Recent immunotherapy use is associated with an increased risk of mortality related to COVID-19 infection.Lay summaryThe case fatality rate among gynecologic oncology patients with a coronavirus disease 2019 (COVID-19) infection is 14.0%; there is no association between cytotoxic chemotherapy and cancer-directed surgery and COVID-19 severity or death. As such, patients can be counseled regarding the safety of continued anticancer treatments during the pandemic. This is important because the ability to continue cancer therapies for cancer control and cure is critical.
| S-EPMC8654115 | biostudies-literature
Project description:BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged populations. Whether disparities in COVID-19 incidence related to race/ethnicity and socioeconomic factors exist in the hemodialysis population is unknown.MethodsOur study involved patients receiving in-center hemodialysis in New York City. We used a validated index of neighborhood social vulnerability, the Social Vulnerability Index (SVI), which comprises 15 census tract-level indicators organized into four themes: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. We examined the association of race/ethnicity and the SVI with symptomatic COVID-19 between March 1, 2020 and August 3, 2020. COVID-19 cases were ascertained using PCR testing. We performed multivariable logistic regression to adjust for demographics, individual-level social factors, dialysis-related medical history, and dialysis facility factors.ResultsOf the 1378 patients on hemodialysis in the study, 247 (17.9%) developed symptomatic COVID-19. In adjusted analyses, non-Hispanic Black and Hispanic patients had significantly increased odds of COVID-19 compared with non-Hispanic White patients. Census tract-level overall SVI, modeled continuously or in quintiles, was not associated with COVID-19 in unadjusted or adjusted analyses. Among non-Hispanic White patients, the socioeconomic status SVI theme, the minority status and language SVI theme, and housing crowding were significantly associated with COVID-19 in unadjusted analyses.ConclusionsAmong patients on hemodialysis in New York City, there were substantial racial/ethnic disparities in COVID-19 incidence not explained by neighborhood-level social vulnerability. Neighborhood-level socioeconomic status, minority status and language, and housing crowding were positively associated with acquiring COVID-19 among non-Hispanic Whites. Our findings suggest that socially vulnerable patients on dialysis face disparate COVID-19-related exposures, requiring targeted risk-mitigation strategies.
| S-EPMC8455266 | biostudies-literature