New York City Research Articles

Clinical Characteristics of COVID-19 Coagulopathy, Experiences in a New York City Safety Net Hospital

Purpose/Objective: COVID-19 is a significant cause of morbidity and mortality in the inner-city population in New York City (NYC), with COVID-19 coagulopathy and venous thromboembolism (VTE) as major contributing factors. A recent meta-analysis of 17 studies demonstrated a pooled 25% increased risk of VTE incidence in hospitalized COVID-19 patients (Zhang et. al, 2020). To assess morbidity burden, the primary objective of this current study is to investigate COVID-19 coagulopathy incidence in hospitalized patients in an Afro-Caribbean NYC population. The secondary objective was to assess the clinical characteristics and risk factors of COVID-19 coagulopathy, classify disease severity and outcomes. Methods: A retrospective study was performed at the NYC Health and Hospitals/Kings County on patients hospitalized with COVID-19. Data was collected from March 1 st, 2020 to December 31 st, 2021 for hospitalized and intensive care patients. Information was collected on the incidence of VTE, type of VTE (deep vein thrombosis or pulmonary embolism), demographics, VTE prevention strategies, VTE management, inflammatory markers, and outcomes. GraphPad PRISM was used for statistical analysis, through unpaired t-tests and odds ratios, with p<0.05 indicating statistical significance. Results: The primary objective investigated 675 patients to assess COVID-19 incidence, with imaging-confirmed VTE incidence in 32 (4.74%), and mortality in 112 (16.6%) patients (Table 1). To assess factors that influence VTE, we assessed demographic, outcome and infection severity between 32 VTE patients, and 142 non-VTE patients (Table 2). Multivariable analysis of comorbidities demonstrated that obesity was an independent risk factor for VTE (OR=11.4938, 95% CI 4.3512 to 30.3615, p<0.001). Interestingly, prior VTE did not increase the risk of VTE between cohorts. Further, there is a trend towards increased mortality risk in VTE patients compared to non-VTE patients, although not statistically significant (OR= 2.7483, 95% CI 0.9332 to 8.0934, p=0.0666). We were unable to deduce differences between VTE prevention strategies between the cohorts due to insufficient power. Upon analyzing inflammatory markers, D-Dimers were determined to be significantly elevated in VTE patients compared to non-VTE patients (p=0.0274), whereas there was no significant difference between LDH or ferritin between the cohorts. Conclusions/Implications: This study characterized the incidence and demographics of COVID-19 coagulopathy in a safety net NYC hospital, wherein there is decreased VTE incidence compared to prior published literature (Zhang et. al, 2020). Our study also supports current literature which identifies obesity as a risk factor for VTE in COVID-19 patients (Wang et al, 2021). We hypothesize that BMI reduction may be protective against COVID-19 induced VTE risk, and targeted BMI reduction programs may mitigate COVID-19 severity. Future studies should continue to investigate COVID-19 risk reduction strategies in patients with comorbidities and can consider anticoagulation use based on risk factors.

The Prevalence and Mutational Spectrum of Clonal Hematopoiesis in Diverse Populations in New York City

