BACKGROUND:Social determinants of health play a crucial role as part of interlinking factors that shape health. Occupation is interrelated with socioeconomic status, a known predictor of mortality, that deserves a closer look in the context of the early period of the pandemic in New York City (NYC). To determine the highest mortality burden of COVID-19 by occupation in NYC during the early pandemic time period, we analyzed NYC Department of Health and Mental Hygiene (DOHMH) death certificate data. Our study considers the role of occupation in relation to deaths among working age individuals. METHODS:We analyzed confirmed and probable COVID-19 deaths among individuals 18-64 years using data from NYCDOHMH, the National Institute for Occupational Safety and Health (NIOSH), and the American Community Survey (ACS). Confirmed and probable COVID-19 deaths occurring from March 11, 2020 to December 31, 2021 were identified among decedents 18-64 years old. Proportional distributions and mortality rates were calculated by occupation. Occupational mortality rates were examined by age, sex, and race and ethnicity. Comparisons by nativity were examined in the context of occupational mortality risk to help identify additional vulnerable populations at risk. RESULTS:The highest overall mortality rate by occupation for the study population was found among food preparation and serving workers (182.1 per 100,000 population). Stratified mortality rates indicated that older adults, males, and minority racial and ethnic groups were disproportionally affected. The highest overall mortality rate by occupation for individuals aged 45-64 were found among protective service workers (419.9 per 100,000 population). More than half of decedents aged 18-64 were foreign-born (n = 3591, 59.2%). CONCLUSIONS:Our analysis highlights the inequities of COVID-19 deaths across occupations in NYC. It informs future studies and tailored interventions that target high-risk populations. This knowledge will ideally lead to more equitable, protective responses to future pandemics.

BACKGROUND:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widespread since 2020 and will likely continue to cause substantial recurring epidemics. However, understanding the underlying infection burden and dynamics, particularly since late 2021 when the Omicron variant emerged, is challenging. Here, we leverage extensive surveillance data available in New York City (NYC) and a comprehensive model-inference system to reconstruct SARS-CoV-2 dynamics therein through August 2023. METHODS:We fit a metapopulation network SEIRSV (Susceptible-Exposed-Infectious-(re)Susceptible-Vaccination) model to age- and neighborhood-specific data of COVID-19 cases, emergency department visits, and deaths in NYC from the pandemic onset in March 2020 to August 2023. We further validate the model-inference estimates using independent SARS-CoV-2 wastewater viral load data. RESULTS:The validated model-inference estimates indicate a very high infection burden-the number of infections (i.e., including undetected asymptomatic/mild infections) totaled twice the population size ( > 5 times documented case count) during the first 3.5 years. Estimated virus transmissibility increased around 3-fold, whereas estimated infection-fatality risk (IFR) decreased by >10-fold during this period. The detailed estimates also reveal highly complex variant dynamics and immune landscape, and higher infection risk during winter in NYC over the study period. CONCLUSIONS:This study provides highly detailed epidemiological estimates and identifies key transmission dynamics and drivers of SARS-CoV-2 during its first 3.5 years of circulation in a large urban center (i.e., NYC). These transmission dynamics and drivers may be relevant to other populations and inform future planning to help mitigate the public health burden of SARS-CoV-2.

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.

Objective: New York City's automated mortality syndromic surveillance system monitors temporal and spatial patterns in mortality. To describe the use of the syndromic surveillance system, we used the system to find mortality patterns for the 15 leading causes of death and for deaths from rare and reportable diseases in New York City from February 2015 through June 2020. We used results to find aberrations that indicate threats to public health.Methods: We used unobserved components models to analyze time series of mortality counts for leading causes of death, historical limits methods for rare and reportable diseases, and SaTScan for temporal-spatial cluster analysis. We obtained data on the number of deaths from the electronic death registry system maintained by the city's Bureau of Vital Statistics.Results: The mortality syndromic surveillance system detected an increase in the number of deaths from heart disease by April 1, 2020, when 75.0 deaths occurred on March 24, 2020, instead of an expected 45.8 deaths (95% upper prediction limit of 61.0) and an increase in the number of deaths from all causes on March 20, 2020, when 194.0 deaths were observed while 150.1 deaths were expected (95% upper prediction limit of 178.0). The number of deaths from all causes returned to normal the week beginning June 14, 2020, when 990.0 deaths were observed and 998.8 deaths were expected.Practice Implications: When compared with efforts from New York City to provide yearly vital statistics, the automated mortality syndromic surveillance system can provide timely mortality data with fewer resources and raise the capacity to detect anomalous increases in mortality.

