Neighborhood-level disparities and subway utilization during the COVID-19 pandemic in New York City.
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ABSTRACT:
SUBMITTER: Carrion D
PROVIDER: S-EPMC8211826 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Using data from New York City from January 2020 to April 2020, we found an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of severe acute respiratory syndrome coronavirus 2 within New York City boroughs. We also conducted a cross-sectional analysis of the associations between human mobility (i.e., subway ridership) on the week of April 11, 2020, sociodemographic factors, and coronavirus disease 2019 (COVID-19) incidence as of April 26, 2020. Areas with lower median income, a greater percentage of individuals who identify as non-White and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of health-care essential workers had more mobility during the pandemic. When adjusted for the percentage of essential workers, these associations did not remain, suggesting essential work drives human movement in these areas. Increased mobility and all sociodemographic variables (except percentage of people older than 75 years old and percentage of health-care essential workers) were associated with a higher rate of COVID-19 cases per 100,000 people, when adjusted for testing effort. Our study demonstrates that the most socially disadvantaged not only are at an increased risk for COVID-19 infection, they lack the privilege to fully engage in social distancing interventions.
| S-EPMC7799254 | 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
Project description:Neighborhood physical disorder, or the deterioration of urban environments, is associated with negative mental and physical health outcomes. Eleven trained raters used CANVAS, a web-based system for conducting reliable virtual street audits, to collect data on nine indicators of physical disorder using Google Street View imagery of 532 block faces in New York City, New York, USA. We combined the block face indicator data into a disorder scale using item response theory; indicators ranged in severity from presence of litter, a weak indicator of disorder, to abandoned cars, a strong indicator. Using this scale, we estimated disorder at the center point of each sampled block. We then used ordinary kriging to interpolate estimates of disorder levels throughout the city. The resulting map condenses a complex estimation process into an interpretable visualization of the spatial distribution of physical disorder in New York City.
| S-EPMC4963033 | 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: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:Introduction:Liver cancer is the fastest increasing cancer in the United States and is one of the leading causes of cancer-related death in New York City (NYC), with wide disparities among neighborhoods. The purpose of this cross-sectional study was to describe liver cancer incidence by neighborhood and examine its association with risk factors. This information can inform preventive and treatment interventions. Materials and methods:Publicly available data were collected on adult NYC residents (n?=?6,407,022). Age-adjusted data on liver and intrahepatic bile duct cancer came from the New York State Cancer Registry (1) (2007-2011 average annual incidence); and the NYC Vital Statistics Bureau (2015, mortality). Data on liver cancer risk factors (2012-2015) were sourced from the New York City Department of Health and Mental Hygiene: (1) Community Health Survey, (2) A1C registry, and (3) NYC Health Department Hepatitis surveillance data. They included prevalence of obesity, diabetes, diabetic control, alcohol-related hospitalizations or emergency department visits, hepatitis B and C rates, hepatitis B vaccine coverage, and injecting drug use. Results:Liver cancer incidence in NYC was strongly associated with neighborhood poverty after adjusting for race/ethnicity (??=?0.0217, p?=?0.013); and with infection risk scores (??=?0.0389, 95% CI?=?0.0088-0.069, p?=?0.011), particularly in the poorest neighborhoods (??=?0.1207, 95% CI?=?0.0147-0.2267, p?=?0.026). Some neighborhoods with high hepatitis rates do not have a proportionate number of hepatitis prevention services. Conclusion:High liver cancer incidence is strongly associated with infection risk factors in NYC. There are gaps in hepatitis prevention services like syringe exchange and vaccination that should be addressed. The role of alcohol and metabolic risk factors on liver cancer in NYC warrants further study.
| S-EPMC6011126 | 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:BackgroundMask use is a cost-effective measure to decrease COVID-19 transmission. Mask mandates intend to increase mask compliance but are often ambiguous when it comes to public outdoor spaces.MethodsWe used a field audit study to examine mask use in New York City neighborhood parks during COVID-19. 1453 park visitors were observed in 13 parks during July-August 2020 using a modified and validated park use audit tool (System for Observing Play and Recreation in Communities) that included items on general and proper mask use (i.e., mask covering both nose and mouth). Generalized estimating equation regression was used to determine the association between proper mask use and demographic (sex and age) and behavioral (physical and social activity) variables, while adjusting for community-level covariates.ResultsOverall, 39.0% of park visitors used masks (24.4% properly, 14.6% improperly). Females (p = 0.023), adults (p = 0.025), and seniors (p = 0.006) showed higher rates of proper mask use compared to males and younger visitors. Physical and social activity were not significantly associated with proper mask use.ConclusionThere is a need for improved messaging regarding the proper use of masks among males and younger people. This is particularly important for future surges of new COVID-19 variants or other public health crises similar to COVID-19. Future research should focus on developing and evaluating targeted public health messages regarding mask use.
| S-EPMC8855606 | biostudies-literature
Project description:OBJECTIVES:Investigate whether or not race is associated with differences in hospitalization and survival to discharge among patients with coronavirus disease-2019 (COVID-19) at the height of the pandemic in New York City (NYC). METHODS:Single-center retrospective cohort study of COVID-19 patients hospitalized at our university-affiliated NYC hospital from 3/10/20 through 4/13/20 with follow-up to 5/1/20. Our primary endpoint was hospitalization rate among patients with confirmed COVID-19 compared with the regional population based on race. Our secondary endpoint survival to discharge among hospitalized COVID-19 patients. NYC Department of Health data were used to calculate hospitalization odds ratios. Chi-square and t tests were used to compare categorial and continuous variables, respectively. Cox proportional hazards regression and predictive analysis were used to investigate our endpoints further. RESULTS:Our cohort of 734 patients included 355 women (48.4%), 372 Blacks (50.7%), 214 Whites (29.2%), and 92 Hispanics (12.5%) in our analysis. Blacks were nearly twice as likely as Whites to require hospitalization for COVID-19 (OR 1.89, 95% CI, 1.59-2.24, p?<?0.001). Hispanics were also more likely to suffer in-hospital mortality from COVID-19 compared with Whites (HR 1.84; 95% CI 1.21-2.80; p?= 0.005). There was a non-significant increased hazard of in-hospital mortality among Blacks when compared with Whites (HR, 1.30; 95% CI, 0.95-1.78; p?= 0.09). CONCLUSIONS AND RELEVANCE:Blacks were more likely than Whites to require hospitalization for COVID-19 while Hispanics were more likely to experience in-hospital mortality. Further investigation into the socioeconomic factors underlying racial disparities in COVID-19 survival and severity requiring hospitalization is needed on a national scale.
| S-EPMC7500250 | biostudies-literature
Project description: Not available
| S-EPMC8025442 | biostudies-literature