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Objective: Assessing excess deaths from benchmarks across causes of death during the first wave of the COVID-19 pandemic and identifying morbidities most frequently mentioned alongside COVID-19 deaths in the death record., Methods: Descriptive study of death records between 11 March 2020 and 27 July 2020, from the New York City Bureau of Vital Statistics. Mortality counts and percentages were compared with the average for the same calendar period of the previous 2 years. Distributions of morbidities from among forty categories of conditions were generated citywide and by sex, race/ethnicity and four age groups. Causes of death were assumed to follow Poisson processes for Z-score construction., Results: Within the study period, 46 563 all-cause deaths were reported; 132.9% higher than the average for the same period of the previous 2 years (19 989). Of those 46 563 records, 19 789 (42.5%) report COVID-19 as underlying cause of death. COVID-19 was the most prevalent cause across all demographics, with respiratory conditions (prominently pneumonia), hypertension and diabetes frequently mentioned morbidities. Black non-Hispanics had greater proportions of mentions of pneumonia, hypertension, and diabetes. Hispanics had the largest proportion of COVID-19 deaths (52.9%). Non-COVID-19 excess deaths relative to the previous 2-year averages were widely reported., Conclusion: Mortality directly due to COVID-19 was accompanied by significant increases across most other causes from their reference averages, potentially suggesting a sizable COVID-19 death undercount. Indirect effects due to COVID-19 may partially account for some increases, but findings are hardly dispositive. Unavailability of vaccines for the time period precludes any impact over excess deaths. Respiratory and cardiometabolic-related conditions were most frequently reported among COVID-19 deaths across demographic characteristics., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To adapt an existing surveillance system to monitor the collateral impacts of the COVID-19 pandemic on health outcomes in New York City across 6 domains: access to care, chronic disease, sexual/reproductive health, food/economic insecurity, mental/behavioral health, and environmental health., Design: Epidemiologic assessment. Public health surveillance system., Setting: New York City., Participants: New York City residents., Main Outcome Measures: We monitored approximately 30 indicators, compiling data from 2006 to 2022. Sources of data include clinic visits, surveillance surveys, vital statistics, emergency department visits, lead and diabetes registries, Medicaid claims, and public benefit enrollment., Results: We observed disruptions across most indicators including more than 50% decrease in emergency department usage early in the pandemic, which rebounded to prepandemic levels by late 2021, changes in reporting levels of probable anxiety and depression, and worsening birth outcomes for mothers who identified as Asian/Pacific Islander or Black. Data are processed in SAS and analyzed using the R Surveillance package to detect possible inflections. Data are updated monthly to an internal Tableau Dashboard and shared with agency leadership., Conclusions: As the COVID-19 pandemic continues into its third year, public health priorities are returning to addressing non-COVID-19-related diseases and conditions, their collateral impacts, and postpandemic recovery needs. Substantial work is needed to return even to a suboptimal baseline across multiple health topic areas. Our surveillance framework offers a valuable starting place to effectively allocate resources, develop interventions, and issue public communications., Competing Interests: The authors have no financial or material support to declare. The authors have indicated that they have no potential conflicts of interest to disclose., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc.)

