"The perfect storm": community worker perspectives on the impact of COVID-19 on New York City immigrants and migrant-serving organizations.

Background: Immigrants in New York City (NYC) have higher COVID-19 mortality than the general population. While migrant-serving organizations (MSOs) provide access to a breadth of services, they are disproportionately impacted by the COVID-19 pandemic due to staffing limitations, funding cuts, and resource limitations of communities served. Methods: Six focus-group discussions were conducted to explore the experiences of MSOs in NYC during the COVID-19 pandemic from November 2021 to March 2022. Study participants csomprised a subsample of survey respondents from a larger study identified via lists of MSOs. Results: Twenty-seven organizational representatives from 11 MSOs across NYC participated in the discussions. In addition to providing information on communities served, services offered, and organizational characteristics, the following themes emerged from the convenings: mental health challenges and resources needed for immigrants; immigration-related challenges; factors exacerbating hardships for immigrants during COVID-19; interorganizational collaborations and partnerships; policy change; and needs/requests of MSOs. MSOs provide a wide range of services as non-profit organizations and use interorganizational collaboration to improve service delivery. The proximity of MSOs to immigrant communities helps providers understand the needs of immigrants relating to the COVID-19 pandemic and factors that shape telehealth services. Conclusion: MSOs are important providers and advocates for immigration policy in the US given their relationship with the populations they serve. These findings have implications for how to support MSOs that serve immigrants in NYC. Strategies to achieve this include timelier availability and exchange of information, policies, and research as well as strengthening the experience-based advocacy of these groups.

Maternal Characteristics and Rates of Unexpected Complications in Term Newborns by Hospital.

Importance: The Joint Commission Unexpected Complications in Term Newborns measure characterizes newborn morbidity potentially associated with quality of labor and delivery care. Infant exclusions isolate relatively low-risk births, but unexpected newborn complications (UNCs) are not adjusted for maternal factors that may be associated with outcomes independently of hospital quality. Objective: To investigate the association between maternal characteristics and hospital UNC rates. Design, Setting, and Participants: This cohort study was conducted using linked 2016 to 2018 New York City birth and hospital discharge datasets among 254 259 neonates at low risk (singleton, ≥37 weeks, birthweight ≥2500 g, and without preexisting fetal conditions) at 39 hospitals. Logistic regression was used to calculate unadjusted hospital-specific UNC rates and replicated analyses adjusting for maternal covariates. Hospitals were categorized into UNC quintiles; changes in quintile ranking with maternal adjustment were examined. Data analyses were performed from December 2022 to July 2023. Main Outcomes and Measures: UNCs were classified according to Joint Commission International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) criteria. Maternal preadmission comorbidities, obstetric factors, social characteristics, and hospital characteristics were ascertained. Results: Among 254 259 singleton births at 37 weeks or later who were at low risk (125 245 female [49.3%] and 129 014 male [50.7%]; 71 768 births [28.2%] to Hispanic, 47 226 births [18.7%] to non-Hispanic Asian, 42 682 births [16.8%] to non-Hispanic Black, and 89 845 births [35.3%] to non-Hispanic White mothers and 2738 births [1.0%] to mothers with another race or ethnicity), 148 393 births (58.4%) were covered by Medicaid and 101 633 births (40.0%) were covered by commercial insurance. The 2016 to 2018 cumulative UNC incidence in New York City hospitals was 37.1 UNCs per 1000 births. Infants of mothers with preadmission risk factors had increased UNC risk; for example, among mothers with vs without preeclampsia, there were 104.4 and 35.8 UNCs per 1000 births, respectively. Among hospitals, unadjusted UNC rates ranged from 15.6 to 215.5 UNCs per 1000 births and adjusted UNC rates ranged from 15.6 to 194.0 UNCs per 1000 births (median [IQR] change from adjustment, 1.4 [-4.7 to 1.0] UNCs/1000 births). The median (IQR) change per 1000 births for adjusted vs unadjusted rates showed that hospitals with low (<601 deliveries/year; -2.8 [-7.0 to -1.6] UNCs) to medium (601 to <954 deliveries/year; -3.9 [-7.1 to -1.9] UNCs) delivery volume, public ownership (-3.6 [-6.2 to -2.3] UNCs), or high proportions of Medicaid-insured (eg, ≥90.72%; -3.7 [-5.3 to -1.9] UNCs), Black (eg, ≥32.83%; -5.3 [-9.1 to -2.2] UNCs), or Hispanic (eg, ≥6.25%; -3.7 [-5.3 to -1.9] UNCs) patients had significantly decreased UNC rates after adjustment, while rates increased or did not change in hospitals with the highest delivery volume, private ownership, or births to predominantly White or privately insured individuals. Among all 39 hospitals, 7 hospitals (17.9%) shifted 1 quintile comparing risk-adjusted with unadjusted quintile rankings. Conclusions and Relevance: In this study, adjustment for maternal case mix was associated with small overall changes in hospital UNC rates. These changes were associated with performance assessment for some hospitals, and these results suggest that profiling on this measure should consider the implications of small changes in rates for hospitals with higher-risk obstetric populations.