We describe how the COVID-19 pandemic affected reproductive choices in New York City, the most acutely impacted area of the United States.We contrast changes in New York City with reproductive outcomes in the rest of the US.We find that births to New York City residents fell 8.4% more between March, 2020 and February 2021 than that would have been expected given trends leading up to the pandemic.Births to US-born residents of New York City fell 5.5% over the same year, triple the observed decline in the rest of the US.Births to foreign-born New York City residents fell 11.4%, twice the decline observed in the rest of the US.Reported induced abortions to New York City residents fell precipitously whereas induced abortions nation-wide rose slightly.The acute downturn and robust recovery in births in New York City maps closely with the spike in mortality and its equally rapid decline three months later.We conclude that the fear and uncertainty in the early months of the pandemic is the best explanation for the sudden, but brief drop in births in New York City.

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.

Bivalent booster vaccination data were

BACKGROUND:We assessed whether participation in Healthy Start Brooklyn's By My Side Birth Support Program-a maternal-health program providing community-based doula support during pregnancy, labor and delivery, and the early postpartum period-was associated with improved birth outcomes. By My Side takes a strength-based approach that aligns with the doula principles of respecting the client's autonomy, providing culturally appropriate care without judgment or conditions, and promoting informed decision making.METHODS:Using a matched cohort design, birth certificate records for By My Side participants from 2010 through 2017 (n = 603) were each matched to three controls who also lived in the program area (n = 1809). Controls were matched on maternal age, race/ethnicity, education level, and trimester of prenatal-care initiation, using the simple random sampling method. The sample was restricted to singleton births. The odds of preterm birth, low birthweight, and cesarean birth were estimated, using conditional logistic regression.RESULTS:By My Side participants had lower odds of having a preterm birth (5.6% vs 11.9%, P < .0001) or a low-birthweight baby (5.8% vs 9.7%, P = .0031) than controls. There was no statistically significant difference in the odds of cesarean delivery.CONCLUSION:Participation in the By My Side Birth Support Program was associated with lower odds of preterm birth and low birthweight for participants, who were predominantly Black and Hispanic. Investing in doula services is an important way to address birth inequities among higher risk populations such as birthing people of color and those living in poverty. It could also help shape a new vision of the maternal-health system, placing the needs and well-being of birthing people at the center.

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

Objective:To conduct a population-based analysis and compare life expectancy between people with HIV and the general population in New York City (NYC).Methods:We obtained the annual total number and age, sex, and race/ethnicity distributions of people with HIV from the NYC HIV registry and generated comparable numbers for the NYC general population from the Census 2000 and 2010 data using linear interpolation.Results:Life expectancy at age 20 among people with HIV increased from 38.5 years [95% confidence interval (CI): 37.4 to 39.5] in 2009 to 50.6 (95% CI: 48.5 to 52.7) in 2018, whereas it increased from 62.0 years (95% CI: 61.8 to 62.1) to 63.6 (95% CI: 63.5 to 63.7) among the NYC general population. The gap between the 2 populations narrowed from 23.5 years (95% CI: 22.4 to 24.6) in 2009 to 13.0 (95% CI: 10.9 to 15.1) in 2018. By sex and race/ethnicity, life expectancy at age 20 among people with HIV increased from 36.7 years in 2009 to 47.9 in 2018 among Black men; 37.5 to 50.5 years among Black women; 38.6 to 48.9 years among Hispanic men; 46.0 to 51.0 years among Hispanic women; 44.7 to 59.7 years among White men; and 38.0 years in 2009-2013 to 50.4 years in 2014-2018 among White women.Conclusions:Life expectancy among people with HIV improved greatly in NYC in 2009-2018, but the improvement was not equal across sex and racial/ethnic groups. The gap in life expectancy between people with HIV and the general population narrowed but remained.

The Centers for Disease Control and Prevention (CDC) and local health jurisdictions have been using HIV surveillance data to monitor mortality among people with HIV in the United States with age-standardized death rates, but the principles of age standardization have not been consistently followed, making age standardization lose its purpose—comparison over time, across jurisdictions, or by other characteristics. We review the current practices of age standardization in calculating death rates among people with HIV in the United States, discuss the principles of age standardization including those specific to the HIV population whose age distribution differs markedly from that of the US 2000 standard population, make recommendations, and report age-standardized death rates among people with HIV in New York City. When we restricted the analysis population to adults aged between 18 and 84 years in New York City, the age-standardized death rate among people with HIV decreased from 20.8 per 1000 (95% confidence interval [CI] = 19.2, 22.3) in 2013 to 17.1 per 1000 (95% CI = 15.8, 18.3) in 2017, and the age-standardized death rate among people without HIV decreased from 5.8 per 1000 in 2013 to 5.5 per 1000 in 2017.