Neighborhood conditions influence people's health; sustaining healthy neighborhoods is a New York City (NYC) Health Department priority. Gentrification is characterized by rapid development in historically disinvested neighborhoods. The gentrification burden, including increased living expenses, and disrupted social networks, disproportionally impacts certain residents. To ultimately target health promotion interventions, we examined serious psychological distress time trends in gentrifying NYC neighborhoods to describe the association of gentrification and mental health overall and stratified by race and ethnicity. We categorized NYC neighborhoods as hypergentrifying, gentrifying, and not-gentrifying using a modified New York University Furman Center index. Neighborhoods with ≥100% rent growth were hypergentrifying; neighborhoods with greater than median and <100% rent growth were gentrifying; and neighborhoods with less than median rent growth were not-gentrifying. To temporally align neighborhood categorization closely with neighborhood-level measurement of serious psychological distress, data during 2000-2017 were used to classify neighborhood type. We calculated serious psychological distress prevalence among adult populations using data from 10 NYC Community Health Surveys during 2002-2015. Using joinpoint and survey-weighted logistic regression, we analyzed serious psychological distress prevalence time trends during 2002-2015 by gentrification level, stratified by race/ethnicity. Among 42 neighborhoods, 7 were hypergentrifying, 7 were gentrifying, and 28 were not gentrifying. In hypergentrifying neighborhoods, serious psychological distress prevalence decreased among White populations (8.1% to 2.3%, β = -0.77, P = 0.02) and was stable among Black (4.6% to 6.9%, β = -0.01, P = 0.95) and Latino populations (11.9% to 10.4%, β = -0.16, P = 0.31). As neighborhoods gentrified, different populations were affected differently. Serious psychological distress decreased among White populations in hypergentrifying neighborhoods, no similar reductions were observed among Black and Latino populations. This analysis highlights potential unequal mental health impacts that can be associated with gentrification-related neighborhood changes. Our findings will be used to target health promotion activities to strengthen community resilience and to ultimately guide urban development policies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Alroy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: To develop recommendations to embed equity into data work at a local health department and a framework for antiracist data praxis., Design: A working group comprised staff from across the agency whose positions involved data collection, analysis, interpretation, or communication met during April-July 2018 to identify and discuss successes and challenges experienced by staff and to generate recommendations for achieving equitable data practices., Setting: Local health department in New York City., Results: The recommendations encompassed 6 themes: strengthening analytic skills, communication and interpretation, data collection and aggregation, community engagement, infrastructure and capacity building, and leadership and innovation. Specific projects are underway or have been completed., Conclusions: Improving equity in data requires changes to data processes and commitment to racial and intersectional justice and process change at all levels of the organization and across job functions. We developed a collaborative model for how a local health department can reform data work to embed an equity lens. This framework serves as a model for jurisdictions to build upon in their own efforts to promote equitable health outcomes and become antiracist organizations., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc.)

Repeated serosurveys are an important tool for understanding trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination. During 1 September 2020-20 March 2021, the NYC Health Department conducted a population-based SARS-CoV-2 antibody prevalence survey of 2096 NYC adults who either provided a blood specimen or self-reported the results of a previous antibody test. The serosurvey, the second in a series of surveys conducted by the NYC Health Department, aimed to estimate SARS-CoV-2 antibody prevalence across the city and for different groups at higher risk for adverse health outcomes. Weighted citywide prevalence was 23.5% overall (95% confidence interval (CI) 20.1-27.4) and increased from 19.2% (95% CI 14.7-24.6) before coronavirus disease 2019 vaccines were available to 31.3% (95% CI 24.5-39.0) during the early phases of vaccine roll-out. We found no differences in antibody prevalence by age, race/ethnicity, borough, education, marital status, sex, health insurance coverage, self-reported general health or neighbourhood poverty. These results show an overall increase in population-level seropositivity in NYC following the introduction of SARS-CoV-2 vaccines and highlight the importance of repeated serosurveys in understanding the pandemic's progression.

Objectives: To examine racial and ethnic disparities in COVID-19-like illness (CLI) during March - August 2020 in New York City, and to test effect modification by age, nativity, and working from home vs outside the home, and mediation via social distancing behavior., Design: Analysis of the monthly Community Health Survey datasets., Setting: New York City., Participants: 5,305 adults living in New York City., Main Outcome Measures: A binary indicator of having new onset of CLI in the past 30 days., Methods: Prevalence of having CLI was compared among racial and ethnic groups using multivariable log-linear regression. Stratified and causal mediation analyses were conducted to test effect modification and mediation, respectively., Results: Overall percentage of CLI decreased from 25% during March-May to 14% during June-August. In both periods, there was no increased prevalence of CLI among Black or Latino New Yorkers compared with White New Yorkers. However, in stratified analyses, Latino vs White New Yorkers had 2.05 times (95%CI=1.09, 3.83) higher prevalence of CLI among adults working outside the home. Mediation via social distancing was not statistically significant., Conclusions: Excess burden of CLI among Latino adults working outside the home underscores inequitable impacts of COVID-19 in New York City., Competing Interests: Competing Interests: None declared., (Copyright © 2022, Ethnicity & Disease, Inc.)