Patterns and Factors Associated With Alcohol Misuse Among Young Black Men Who Have Sex With Men in New York City.

Alcohol misuse is a significant health concern among gay, bisexual, same-gender-loving, and other men who have sex with men (MSM). Yet, little is known about the severity and predictors of alcohol misuse among self-reported young Black MSM. This study aimed to identify patterns of and factors associated with alcohol misuse in a sample of young Black MSM living in New York City. Baseline data from a randomized controlled trial aimed at improving the uptake of HIV testing among 250 MSM aged 18 to 29 were analyzed. Log-binominal regression analyses were conducted to assess the association of demographic and psychosocial factors with alcohol misuse in the past year and past 3 months among young Black MSM. Overall, 33.2% and 28.0% of young Black MSM in the study experienced alcohol misuse in the past year and past 3 months, respectively. In the adjusted model, factors positively associated with past-year alcohol misuse included marijuana use, a history of drug use, and having one-two or more than two male sex partners. Likewise, participants who used marijuana and those with one-two or more than two male partners were more likely to report past 3-month alcohol misuse. No significant association was found between positive screening for depressive symptoms, chemsex, internalized homophobia, and the likelihood of having alcohol misuse. The high prevalence of alcohol misuse underscores the importance of raising awareness of alcohol misuse and designing alcohol risk reduction programs that jointly address HIV risk among young Black MSM.

Racial and ethnic disparities post-hospitalization for COVID-19: barriers to access to care for survivors of COVID-19 acute respiratory distress syndrome.

Racial and ethnic health disparities in the incidence and severity of Coronavirus Disease 2019 (COVID-19) have been observed globally and in the United States. Research has focused on transmission, hospitalization, and mortality among racial and ethnic minorities, but Long COVID-19 health disparities research is limited. This study retrospectively evaluated 195 adults who survived COVID-19 associated acute respiratory distress syndrome (C-ARDS) in New York City from March-April 2020. Among survivors, 54% met the criteria for Long COVID syndrome. Hispanic/Latinx patients, were more likely to be uninsured (p = 0.027) and were less frequently discharged to rehabilitation facilities (p < 0.001). A cross-sectional telephone survey and interview were conducted with a subset of survivors (n = 69). Among these, 11% reported a lack of follow-up primary care post-discharge and 38% had subsequent emergency room visits. Notably, 38% reported poor treatment within the health care system, with 67% attributing this to racial or ethnic bias. Thematic analysis of interviews identified four perceived challenges: decline in functional status, discrimination during hospitalization, healthcare system inequities, and non-healthcare-related structural barriers. Sources of resilience included survivorship, faith, and family support. This study highlights structural and healthcare-related barriers rooted in perceived racism and poverty as factors impacting post-COVID-19 care.

Increasing disparities in obesity and severe obesity prevalence among public elementary and middle school students in New York City, school years 2011-12 through 2019-20.

