Descriptive study of causes of death and COVID-19-associated morbidities from the New York City electronic death record: first wave of the pandemic March-July 2020.

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.

Exploring spatio-temporal impact of COVID-19 on citywide taxi demand: A case study of New York City.

Coronavirus disease 2019 (COVID-19) has brought dramatic changes in our daily life, especially in human mobility since 2020. As the major component of the integrated transport system in most cities, taxi trips represent a large portion of residents' urban mobility. Thus, quantifying the impacts of COVID-19 on city-wide taxi demand can help to better understand the reshaped travel patterns, optimize public-transport operational strategies, and gather emergency experience under the pressure of this pandemic. To achieve the objectives, the Geographically and Temporally Weighted Regression (GTWR) model is used to analyze the impact mechanism of COVID-19 on taxi demand in this study. City-wide taxi trip data from August 1st, 2020 to July 31st, 2021 in New York City was collected as model's dependent variables, and COVID-19 case rate, population density, road density, station density, points of interest (POI) were selected as the independent variables. By comparing GTWR model with traditional ordinary least square (OLS) model, temporally weighted regression model (TWR) and geographically weighted regression (GWR) model, a significantly better goodness of fit on spatial-temporal taxi data was observed for GTWR. Furthermore, temporal analysis, spatial analysis and the epidemic marginal effect were developed on the GTWR model results. The conclusions of this research are shown as follows: (1) The virus and health care become the major restraining and stimulative factors of taxi demand in post epidemic era. (2) The restraining level of COVID-19 on taxi demand is higher in cold weather. (3) The restraining level of COVID-19 on taxi demand is severely influenced by the curfew policy. (4) Although this virus decreases taxi demand in most of time and places, it can still increase taxi demand in some specific time and places. (5) Along with COVID-19, sports facilities and tourism become obstacles on increasing taxi demand in most of places and time in post epidemic era. The findings can provide useful insights for policymakers and stakeholders to improve the taxi operational efficiency during the remainder of the COVID-19 pandemic.

Hospital segregation, critical care strain, and inpatient mortality during the COVID-19 pandemic in New York City.

BACKGROUND: Hospital segregation by race, ethnicity, and health insurance coverage is prevalent, with some hospitals providing a disproportionate share of undercompensated care. We assessed whether New York City (NYC) hospitals serving a higher proportion of Medicaid and uninsured patients pre-pandemic experienced greater critical care strain during the first wave of the COVID-19 pandemic, and whether this greater strain was associated with higher rates of in-hospital mortality. METHODS: In a retrospective analysis of all-payer NYC hospital discharge data, we examined changes in admissions, stratified by use of intensive care unit (ICU), from the baseline period in early 2020 to the first COVID-19 wave across hospital quartiles (265,329 admissions), and crude and risk-adjusted inpatient mortality rates, also stratified by ICU use, in the first COVID wave across hospital quartiles (23,032 inpatient deaths), based on the proportion of Medicaid or uninsured admissions from 2017-2019 (quartile 1 lowest to 4 highest). Logistic regressions were used to assess the cross-sectional association between ICU strain, defined as ICU volume in excess of the baseline average, and patient-level mortality. RESULTS: ICU admissions in the first COVID-19 wave were 84%, 97%, 108%, and 123% of the baseline levels by hospital quartile 1-4, respectively. The risk-adjusted mortality rates for ICU admissions were 36.4 (CI = 34.7,38.2), 43.6 (CI = 41.5,45.8), 45.9 (CI = 43.8,48.1), and 45.7 (CI = 43.6,48.0) per 100 admissions, and those for non-ICU admissions were 8.6 (CI = 8.3,9.0), 10.9 (CI = 10.6,11.3), 12.6 (CI = 12.1,13.0), and 12.1 (CI = 11.6,12.7) per 100 admissions by hospital quartile 1-4, respectively. Compared with the reference group of 100% or less of the baseline weekly average, ICU admissions on a day for which the ICU volume was 101-150%, 151-200%, and > 200% of the baseline weekly average had odds ratios of 1.17 (95% CI = 1.10, 1.26), 2.63 (95% CI = 2.31, 3.00), and 3.26 (95% CI = 2.82, 3.78) for inpatient mortality, and non-ICU admissions on a day for which the ICU volume was 101-150%, 151-200%, and > 200% of the baseline weekly average had odds ratios of 1.28 (95% CI = 1.22, 1.34), 2.60 (95% CI = 2.40, 2.82), and 3.44 (95% CI = 3.11, 3.63) for inpatient mortality. CONCLUSIONS: Our findings are consistent with hospital segregation as a potential driver of COVID-related mortality inequities and highlight the need to desegregate health care to address structural racism, advance health equity, and improve pandemic resiliency.