The New York City (NYC) Department of Health and Mental Hygiene ("Health Department") conducts routine surveys to describe the health of NYC residents. During the COVID-19 pandemic, the Health Department adjusted existing surveys and developed new ones to improve our understanding of the impact of the pandemic on physical health, mental health, and social determinants of health and to incorporate more explicit measures of racial inequities. The longstanding Community Health Survey was adapted in 2020 to ask questions about COVID-19 and recruit respondents for a population-based severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey. A new survey panel, Healthy NYC, was launched in June 2020 and is being used to collect data on COVID-19, mental health, and social determinants of health. In addition, 7 Health Opinion Polls were conducted from March 2020 through March 2021 to learn about COVID-19-related knowledge, attitudes, and opinions, including vaccine intentions. We describe the contributions that survey data have made to the emergency response in NYC in ways that address COVID-19 and the profound inequities of the pandemic. ( Am J Public Health . 2021;111(12):2176-2185. https://doi.org/10.2105/AJPH.2021.306515).

Using a population-based, representative telephone survey, ~930 000 New York City residents had COVID-19 illness beginning 20 March-30 April 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics., (Published by Oxford University Press for the Infectious Diseases Society of America 2021.)

Background: Serosurveys help to ascertain burden of infection. Prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveys in New York City (NYC) used nonrandom samples. During June-October 2020, the NYC Health Department conducted a population-based survey estimating SARS-CoV-2 antibody prevalence in NYC adults., Methods: Participants were recruited from the NYC 2020 Community Health Survey. We estimated citywide and stratified antibody prevalence using a hybrid design: serum tested with the DiaSorin LIAISON SARS-CoV-2 S1/S2 IgG assay and self-reported antibody test results were used together. We estimated univariate frequencies and 95% confidence intervals (CI), accounting for complex survey design. Two-sided P values ≤ .05 were statistically significant., Results: There were 1074 respondents; 497 provided blood and 577 provided only a self-reported antibody test result. Weighted prevalence was 24.3% overall (95% CI, 20.7%-28.3%). Latino (30.7%; 95% CI, 24.1%-38.2%; P < .01) and black (30.7%; 95% CI, 21.9%-41.2%; P = .02) respondents had a higher weighted prevalence compared with white respondents (17.4%; 95% CI, 12.5%-23.7%)., Conclusions: By October 2020, nearly 1 in 3 black and 1 in 3 Latino NYC adults had SARS-CoV-2 antibodies, highlighting unequal impacts of the coronavirus disease 2019 (COVID-19) pandemic on black and Latino NYC adults., (Published by Oxford University Press for the Infectious Diseases Society of America 2021.)

Context: Food-induced anaphylaxis is potentially fatal but preventable by allergen avoidance and manageable through immediate treatment. Considerable effort has been invested in preventing fatalities from nut exposure among school-aged children, but few population-based studies exist to guide additional prevention efforts., Objectives: To describe the epidemiology and trends of food-related anaphylaxis requiring emergency treatment during a 15-year span in New York City when public health initiatives to prevent deaths were implemented and to understand the situational circumstances of food-related deaths., Design/setting/participants: Retrospective death record review and analysis of inpatient hospital discharges and emergency department (ED) visits in New York City residents, 2000-2014., Main Outcome: Vital statistics data, medical examiner reports, ED, and hospital discharge data were used to examine risk for death and incidence trends in medically attended food-related anaphylaxis. Potentially preventable deaths were those among persons with a known allergy to the implicated food or occurring in public settings., Results: There were 24 deaths, (1.6 deaths/year; range: 0-5), 3049 hospitalizations, and 4014 ED visits, including 7 deaths from crustacean, 4 from peanut, and 2 each from tree nut or seeds and fish exposures. Risk for death among those hospitalized or treated in the ED was highest for persons older than 65 years and for those treated for crustacean reactions (relative risk 6.5 compared with those treated for peanuts, 95% confidence interval = 1.9-22.1). Eleven of 16 deaths with medical examiner data were potentially preventable. Hospitalizations (2000-2014) and ED visit rates (2005-2014) were highest for children and those with peanut exposure and increased across periods., Conclusions: Deaths from food-related anaphylaxis were rare; however, rates of hospitalization and ED visits increased. Prevention efforts related to peanut allergies among children should continue, and additional attention is needed to prevent and treat anaphylaxis among adults, particularly those with known crustacean allergies where case fatality is highest.