Recent national trends in the United States indicate a significant increase in childhood obesity, a major public health concern with documented physical and mental comorbidities and sociodemographic disparities. We aimed to estimate the prevalence of obesity and severe obesity among youth in New York City (NYC) before the COVID-19 pandemic and examine time trends overall and by key characteristics. We included all valid height and weight measurements of kindergarten through 8th grade public school students aged 5 to 15 from school years 2011-12 through 2019-20 (N = 1,370,890 unique students; 5,254,058 observations). Obesity and severe obesity were determined using age- and sex-specific body mass index percentiles based on the Centers for Disease Control and Prevention growth charts. Analyses were performed using multivariate logistic regression models with repeated cross-sectional observations weighted to represent the student population for each year and clustered by student and school. Among youth attending public elementary and middle schools in NYC, we estimate that 20.9% and 6.4% had obesity and severe obesity, respectively, in 2019-20. While consistent declines in prevalence were observed overall from 2011-12 to 2019-20 (2.8% relative decrease in obesity and 0.2% in severe obesity, p<0.001), increasing trends were observed among Black, Hispanic, and foreign-born students, suggesting widening disparities. Extending previous work reporting prevalence estimates in this population, nearly all groups experienced significant increases in obesity and severe obesity from 2016-17 to 2019-20 (relative change = 3.5% and 6.7%, respectively, overall; p<0.001). Yet, some of the largest increases in obesity were observed among those already bearing the greatest burden, such as Black and Hispanic students and youth living in poverty. These findings highlight the need for greater implementation of equity-centered obesity prevention efforts. Future research should consider the influence of the COVID-19 pandemic and changes in clinical guidance on childhood obesity and severe obesity in NYC.

Major Traffic Safety Reform and Road Traffic Injuries Among Low-Income New York Residents, 2009-2021.

Objectives. To evaluate the effects of a comprehensive traffic safety policy-New York City's (NYC's) 2014 Vision Zero-on the health of Medicaid enrollees. Methods. We conducted difference-in-differences analyses using individual-level New York Medicaid data to measure traffic injuries and expenditures from 2009 to 2021, comparing NYC to surrounding counties without traffic reforms (n = 65 585 568 person-years). Results. After Vision Zero, injury rates among NYC Medicaid enrollees diverged from those of surrounding counties, with a net impact of 77.5 fewer injuries per 100 000 person-years annually (95% confidence interval = -97.4, -57.6). We observed marked reductions in severe injuries (brain injury, hospitalizations) and savings of $90.8 million in Medicaid expenditures over the first 5 years. Effects were largest among Black residents. Impacts were reversed during the COVID-19 period. Conclusions. Vision Zero resulted in substantial protection for socioeconomically disadvantaged populations known to face heightened risk of injury, but the policy's effectiveness decreased during the pandemic period. Public Health Implications. Many cities have recently launched Vision Zero policies and others plan to do so. This research adds to the evidence on how and in what circumstances comprehensive traffic policies protect public health. (Am J Public Health. 2024;114(6):633-641. https://doi.org/10.2105/AJPH.2024.307617).

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.

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.

Impact of jail-based methadone or buprenorphine treatment on non-fatal opioid overdose after incarceration.

BACKGROUND: Non-fatal overdose is a leading predictor of subsequent fatal overdose. For individuals who are incarcerated, the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community. We assessed if enrollment in jail-based medications for opioid use disorder (MOUD) is associated with lower risk of non-fatal opioid overdoses after jail release among individuals with opioid use disorder (OUD). METHODS: This was a retrospective, observational cohort study of adults with OUD who were incarcerated in New York City jails and received MOUD or did not receive any MOUD (out-of-treatment) within the last three days before release to the community in 2011-2017. The outcome was the first non-fatal opioid overdose emergency department (ED) visit within 1 year of jail release during 2011-2017. Covariates included demographic, clinical, incarceration-related, and other characteristics. We performed multivariable cause-specific Cox proportional hazards regression analysis to compare the risk of non-fatal opioid overdose ED visits within 1 year after jail release between groups. RESULTS: MOUD group included 8660 individuals with 17,119 incarcerations; out-of-treatment group included 10,163 individuals with 14,263 incarcerations. Controlling for covariates and accounting for competing risks, in-jail MOUD was associated with lower non-fatal opioid overdose risk within 14 days after jail release (adjusted HR=0.49, 95% confidence interval=0.33-0.74). We found no significant differences 15-28, 29-56, or 57-365 days post-release. CONCLUSION: MOUD group had lower risk of non-fatal opioid overdose immediately after jail release. Wider implementation of MOUD in US jails could potentially reduce post-release overdoses, ED utilization, and associated healthcare costs.