Introduction: Clonal hematopoiesis (CH) is a pre-malignant condition characterized by over-representation of blood cells derived from a single stem-cell clone. CH is strongly associated with aging with 10-20% of people over the age of 70 in various series reported to harbor a detectable clone. The most commonly mutated genes in aging-related CH are DNMT3A & TET2 followed by ASXL1 as a distant third and a smaller frequency of mutations in the splicing genes SF3B1, SRSF2, PRPF8 and U2AF1. CH portends a strong underlying risk for development of Myelodysplastic Syndrome (MDS) and other hematologic neoplasms as well as future cardiovascular disease and all-cause mortality. While much is known about these pre-leukemic states that confer risk for developing AML, most of the published studies are based on predominantly white Europeans. There has also recently been an effort to provide genomic and clinical services to high-risk individuals (CH clinics) to predict their pre-leukemic risk, however almost all these services are unavailable to underserved, ethnic minority populations. We decided to query the rate and associations of CH in diverse populations of New York City (NYC). The few published studies investigating CH in diverse populations have used self-identified categorization of race and ethnicity. However, these groupings can be too general and inaccurate when investigating genetic variation, particularly in diverse and multi-ethnic populations. Here we present our CH analysis on the multi-ethnic All of Us (AoU) cohort (version 6) for NYC individuals. A population genetics approach was used to identify groups of individuals who share genetic segments identical by descent, which corresponded to several known communities. We estimated the frequency of CH among the populations identified through this approach. Methods & Results: Of a total of 8538 NYC individuals in the AoU cohort that had information on lifestyle (smoking), 393 (4.64%) had CH. We assigned these individuals to 11 genetic ancestry groups based on sharing of genomic segments identical by descent. Out of these 11 groups, 6 had >20 individuals with CH, so we focused on those groups for further analysis (Figure 1). We constructed a logistic regression model between CH status and ancestry taking into account age, age*age (to account for a non-linear effect), sex, smoking and mean BMI with individuals belonging to the ‘Non-Jewish European ancestry group’ as a reference. We found that Dominicans have a higher rate of CH in comparison to other ancestry groups (OR: 1.62; p-value: 0.018; Figure 2). Dominicans as an ancestry group independently showed statistically significant associations with cardiovascular diseases such as heart failure, cardiac arrythmia and cardiomegaly. Whether this association is related to elevated CH remains to be investigated. We also measured the enrichment of variants in individual CH genes in each ancestry group, keeping all other individuals as a reference. Our results showed that CH in individuals belonging to the African ancestry group, as well as the Ashkenazi Jewish group have significantly higher rates of somatic mutations in DNMT3A (OR: 1.82; p-value: 0.027) and TET2 (OR: 2.36; p-value 0.004), respectively, compared to the other populations. Conclusions: Leveraging population genetic-based inference of ancestry groups, we have demonstrated for the first time that different ancestries residing in NYC have a different risk and pattern of CH somatic mutations. In particular, we demonstrate that non-Jewish Europeans have lower risk of CH compared to all other groups, and Dominicans in particular have a significantly higher risk. Understanding the relative rates of CH across ancestries and their association with chronic diseases such as CVD and cancer will further refine recommendations directed towards lifestyle modifications and rational therapeutics that prevent the progression of CH & associated comorbidities.

1771. A Novel Approach to Distributing COVID-19 Oral Antivirals During a Public Health Emergency Using a Pharmacy Home Delivery Model in New York City, 2022

Abstract Background In December 2021, the oral antivirals (OAVs) nirmatrelvir/ritonavir and molnupiravir were authorized for the treatment of COVID-19 in high-risk patients. Initial supplies were limited and states designated pharmacies to receive OAVs from a weekly federal allocation. New York City (NYC) has nearly 3,000 pharmacies serving a diverse population across a large urban area. To ensure fair access to OAVs, the NYC Health Department partnered with an online pharmacy to provide rapid delivery to any NYC address. Here we describe characteristics of patients served and metrics used to evaluate the program as the pandemic and OAV access evolved in 2022. Methods The NYC partner pharmacy provided data on OAV prescriptions including patient age, sex, delivery zip code, and dates of prescription and delivery. These data were matched with the NYC Health Department’s COVID-19 surveillance data including positive lab reported cases, Citywide Immunization Registry, deaths, all-cause emergency department (ED) visits and hospital admissions. Descriptive statistics were calculated using R Statistical Software. Results A total of 48,947 OAV prescriptions were delivered in 2022, reaching 99.5% of residential zip codes, accounting for 17.5% of the OAVs dispensed in NYC. The median time from prescription receipt to delivery was 17 hours (IQR 6-24) with half (49%) of deliveries going to high social vulnerability zip codes. Of OAV recipients, most (58%) were female, with a median age of 56 years (IQR 39, 68) with 32% aged 65 years or older; 78% had received at least a primary vaccination series; 36% matched with a lab reported COVID-19 case; 5.5% had an ED visit and 0.8% were hospitalized in NYC for any cause within 30 days of prescription date. Conclusion The NYC antiviral delivery program provided broad and timely access to COVID OAVs, serving a significant proportion of patients in high social vulnerability neighborhoods and older adults at higher risk for severe outcomes. Of note, an increasing proportion of people receiving OAVs were not reported as cases to public health, which likely reflects the increasing use of home tests in 2022. Limitations include the lack of data on race/ethnicity, underlying medical conditions and for patients receiving OAVs through other pharmacies. Disclosures All Authors: No reported disclosures