Context: The Trump administration has enacted or proposed many policies that could impact public health. These include attempts to dismantle or repeal the Patient Protection and Affordable Care Act (ACA), restricting funding for women's health care, and loosening of environmental regulations., Objective: To develop a surveillance system to monitor the public health impacts of the Trump administration in New York City., Design: Epidemiologic assessment. Public health surveillance system., Setting: New York City., Participants: New York City residents., Main Outcomes Measures: We identified approximately 25 indicators across 5 domains: access to care, food insecurity, reproductive health, environmental health, and general physical and mental health. Sources of data include the New York City Department of Health and Mental Hygiene's (DOHMH's) health and risk behavior telephone survey, vital statistics, emergency department visits, DOHMH sexual health clinics, Federally Qualified Health Centers, lead and diabetes registries, Medicaid claims, Supplementary Nutrition Assistance Program enrollment, Women, Infant, and Children program enrollment, and 311 call records. Data are collected monthly or quarterly where possible. We identified measures to stratify indicators by individual and area-based measures of immigration and poverty., Results: Since April 2017, we have compiled quarterly reports, including establishing a historical baseline of 10 years to account for secular trends and encompass the establishment and enactment of the ACA. Indicators are interpreted within the context of changes in programming or local policy that might explain trends., Conclusions: We have successfully established an adaptive surveillance system that is poised to rapidly detect changes in the health of New York City residents resulting from changes by the Trump administration to public health policy. The development of such systems is a critical function for health departments across the country to play a role in the current political and policy environment.

We assessed the added value and limitations of generating directly estimated ZIP Code-level estimates by aggregating 5 years of data from an annual cross-sectional survey, the New York City Community Health Survey (n = 44,886) from 2009 to 2013, that were designed to provide reliable estimates only of larger geographies. Survey weights generated directly-observed ZIP Code (n = 128) level estimates. We assessed the heterogeneity of ZIP Code-level estimates within coarser United Hospital Fund (UHF) neighborhood areas (n = 34) by using the Rao-Scott Chi-Square test and one-way ANOVA. Orthogonal linear contrasts assessed whether there were linear trends at the UHF level from 2009 to 2013. 22 of 37 health indicators were reliable in over 50% of ZIP Codes. 14 of the 22 variables showed heterogeneity in ≥4 UHFs. Variables for drinking, nutrition, and HIV testing showed heterogeneity in the most UHFs (9-24 UHFs). In half of the 32 UHFs, >20% variables had within-UHF heterogeneity. Flu vaccination and sugary beverage consumption showed significant time trends in the largest number of UHFs (12 or more UHFs). Overall, heterogeneity of ZIP Code-level estimates suggests that there is value in aggregating 5 years of data to make direct small area estimates.

Supportive housing addresses a fundamental survival need among homeless persons, which can lead to reduced risk of diabetes mellitus and improved diabetes care. We tested the association between supportive housing and diabetes outcomes among homeless adults who were eligible for New York City's supportive housing program in 2007-2012. We used multiple administrative data sources, identifying 7,525 Medicaid-eligible adults. The outcomes included receiving medical evaluation and management services, hemoglobin A1C and lipid testing (n = 1,489 persons with baseline diabetes), and incidence of new diabetes diagnoses (n = 6,036 persons without baseline diabetes) in the 2 years postbaseline. Differences in these outcomes by placement were estimated using inverse-probability-of-treatment weighting. Placed persons were more likely to receive evaluation and management services (relative risk (RR) = 1.03, 95% confidence interval (CI): 1.01, 1.04) than unplaced persons. For those with baseline diabetes, placed persons were more likely to receive hemoglobin A1C tests (RR = 1.10, 95% CI: 1.02, 1.19) and lipid tests (RR = 1.09, 95% CI: 1.02, 1.17). For those without baseline diabetes, placement was also associated with lower risk of new diabetes diagnoses (RR = 0.87, 95% CI: 0.76, 0.99). These findings show that benefits of supportive housing may be extended to diabetes care and prevention., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2019.)