Immediate Injury Deaths Related to the Remnants From Hurricane Ida in New York City, September 1-2, 2021.

The remnants from Hurricane Ida in September 2021 caused unprecedented rainfall and inland flooding in New York City (NYC) and resulted in many immediate deaths. We reviewed death records (electronic death certificates and medical examiner reports) to systematically document the circumstances of death and demographics of decedents to inform injury prevention and climate adaptation actions for future extreme precipitation events. There were 14 Ida-related injury deaths in NYC, of which 13 (93%) were directly caused by Ida, and 1 (7%) was indirectly related. Most decedents were Asian (71%) and foreign-born (71%). The most common circumstance of death was drowning in unregulated basement apartments (71%). Themes that emerged from the death records review included the suddenness of flooding, inadequate exits, nighttime risks, and multiple household members were sometimes affected. These deaths reflect interacting housing and climate crises, and their disproportionate impact on disadvantaged populations needing safe and affordable housing. Climate adaptation actions, such as improving stormwater management infrastructure, informing residents about flood risk, implementing Federal Emergency Management Agency recommendations to make basements safer, and expanding emergency notification measures can mitigate risk. As climate change increases extreme precipitation events, multi-layered efforts are needed to keep residents safe.

The privilege of working from home and health disparities during the covid-19 pandemic in major American cities.

Working from home (WFH) has been adopted as a key mitigation strategy in the COVID-19 pandemic; yet few research has studied its impact on pandemic outcomes. Using multiple sources of data including cellphone data and online survey during the pandemic, this study investigates the effect of WFH on intra-city health disparities during the COVID-19 pandemic in American cities. Pandemic data for zip code tabulation areas and cellphone mobility data for census block groups in New York City (NYC), Chicago, and Philadelphia are converted to census tract level, which are then merged with 2019 census data. WFH is measured with the proportion of workers who potentially can telework based on employment composition in census tracts and percentages of jobs in each industry that actually WFH during the pandemic. Results show that while infection and death rates are higher in NYC, intra-city disparities in pandemic outcomes are more pronounced in Philadelphia. Poisson regressions show a negative association between WFH and COVID-19 infection and death rates in NYC and Chicago, which is weakened by increased time spent at home during the pandemic and in minority neighborhoods (in NYC). In Philadelphia, WFH is barely relevant for infection rates but has a marginally positive association with death rates, which is also moderated by the time spent at home. This study demonstrates the relative effectiveness of WFH in mitigating pandemic outcomes and underscores the intersectionality between WFH and race/ethnicity and resident behaviors. It provides important policy implications for future pandemic mitigation.

Longitudinal Associations of Food Security with Health and Dietary Factors among Food FARMacy Participants during COVID-19 in New York City.

In cross-sectional studies, food insecurity is associated with adverse health and dietary outcomes. Whether self-reported health and dietary outcomes change in response to improvements in food security has not been examined. We sought to examine how increases in food security are related to changes in health and dietary factors. In this longitudinal, observational study, we included adult participants in a clinical-community emergency food assistance program in New York City from July 2020 to November 2021. Program staff measured food security with a validated six-item measure at program enrollment and six-month re-enrollment. Participants self-reported health and dietary factors (vegetable, fruit, juice, and sugar-sweetened beverage (SSB) consumption frequency). We used multivariable regression to examine associations between change in food security with change in health and dietary factors over six months. Among 310 participants, the mean food security score improved by 1.7 ± 2.3 points over six months. In unadjusted models, each point improvement in food security was associated with increased vegetable (ß = 0.10 times; 95% CI: 0.05-0.15); fruit (ß = 0.08 times; 95% CI: 0.03-0.14); and juice (ß = 0.10 times; 95% CI: 0.05-0.15) consumption. In adjusted models, results remained significant for vegetable and fruit consumption, but not juice. Change in food security was not associated with change in health or SSB outcomes. In this cohort during COVID-19, improved food security was associated with improved vegetable and fruit consumption. Randomized trials that examine the effectiveness of clinical-community partnerships focused on improving food security and nutrition are warranted.

Comparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City.

BACKGROUND: Area-level social determinants of health (SDOH) based on patients' ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individual SDOH measures, specifically individual educational attainment, is unknown. METHODS: This is a retrospective study using data from the Mount Sinai BioMe Biobank. We included participants that completed a validated questionnaire on educational attainment and had home addresses in New York City. ZIP code-level education was derived from the American Community Survey matched for the participant's gender and race/ethnicity. We tested several algorithms to predict individual educational attainment from routinely collected clinical and demographic data. To evaluate how using different measures of educational attainment will impact model performance, we developed three distinct models for predicting cardiovascular (CVD) hospitalization. Educational attainment was imputed into models as either survey-derived, ZIP code-derived, or ML-predicted educational attainment. RESULTS: A total of 20,805 participants met inclusion criteria. Concordance between survey and ZIP code-derived education was 47%, while the concordance between survey and ML model-predicted education was 67%. A total of 13,715 patients from the cohort were included into our CVD hospitalization prediction models, of which 1,538 (11.2%) had a history of CVD hospitalization. The AUROC of the model predicting CVD hospitalization using survey-derived education was significantly higher than the model using ZIP code-level education (0.77 versus 0.72; p < 0.001) and the model using ML model-predicted education (0.77 versus 0.75; p < 0.001). The AUROC for the model using ML model-predicted education was also significantly higher than that using ZIP code-level education (p = 0.003). CONCLUSION: The concordance of survey and ZIP code-level educational attainment in NYC was low. As expected, the model utilizing survey-derived education achieved the highest performance. The model incorporating our ML model-predicted education outperformed the model relying on ZIP code-derived education. Implementing ML techniques can improve the accuracy of SDOH data and consequently increase the predictive performance of outcome models.

Evaluating completion rates of COVID-19 contact tracing surveys in New York City.

IMPORTANCE: Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs. OBJECTIVE: To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021. METHODS: We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used. RESULTS: The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age < = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age < = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%. CONCLUSION: These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.

JYNNEOS™ effectiveness as post-exposure prophylaxis against mpox: Challenges using real-world outbreak data.

BACKGROUND: JYNNEOSTM vaccine has been used as post-exposure prophylaxis (PEP) during a mpox outbreak in New York City (NYC). Data on effectiveness are limited. METHODS: Effectiveness of a single dose of JYNNEOSTM vaccine administered subcutaneously ≤ 14 days as PEP for preventing mpox disease was assessed among individuals exposed to case-patients from May 22, 2022-August 24, 2022. Individuals were evaluated for mpox through 21 days post-exposure. An observational study was conducted emulating a sequence of nested "target" randomized trials starting each day after exposure. Results were adjusted for exposure risk and race/ethnicity. Analyses were conducted separately based on last (PEPL) and first (PEPF) exposure date. We evaluated the potential to overestimate PEP effectiveness when using conventional analytic methods due to exposed individuals developing illness before they can obtain PEP (immortal time bias) compared to the target trial. RESULTS: Median time from last exposure to symptom onset (incubation period) among cases that did not receive PEPL was 7 days (range 1-16). Time to PEPL receipt was 7 days (range 0-14). Among 549 individuals, adjusted PEPL and PEPF effectiveness was 19 % (95 % Confidence Interval [CI], -54 % to 57 %) and -7% (95 % CI, -144 % to 53 %) using the target trial emulation, respectively, and 78 % (95 % CI, 50 % to 91 %) and 73 % (95 % CI, 31 % to 91 %) using conventional analysis. CONCLUSIONS: Determining PEP effectiveness using real-world data during an outbreak is challenging. Time to PEP in NYC coupled with the observed incubation period resulted in overestimated PEP effectiveness using a conventional method. The target trial emulation, while yielding wide confidence intervals due to small sample size, avoided immortal time bias. While results from these evaluations cannot be used as reliable estimates of PEP effectiveness, we present important methodologic considerations for future evaluations.

Who enrolls and why? Examining center-specific underlying patterns behind enrollment: a New York City-based traumatic brain injury model systems study.