As of September 21, 2020, the coronavirus disease 2019 (COVID-19) pandemic had resulted in 6,786,352 cases and 199,024 deaths in the United States.* Health care personnel (HCP) are essential workers at risk for exposure to patients or infectious materials (1). The impact of COVID-19 on U.S. HCP was first described using national case surveillance data in April 2020 (2). Since then, the number of reported HCP with COVID-19 has increased tenfold. This update describes demographic characteristics, underlying medical conditions, hospitalizations, and intensive care unit (ICU) admissions, stratified by vital status, among 100,570 HCP with COVID-19 reported to CDC during February 12-July 16, 2020. HCP occupation type and job setting are newly reported. HCP status was available for 571,708 (22%) of 2,633,585 cases reported to CDC. Most HCP with COVID-19 were female (79%), aged 16-44 years (57%), not hospitalized (92%), and lacked all 10 underlying medical conditions specified on the case report form† (56%). Of HCP with COVID-19, 641 died. Compared with nonfatal COVID-19 HCP cases, a higher percentage of fatal cases occurred in males (38% versus 22%), persons aged ≥65 years (44% versus 4%), non-Hispanic Asians (Asians) (20% versus 9%), non-Hispanic Blacks (Blacks) (32% versus 25%), and persons with any of the 10 underlying medical conditions specified on the case report form (92% versus 41%). From a subset of jurisdictions reporting occupation type or job setting for HCP with COVID-19, nurses were the most frequently identified single occupation type (30%), and nursing and residential care facilities were the most common job setting (67%). Ensuring access to personal protective equipment (PPE) and training, and practices such as universal use of face masks at work, wearing masks in the community, and observing social distancing remain critical strategies to protect HCP and those they serve.

New York City (NYC) was an epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States during spring 2020 (1). During March-May 2020, approximately 203,000 laboratory-confirmed COVID-19 cases were reported to the NYC Department of Health and Mental Hygiene (DOHMH). To obtain more complete data, DOHMH used supplementary information sources and relied on direct data importation and matching of patient identifiers for data on hospitalization status, the occurrence of death, race/ethnicity, and presence of underlying medical conditions. The highest rates of cases, hospitalizations, and deaths were concentrated in communities of color, high-poverty areas, and among persons aged ≥75 years or with underlying conditions. The crude fatality rate was 9.2% overall and 32.1% among hospitalized patients. Using these data to prevent additional infections among NYC residents during subsequent waves of the pandemic, particularly among those at highest risk for hospitalization and death, is critical. Mitigating COVID-19 transmission among vulnerable groups at high risk for hospitalization and death is an urgent priority. Similar to NYC, other jurisdictions might find the use of supplementary information sources valuable in their efforts to prevent COVID-19 infections.

During March 1-May 16, 2020, 191,392 laboratory-confirmed COVID-19 cases were diagnosed and reported and 20,141 confirmed and probable COVID-19 deaths occurred among New York City (NYC) residents. We applied a network model-inference system developed to support the City's pandemic response to estimate underlying SARS-CoV-2 infection rates. Based on these estimates, we further estimated the infection fatality risk (IFR) for 5 age groups (i.e. <25, 25-44, 45-64, 65-74, and 75+ years) and all ages overall, during March 1-May 16, 2020. We estimated an overall IFR of 1.45% (95% Credible Interval: 1.09-1.87%) in NYC. In particular, weekly IFR was estimated as high as 6.1% for 65-74 year-olds and 17.0% for 75+ year-olds. These results are based on more complete ascertainment of COVID-19-related deaths in NYC and thus likely more accurately reflect the true, higher burden of death due to COVID-19 than previously reported elsewhere. It is thus crucial that officials account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the pandemic unfolds.