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.

Impact of Neighborhood Social Cohesion and Rodent Sightings on Mental Health among Residents of New York City During the COVID-19 Pandemic.

Common mental disorders such as depression and anxiety are prevalent globally, and rates are especially high in New York City (NYC) since the COVID-19 pandemic. Neighborhood social and physical environments have been found to influence mental health. We investigated the impact of neighborhood social cohesion and neighborhood rodent sightings (as an indicator of neighborhood cleanliness) on nonspecific serious psychological distress (NSPD) status using 2020 NYC Community Health Survey data from 8781 NYC residents. Multivariable logistic regression was used to evaluate the relationships among social cohesion, rodent sightings, and NSPD adjusted for confounders and complex sampling and weighted to the NYC population. Effect measure modification of rodent sightings on the effect of social cohesion on NSPD was evaluated on the multiplicative scale by adding the interaction term to the multivariable model and, if significant, stratifying on the effect modifier, and on the additive scale using the relative excess risk due to interaction (RERI). Social cohesion was found to decrease the odds of NSPD, and rodent sightings were found to increase the odds of NSPD. We found significant evidence of effect measure modification on the multiplicative scale. In the stratified models, there was a protective effect of social cohesion against NSPD among those not reporting rodent sightings, but no effect among those reporting rodent sightings. Our findings suggest that both neighborhood social cohesion and rodent sightings impact the mental health of New Yorkers and that rodent infestations may diminish the benefit of neighborhood social cohesion.

SARS-CoV-2 infection increases long-term multiple sclerosis disease activity and all-cause mortality in an underserved inner-city population.

BACKGROUND: Although certain subsets patients with multiple sclerosis (MS), an immune-mediated disorder, are at higher risk of worse acute COVID-19 outcomes compared to the general population, it is not clear whether SARS-CoV-2 infection impacts long-term outcomes compared with MS patients without COVID-19 infection. OBJECTIVES: This study investigated MS disease activity and mortality 3.5 years post SARS-CoV-2 infection and compared with MS patients without COVID-19. METHODS: This retrospective study evaluated 1,633 patients with MS in the Montefiore Health System in the Bronx from January 2016 to July 2023. This health system serves a large minority population and was an epicenter for the early pandemic and subsequent surges of infection. Positive SARS-CoV-2 infection was determined by a positive polymerase-chain-reaction test. Primary outcomes were all-cause mortality, and optic neuritis post SARS-CoV-2 infection. Secondary outcomes included change in disease-modifying therapy (DMT), treatment with high-dose methylprednisolone, cerebellar deficits, relapse, and all-cause hospitalization post-infection. RESULTS: MS patients with COVID-19 had similar demographics but higher prevalence of pre-existing major comorbidities (hypertension, type-2 diabetes, chronic obstructive pulmonary disease, congestive heart failure, chronic kidney disease, and coronary artery disease), optic neuritis, and history of high dose steroid treatment for relapses compared to MS patients without COVID-19. MS patients with COVID-19 had greater risk of mortality (adjusted HR=4.34[1.67, 11.30], p < 0.005), greater risk of post infection optic neuritis (adjusted HR=2.97[1.58, 5.58], p < 0.005), higher incidence of methylprednisolone treatment for post infection acute relapse (12.65% vs. 2.54 %, p < 0.001), and more hospitalization (78.92% vs. 66.81 %, p < 0.01), compared to MS patients without COVID-19. CONCLUSIONS: MS patients who survived COVID-19 infection experienced worse long-term outcomes, as measured by treatment for relapse, hospitalization and mortality. Identifying risk factors for worse long-term outcomes may draw clinical attention to the need for careful follow-up of at-risk individuals post-SARS-CoV-2 infection.