BACKGROUND: To elucidate the sociodemographic and study factors involved in enrollment in the Traumatic Brain Injury Model System (TBIMS) database, this study examined the effect of a variety of variables on enrollment at a local TBIMS center. METHODS: A sample of 654 individuals from the local TBIMS center was studied examining enrollment by age, gender, race, ethnicity, homelessness status at date of injury, history of homelessness, health insurance status, presence of social support, primary language, consenting in hospital or after discharge, and the need for an interpreter. Binary logistic regression was conducted to identify variables that predict center-based enrollment into TBIMS. RESULTS: Results demonstrated that older age was associated with decreasing enrollment (OR = 0.99, p = 0.01), needing an interpreter made enrollment less likely (OR = 0.33, p < 0.01), being primarily Spanish speaking predicted enrollment (OR = 3.20, p = 0.02), Hispanic ethnicity predicted enrollment (OR = 7.31, p = 0.03), and approaching individuals in the hospital predicted enrollment (OR = 6.94, p < 0.01). Here, OR denotes the odds ratio estimate from a logistic regression model and P denotes the corresponding p-value. CONCLUSIONS: These results can be useful in driving enrollment strategies at this center for other similar TBI research, and to contribute a representative TBI sample to the national database.

Impact of the Coronavirus Disease 2019 Pandemic on Utilization of Emergency Medical Services in New York City.

Background: This study evaluates trends in the utilization of emergency medical services (EMS) in New York City, the "epicenter" of the first "wave" of the coronavirus pandemic. We hypothesize that EMS call volumes decreased overall in New York City during the first year of the pandemic, specifically with respect to trauma/injury calls. Contrarily, we posit that calls for "sick" events increased given pervasive fear of virus transmission. Materials and Methods: Retrospective New York City EMS calls data (January 1, 2019 to December 31, 2020) were obtained from the NYC Open Data/EMS Incident Dispatch database. Total EMS calls, trauma/injury calls, and "sick" event calls were collected for New York City and for all five boroughs. Census data for each borough were used to weigh daily EMS calls per 100,000 individuals. Mann-Whitney U tests were used to compare pre-pandemic (2019 to March 2020) versus pandemic (April 2020 to December 2020) EMS call volumes, p = 0.05. Results: Median daily EMS calls per 100,000 individuals decreased 21.6% at the start of the pandemic across New York City (pre-pandemic, 3,262 calls; pandemic, 2,556 calls; p < 0.001) and similarly decreased when stratified by borough (all, p < 0.001). Median daily trauma/injury and sick event calls per 100,000 also decreased in New York City and the five boroughs from pre-pandemic to pandemic time periods (all, p < 0.001). Discussion and Conclusions: These data reflect an unprecedented window into EMS utilization during an infectious disease pandemic. As decreased EMS utilization for multiple conditions likely reflects delayed or impeded access to care, utilization data have important implications for provision of acute care services during possible future disruptions related to the pandemic.

"No sufro, estoy bien/I am not suffering, so I am doing OK": A mixed method exploration of individual and network-level factors and Type 2 Diabetes Mellitus (T2DM) among Mexican American adults in New York City.

INTRODUCTION: The prevalence of type 2 Diabetes Mellitus (T2DM) is 2-3 times greater among Mexican Americans than non-Latino whites, and Mexican Americans are more likely to develop T2DM at younger ages and experience higher rates of complications. Social networks might play a crucial role in both T2DM etiology and management through social support, access to resources, social engagement, and health behavioral norms. OBJECTIVE: To quantitatively identify the social network features associated with glycated hemoglobin (HbA1c) in a community sample of Mexican immigrants residing in New York City, and to explore the extent to which these quantitative findings converge with qualitative narratives of their lived experiences. METHODS: This study used a convergent mixed methods design. To collect personal network data, we used EgoWeb, and obtained 1,400 personal network ties from 81 participants. HbA1c readings were collected using dried blood spots and categorized according to the laboratory criteria of the American Diabetes Association. Additional survey data were collected using Qualtrics software. To investigate the significance of the network-level factors after accounting for the socioeconomic and demographic individual-level factors that the literature indicates to be associated with T2DM, we used a multiple regression model on quantitative data sources. For the qualitative portion of the study, we selected a subset of individuals who participated in the quantitative portion, which represented 500 personal network ties from 25 participants. We conducted in-depth interviews guided by the visualization of these ties to explore who was helpful or difficult in managing their health and health behaviors. RESULTS: Individual-level indicators associated with lower HbA1c scores were body mass index (ß = -0.07, p<0.05), and healthy eating index scores (ß = -0.03, p<0.02). The network-level predictor associated with higher HbA1c levels was the percentage of diabetic alters in the network (ß = 0.08, p <0.001, with a 25% increase in the percentages associated 2.0 change in HbA1c levels. The qualitative data highlighted that most of the diabetes-related information diffused through the social networks of our participants was related to dietary practices, such as reducing sugar and red meat consumption, eating out less, and reducing portion sizes. Notably, even among those with elevated levels and diabetes-related health complications, HbA1c was not considered a part of the lay descriptions of good health since they were not "suffering." Participants regarded doctors as the ultimate authority in diabetes care, even if they had supportive members in their personal networks. CONCLUSION: Our study provides quantitative evidence for the significant role of diabetic network members in the etiology and management of T2DM among Mexican Americans. Our qualitative findings suggest important ley terms for T2DM management and the importance of physicians, which could be included in in future social networks studies seeking to diffuse diabetes-related health information for T2DM prevention and management efforts in this population.