AbstractBackgroundAs the COVID-19 pandemic continues to unfold, the infection fatality risk (IFR, i.e. risk of death among all infections including asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here we estimate the IFR of COVID-19 in New York City (NYC), the first epidemic center in the United States where the IFR remains unclear.MethodsWe developed a meta-population network model-inference system to estimate underlying SARS-CoV-2 infection rates in NYC during the 2020 spring pandemic wave using case, mortality, and mobility data. Based on these estimates, we further estimated the IFR for all ages overall and for 5 age groups (i.e. <25, 25-44, 45-64, 65-74, and 75+ years) separately, during March 1 – June 6, 2020 (i.e., before NYC began its phased reopening).FindingsDuring March 1 – June 6, 2020, 205,639 laboratory-confirmed COVID-19 cases were diagnosed and 21,447 confirmed and probable COVID-19 deaths occurred among NYC residents. We estimated an overall IFR of 1.39% (95% Credible Interval: 1.04-1.77%) in NYC. Estimated IFR for the two oldest age groups (65-74 and 75+ years) was much higher than the younger age groups and about double estimates reported for elsewhere. In particular, weekly IFR was estimated as high as 6.7% for 65-74 year-olds and 19.1% for 75+ year-olds.InterpretationThese results are based on more complete ascertainment of COVID-19-associated deaths in NYC and thus likely more accurately reflect the true, higher burden of death due to COVID-19 than previously reported elsewhere.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), was first identified in December 2019 in Wuhan, China, and has since spread worldwide. On March 11, 2020, the World Health Organization declared COVID-19 a pandemic (1). That same day, the first confirmed COVID-19-associated fatality occurred in New York City (NYC). To identify confirmed COVID-19-associated deaths, defined as those occurring in persons with laboratory-confirmed SARS-CoV-2 infection, on March 13, 2020, the New York City Department of Health and Mental Hygiene (DOHMH) initiated a daily match between all deaths reported to the DOHMH electronic vital registry system (eVital) (2) and laboratory-confirmed cases of COVID-19. Deaths for which COVID-19, SARS-CoV-2, or an equivalent term is listed on the death certificate as an immediate, underlying, or contributing cause of death, but that do not have laboratory-confirmation of COVID-19 are classified as probable COVID-19-associated deaths. As of May 2, a total of 13,831 laboratory-confirmed COVID-19-associated deaths, and 5,048 probable COVID-19-associated deaths were recorded in NYC (3). Counting only confirmed or probable COVID-19-associated deaths, however, likely underestimates the number of deaths attributable to the pandemic. The counting of confirmed and probable COVID-19-associated deaths might not include deaths among persons with SARS-CoV-2 infection who did not access diagnostic testing, tested falsely negative, or became infected after testing negative, died outside of a health care setting, or for whom COVID-19 was not suspected by a health care provider as a cause of death. The counting of confirmed and probable COVID-19-associated deaths also does not include deaths that are not directly associated with SARS-CoV-2 infection. The objective of this report is to provide an estimate of all-cause excess deaths that have occurred in NYC in the setting of widespread community transmission of SARS-CoV-2. Excess deaths refer to the number of deaths above expected seasonal baseline levels, regardless of the reported cause of death. Estimation of all-cause excess deaths is used as a nonspecific measure of the severity or impact of pandemics (4) and public health emergencies (5). Reporting of excess deaths might provide a more accurate measure of the impact of the pandemic.

Objectives. To assess if historical redlining, the US government’s 1930s racially discriminatory grading of neighborhoods’ mortgage credit-worthiness, implemented via the federally sponsored Home Owners’ Loan Corporation (HOLC) color-coded maps, is associated with contemporary risk of preterm birth (< 37 weeks gestation). Methods. We analyzed 2013–2017 birth certificate data for all singleton births in New York City (n = 528 096) linked by maternal residence at time of birth to (1) HOLC grade and (2) current census tract social characteristics. Results. The proportion of preterm births ranged from 5.0% in grade A (“best”—green) to 7.3% in grade D (“hazardous”—red). The odds ratio for HOLC grade D versus A equaled 1.6 and remained significant (1.2; P < .05) in multilevel models adjusted for maternal sociodemographic characteristics and current census tract poverty, but was 1.07 (95% confidence interval = 0.92, 1.20) after adjustment for current census tract racialized economic segregation. Conclusions. Historical redlining may be a structural determinant of present-day risk of preterm birth. Public Health Implications. Policies for fair housing, economic development, and health equity should consider historical redlining’s impacts on present-day residential segregation and health outcomes.

BACKGROUND:As the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear. METHODS:In this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening). FINDINGS:During the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older. INTERPRETATION:Our results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds. FUNDING:National Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.

BACKGROUND:Severe stressors can induce preterm birth (PTB; gestation <37 weeks), with such stressors including social and economic threats, interpersonal violence, hate crimes and severe sociopolitical stressors (ie, arising from political leaders' threatening rhetoric or from political legislation). We analysed temporal changes in risk of PTB among immigrant, Hispanic and Muslim populations targeted in the US 2016 presidential election and its aftermath.METHODS:Trend analysis of all singleton births in New York City from 1 September 2015 to 31 August 2017 (n=230 105).RESULTS:Comparing the period before the US presidential nomination (1 September 2015 to 31 July 2016) to the post-inauguration period (1 January 2017 to 31 August 2017), the overall PTB rate increased from 7.0% to 7.3% (relative risk (RR): 1.04; 95% CI 1.00 to 1.07). Among Hispanic women, the highest post-inauguration versus pre-inauguration increase occurred among foreign-born Hispanic women with Mexican or Central American ancestry (RR: 1.15; 95% CI 1.01 to 1.31). The post-inauguration versus pre-inauguration PTB rate also was higher for women from the Middle East/North Africa and from the travel ban countries, although non-significant due to the small number of events.CONCLUSION:Severe sociopolitical stressors may contribute to increases in the risk of PTB among targeted populations.