Homelessness in Pregnancy and Increased Risk of Adverse Outcomes: A Retrospective Cohort Study.

Limited data indicates that homelessness during pregnancy is linked to adverse outcomes for both mothers and newborns, but there is an information gap surrounding pregnant individuals struggling with homelessness. In a landscape of increasing healthcare disparities, housing shortages and maternal mortality, information on this vulnerable population is fundamental to the creation of targeted interventions and outreach. The current study investigates homelessness as a risk factor for adverse obstetrical, neonatal, and postpartum outcomes. We reviewed more than 1000 deliveries over 1 year at a large public hospital in New York City, comparing homeless subjects to a group of age-matched, stably housed controls. Multiple outcomes were assessed regarding obstetrical, neonatal, and postpartum outcomes along with social stressors. Homeless pregnant individuals were more likely to experience numerous adverse outcomes, including cesarean delivery and preterm delivery. Their neonates were more likely to undergo an extended stay in the intensive care unit and evaluation by the Administration for Children's Services, suggesting that they may be at an increased risk for family separation. After delivery, patients were less likely to exclusively breastfeed or return for their postpartum visit. Regarding personal history, they were more likely to endorse a history of violence or abuse, use illicit substances, and carry a psychiatric diagnosis. These findings indicate that homelessness is linked to numerous adverse obstetrical, neonatal, and postpartum outcomes that worsen health indices and exacerbate pre-existing disparities. Initiatives must focus on improved outreach and care delivery for homeless pregnant individuals.

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.

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.

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.

Increases in the use of drug testing kits among nightclub and festival attendees in New York City who use ecstasy, 2017-2022.

INTRODUCTION: Ecstasy (3,4-methylenedioxymethamphetamine [MDMA]) is a drug commonly used by people who attend electronic dance music (EDM) events at nightclubs and dance festivals. Drug checking has gained popularity in recent years to test for adulterants, but epidemiology studies are needed to estimate potential shifts in prevalence of drug checking to further inform harm reduction efforts. METHODS: Adults entering randomly selected EDM events in New York City were surveyed in 2017 and 2022. Those reporting past-year ecstasy use were asked if they tested their ecstasy in the past year using a drug testing kit and whether they found out or suspected their ecstasy contained other drugs. We compared estimates between 2017 and 2022. RESULTS: In 2017, an estimated 23.1% had tested their ecstasy, and this estimate increased to 43.1% in 2022 (86.6% increase, p = 0.006). Among those who tested their ecstasy, in 2017, 31.2% always tested their drug, and this increased to 60.6% in 2022 (94.2% increase, p = 0.026). In 2017, 59.6% of those who tested their ecstasy reported finding out or suspecting their drug was adulterated, which decreased to 18.4% in 2022 (69.1% decrease, p < 0.001). Suspected methamphetamine adulteration in particular decreased, from 21.9% in 2017 to 3.6% in 2022 (83.6% decrease, p = 0.007). DISCUSSION AND CONCLUSIONS: The use of drug testing kits has increased among EDM event attendees who use ecstasy and, at the same time, among those who had tested their ecstasy, suspected adulteration has decreased. Continued interest in understanding ecstasy contents among this population suggests the need for formal drug checking services.

Five human pathogens detected by tick surveillance in New York City parks, 2014-2015.

A total of 2,504 ticks of 5 species (Ixodes scapularis, Dermacentor variabilis, Amblyomma americanum, Haemaphysalis leporispalustris, and H. longicornis) were collected over 2 yr (2014-2015) in New York City parks. Specimens were collected via tick-dragging, identified to species, and tested for pathogens of human diseases. The causative agents of 5 human diseases (Lyme borreliosis, ehrlichiosis, babesiosis, anaplasmosis, and Rocky Mountain spotted fever) were detected in a subset of samples. Results of this surveillance effort further illustrate that risk of tick-borne disease is considerable even in parks located adjacent to densely populated areas.