Up-to-Date Colonoscopy Use in Asian and Hispanic Subgroups in New York City, 2003-2016.

BACKGROUND: Colorectal cancer screening uptake in the United States overall has increased, but racial/ethnic disparities persist and data on colonoscopy uptake by racial/ethnic subgroups are lacking. We sought to better characterize these trends and to identify predictors of colonoscopy uptake, particularly among Asian and Hispanic subgroups. STUDY: We used data from the New York City Community Health Survey to generate estimates of up-to-date colonoscopy use in Asian and Hispanic subgroups across 6 time periods spanning 2003-2016. For each subgroup, we calculated the percent change in colonoscopy uptake over the study period and the difference in uptake compared to non-Hispanic Whites in 2015-2016. We also used multivariable logistic regression to identify predictors of colonoscopy uptake. RESULTS: All racial and ethnic subgroups with reliable estimates saw a net increase in colonoscopy uptake between 2003 and 2016. In 2015-2016, compared with non-Hispanic Whites, Puerto Ricans, Dominicans, and Central/South Americans had higher colonoscopy uptake, whereas Chinese, Asian Indians, and Mexicans had lower uptake. On multivariable analysis, age, marital status, insurance status, primary care provider, receipt of flu vaccine, frequency of exercise, and smoking status were the most consistent predictors of colonoscopy uptake (≥4 time periods). CONCLUSIONS: We found significant variation in colonoscopy uptake among Asian and Hispanic subgroups. We also identified numerous demographic, socioeconomic, and health-related predictors of colonoscopy uptake. These findings highlight the importance of examining health disparities through the lens of disaggregated racial/ethnic subgroups and have the potential to inform future public health interventions.

Newly Acquired Burnout During the Coronavirus Disease 2019 (COVID-19) Pandemic: A Retrospective Cohort Study on the Experiences of New York State Primary Care Clinicians.

The well-being of primary care clinicians represents an area of increasing interest amid concerns that the COVID-19 pandemic may have exacerbated already high prevalence rates of clinician burnout. This retrospective cohort study was designed to identify demographic, clinical, and work-specific factors that may have contributed to newly acquired burnout after the onset of the COVID-19 pandemic. An anonymous web-based questionnaire distributed in August 2020 to New York State (NYS) primary care clinicians, via email outreach and newsletters, produced 1,499 NYS primary care clinician survey respondents. Burnout assessment was measured pre-pandemic and early in the pandemic using a validated single-item question with a 5-point scale ranging from (1) enjoy work to (5) completely burned out. Demographic and work factors were assessed via the self-reporting questionnaire. Thirty percent of 1,499 survey respondents reported newly acquired burnout during the early pandemic period. This was more often reported by clinicians who were women, were younger than 56 years old, had adult dependents, practiced in New York City, had dual roles (patient care and administration), and were employees. Lack of control in the workplace prior to the pandemic was predictive of burnout early in the pandemic, while work control changes experienced following the pandemic were associated with newly acquired burnout. Low response rate and potential recall bias represent limitations. These findings demonstrate that reporting of burnout increased among primary care clinicians during the pandemic, partially due to varied and numerous work environment and systemic factors.