Background: In 2016, an influenza A(H7N2) virus outbreak occurred in cats in New York City's municipal animal shelters. One human infection was initially detected., Methods: We conducted a serological survey using a novel approach to rule out cross-reactive antibodies to other seasonal influenza viruses to determine whether additional A(H7N2) human infections had occurred and to assess exposure risk., Results: Of 121 shelter workers, one had serological evidence of A(H7N2) infection, corresponding to a seroprevalence of 0.8% (95% confidence interval, .02%-4.5%). Five persons exhibited low positive titers to A(H7N2) virus, indicating possible infection; however, we could not exclude cross-reactive antibody responses to seasonal influenza viruses. The remaining 115 persons were seronegative. The seropositive person reported multiple direct cat exposures without using personal protective equipment and mild illness with subjective fever, runny nose, and sore throat., Conclusions: We identified a second case of A(H7N2) infection from this outbreak, providing further evidence of cat-to-human transmission of A(H7N2) virus., (Published by Oxford University Press for the Infectious Diseases Society of America 2018.)

Objective: To assess the impact of a New York City supportive housing program on housing stability and preventable emergency department (ED) visits/hospitalizations among heads of homeless families with mental and physical health conditions or substance use disorders., Data Sources: Multiple administrative data from New York City and New York State for 966 heads of families eligible for the program during 2007-12., Study Design: We captured housing events and health care service utilization during 2 years prior to the first program eligibility date (baseline) and 2 years postbaseline. We performed sequence analysis to measure housing stability and compared housing stability and preventable ED visits and hospitalizations between program participants (treatment group) and eligible applicants not placed in the program (comparison group) via marginal structural modeling., Data Collection/extraction Methods: We matched electronically collected data., Principal Findings: Eighty-seven percent of supportive housing tenants experienced housing stability in 2 years postbaseline. Compared with unstably housed heads of families in the comparison group, those in the treatment group were 0.60 times as likely to make preventable ED visits postbaseline (95% CI = 0.38, 0.96)., Conclusions: Supportive housing placement was associated with improved housing stability and reduced preventable health care visits among homeless families., (© Health Research and Educational Trust.)

It is unknown whether providing housing to persons experiencing homelessness decreases HIV risk. Housing, including access to preventive services and counseling, might provide a period of transition for persons with HIV risk factors. We assessed whether the new HIV diagnosis rate was associated with duration of supportive housing. We linked data from a cohort of 21,689 persons without a previous HIV diagnosis who applied to a supportive housing program in New York City (NYC) during 2007-2013 to the NYC HIV surveillance registry. We used time-dependent Cox modeling to compare new HIV diagnoses among recipients of supportive housing (defined a priori, for program evaluation purposes, as persons who spent > 7 days in supportive housing; n = 6447) and unplaced applicants (remainder of cohort), after balancing the groups on baseline characteristics with propensity score weights. Compared with unplaced applicants, persons who received ≥ 3 continuous years of supportive housing had decreased risk for new HIV diagnosis (HR 0.10; CI 0.01-0.99). Risk of new HIV diagnosis decreased with longer duration placement in supportive housing. Supportive housing might aid in primary HIV prevention.

This study examined factors associated with being paid for sick leave after implementation of the New York City (NYC) paid sick leave law. A random sample of NYC residents was surveyed by telephone multiple times over a 2-year period. Participants (n = 1195) reported socio-demographics, awareness of the law, income, work hours per week, and payment for sick time off work. In the year after implementation of the law, part-time workers were significantly more likely to attend work while sick than full-time workers (relative risk = 1.25, 95% CI = 1.1, 1.4). Seventy percent of workers who missed work due to illness (n = 249) were paid for sick leave. Part-time workers, respondents not aware of the benefit (30% of workers), and workers without a college degree were the least likely to be paid for sick days. More than one third (37%) of persons not paid for sick leave worked in retail, food service, or health care. Although 70% of respondents were paid for sick leave after implementation of the law, part-time workers and workers with low education were least likely to access the benefit and more likely to work while sick. The disparity in paid sick leave may have public health consequences as many persons not paid for sick leave had occupations that carry a high risk of disease transmission to others.