Acute Appendicitis in the Epicenter of the COVID-19 Pandemic: A New York City Single-Center Experience.

BACKGROUND: Appendectomy is the gold standard for simple appendicitis. During the coronavirus-19 pandemic, it was estimated that appendectomies in the United States decreased by 24%. We aimed to describe trends in acute appendicitis management at a center located in one of the largest epicenters of the pandemic. METHODS: This is a retrospective cohort study in a single institution located in Queens, New York, of patients who presented with acute appendicitis. A pre-COVID time period, March-June 2019, was compared to peak-COVID, March-June 2020, and late-COVID, March-June 2021. RESULTS: Of the 382 patients admitted with appendicitis during the time periods, 164 were admitted pre-COVID. Appendicitis presentations decreased by 44% during peak-COVID and 23% in late-COVID. Patients were younger during peak-COVID compared to pre-COVID (39 vs 34 years old, P = .036). Incidence of complicated appendicitis in pre-, peak-, and late-COVID was equivalent (41% vs 46% vs 45%) and operative management was similar (85% vs 76% vs 79%). Non-operative patients had shorter lengths of stay (pre- vs peak-COVID: 4.6 vs 2.9 days, P = .006). Readmission rates were similar between the cohorts across time periods. CONCLUSIONS: During peak-COVID, there was a significant decrease in presentation of acute appendicitis but clinical presentation and outcomes remained similar between the cohorts. Patients who were managed non-operatively may be discharged earlier without increased rates of readmissions.

Self-reported Cardiovascular Disease in Career Firefighters With and Without World Trade Center Exposure.

OBJECTIVE: To assess the effect of World Trade Center (WTC) exposure on cardiovascular disease (CVD) in career firefighters. Methods: Firefighters from four US cities completed health questionnaires that provide information about demographics, CVD diagnoses, and CVD risk factors. Firefighters were also compared with respondents of the 2019 National Health Interview Survey. Results: Greater WTC exposure was positively associated with combined coronary artery disease, myocardial infarction, and angina (termed "CAD") when comparing WTC-exposed with non-WTC-exposed firefighters. Compared with the National Health Interview Survey population, firefighters had lower odds of CAD and stroke. Conclusions: An occupationally appropriate comparison is important to mitigate potential bias from the healthy worker effect. While the risk of CVD in WTC-exposed and non-WTC-exposed firefighters was significantly lower than a general US population, we observed an exposure gradient where greater WTC exposure was associated with greater odds of CVD.

Factors Associated With COVID-19 Vaccine Hesitancy in Rheumatology Outpatients in New York City.

OBJECTIVE: The aim of this study was to measure COVID-19 vaccine hesitancy among rheumatology outpatients from an early COVID-19 "hotspot" during the initial period of vaccine availability. METHODS: In March 2021, a Web-based survey was sent to 7505 adults seen at a Rheumatology Division in New York City. We evaluated characteristics associated with 3 categories of COVID-19 vaccination status: declined, undecided, and willing/already received. We used multinomial logistic regression models to calculate relative risk ratios assessing predictors of vaccination status. RESULTS: Among 2384 (32%) respondents (80% female, 87% White, 59% with systemic rheumatic disease), 2240 (94.0%) were willing/already received COVID-19 vaccination, 88 (3.7%) were undecided, and 56 (2.3%) declined. Compared with those willing/already vaccinated, those declining or undecided were younger, more likely identified as Black or Hispanic/Latinx, and had lower household income and educational attainment. Immunosuppressive medication use did not differ among groups. After multivariable adjustment, every 1-year increase in age was associated with a 0.96 lower relative risk of declining or being undecided versus willing/already vaccinated. Respondents identifying as Black versus White had a higher relative risk ratio of being undecided (4.29 [95% confidence interval, 1.96-9.36]), as did those identifying as Hispanic/Latinx versus non-Hispanic/non-Latinx (2.81 [95% confidence interval, 1.29-6.09]). Those declining vaccination were least likely to believe in general vaccine importance or the safety and efficacy of the COVID-19 vaccine. CONCLUSIONS: Among rheumatology patients in New York City with and without systemic rheumatic disease, COVID-19 vaccine uptake was high after its initial availability. Sociodemographic but not medication-related factors were associated with vaccine hesitancy; these findings can inform future rheumatology vaccination programs.

Five cases of unintentional exposure to BZO-4en-POXIZID among nightclub attendees in New York City.

A new class of synthetic cannabinoids called OXIZIDs has emerged in recent years. This class consists of compounds with oxindole cores and hydrazide/hydrazone linker moieties and has often been described as being designed to circumvent a Chinese class-wide ban that was effective as of 1 July 2021. However, through hair testing of nightclub attendees in New York City-a high-risk population for recreational drug use-we have evidence suggesting exposures to an OXIZID called BZO-4en-POXIZID (4en-pentyl MDA-19) prior to the effective ban. Through analysis of 6 cm segmented hair samples from attendees collected in 2021, we detected five cases of exposure. Specifically, we detected a cluster of three cases based on hair samples collected on 20 June 2021, and then two additional cases from samples collected on 16 July 2021. Four of these hair samples were long enough to analyze two 6 cm hair segments (representing approximately two 6-month timeframes) and three of four of these cases tested positive for repeated exposure (for an estimated exposure over 6 months prior to hair collection). All cases included young adult females reporting past-year cannabis use but all tested negative for tetrahydrocannabinol exposure. Three cases also reported past-year use of cocaine, ecstasy, and/or ketamine, and four cases tested positive for exposure to cocaine, 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), methamphetamine and/or eutylone. These subjects were exposed to BZO-4en-POXIZID-likely as an adulterant in other drugs, and these cases are among the first documented cases which occurred approximately half a year before the Chinese legislative ban.

Impact of COVID-19 on HPV Vaccination Rates in New York City and Long Island.

BACKGROUND: In the United States, uptake of human papillomavirus (HPV) vaccination has been exceptionally low as compared with other vaccines. During the coronavirus disease (COVID-19) pandemic, routine vaccinations were deferred or delayed, further exacerbating HPV vaccine hesitancy. The specific effect of the pandemic on HPV vaccination rates in the United States has not been yet described. METHODS: We aimed to determine the percentage of children achieving full HPV vaccination (2 doses) by age 15 years and to compare prepandemic to pandemic rates of HPV vaccination at pediatric practices across our institution. A retrospective chart review was performed to compare HPV vaccination rates in the "prepandemic" and "pandemic" periods for all children 9 through 14 years of age. Additionally, peaks in COVID-19 positivity were compared with HPV vaccination rates. RESULTS: Of children 9-14 years old, 49.3% received at least 1 dose of HPV vaccine in the prepandemic period, compared with 33.5% during the pandemic ( P < 0.0001). Only 33.5% of patients received the full 2-dose series of HPV prepandemic, compared with 19.0% of patients during the pandemic ( P < 0.0001). When COVID-19 positivity rates peaked, HPV vaccination also declined. CONCLUSIONS: The issue of low HPV vaccination rates was amplified due to the COVID-19 pandemic, as illustrated by the correlation between peaks in COVID-19 positivity and low rates of HPV vaccination.

Gentrification and childhood obesity: Evidence from New York City public school students in public housing.

OBJECTIVE: The study objective was to determine the effect of gentrification on the weight outcomes of New York City public school students living in public housing. METHODS: In a prospective cohort of 19,022 New York City public school students in public housing followed during 2009-2017, weight outcomes of students living in public housing buildings in gentrified neighborhoods were compared to those living in consistently low-socioeconomic-status neighborhoods; assignment was quasi-random in each borough. RESULTS: Among the 42,182 student-year observations, gentrification did not increase weight outcomes significantly, for BMI z scores (0.037; 95% CI: -0.012 to 0.086), obesity (0.6 percentage points [pp]; 95% CI: -0.9 to 2.1), or overweight (1.3 pp; 95% CI: -0.7 to 3.2). However, heterogeneous effects by borough were found, where the gentrification in Manhattan increased students' BMI z scores by 0.19 (95% CI: 0.09-0.29), obesity by 3.4 pp (95% CI: 0.03-6.5), and overweight by 9.2 pp (95% CI: 6.3-12.1). No heterogeneity by race and ethnicity, gender, or age was found. CONCLUSIONS: With strong internal validity, this study shows that neighborhood gentrification differentially influenced children's health through obesity, based on borough of residence. Such findings could inform policies or interventions focused on subpopulations and geographies.