1484. Hepatitis C Virus Infection and Cure by Priority Population Among New York City Ryan White HIV/AIDS Program Part A Clients

Abstract Background Hepatitis C virus (HCV) infection is a common comorbidity among people with HIV (PWH). HCV-related liver disease is the second leading cause of death among PWH. To identify opportunities to improve service integration and health equity, we examined HCV infection and cure among priority populations identified for New York City (NYC) Ryan White HIV/AIDS Program Part A (RWPA) service delivery. Methods Using a merge of NYC HIV and HCV surveillance data with RWPA program data, we identified RWPA clients receiving services from 01/2019–12/2022. We categorized clients into priority populations: Black or Latina cisgender women; Black or Latino men who have sex with men (MSM); transgender, intersex, gender non-conforming, or non-binary (TIGNCNB) people; people who inject drugs (PWID); and people aging (age >50) with HIV (PAWH). We measured active HCV infections (any positive RNA test during analysis period), and HCV cure­ (negative RNA result on the most recent HCV test >12 weeks after most recent positive RNA result obtained during the analysis period). Using logistic regression, we compared HCV prevalence and HCV cure by population, adjusting for potential confounders. Results Among 15,702 RWPA clients, 15% (n=2,278) had active HCV infection, with 70% (n=1,596) achieving cure. 53% of clients were PAWH, 36% were Black/Latino MSM, 26% were Black/Latina cisgender women, 5% were TIGNCNB people, and 2% were PWID. PWID had the highest proportion of HCV infection (38%), and PAWH had the highest cure proportion (73%) (Table 1). After adjusting for potential confounders, PWID and PAWH had higher odds of HCV infection compared to other clients [adjusted odds ratio (aOR): 4.37, 95% CI: 3.41, 5.59 for PWID; aOR: 4.05, 95% CI: 3.61, 4.54 for PAWH]. Black/Latino MSM and Black/Latina cisgender women had lower odds of infection (aOR: 0.79, 95% CI: 0.71, 0.88 and aOR: 0.60, 95% CI: 0.53, 0.68, respectively) compared to other clients. Among clients with HCV, PWID had lower odds of cure compared to non-PWID (aOR: 0.58, 95% CI: 0.39, 0.85; Table 2). Table 1, Part 1 Table 1, Part 2 Conclusion These findings – particularly the low odds of HCV cure among PWID, who had the highest odds of infection – highlight gaps that can inform resource allocation and targeted integration of HIV/HCV care. Disclosures All Authors: No reported disclosures

2313. Population-based Incidence of SARS-CoV-2-associated Hospitalizations across the Age Spectrum in New York City, 2020-2021

Abstract Background Population-based incidence rates for hospitalizations due to SARS-CoV-2 can provide an increased understanding of the impact of transmission and mitigation strategies over time, yet there are relatively few estimates of such rates. Thus, we conducted a population-based, surveillance study to estimate incidence rates of SARS-CoV-2 hospitalizations among patients across the age spectrum. Methods From March 2020 to December 2021, we retrospectively reviewed the electronic medical records of patients admitted to an academic, multi-hospital system in New York City (NYC) to determine population-based incidence rates. Eligible patients resided in the pre-defined surveillance area, had ≥2 acute symptoms, and had laboratory-confirmed SARS-CoV-2 infection detected within 14 calendar-days prior to admission to 2 calendar-days after admission. Overall and age group incidence of SARS-CoV-2 hospitalization per 100,000 persons living in the surveillance area were calculated using 2020 census data, adjusted by hospital market share. Results From 2020-2021, 3,283 eligible patients were hospitalized with SARS-CoV-2 at the study hospitals. Patients’ median age in 2020 was 69 years (IQR 56, 80) and in 2021 was 67 years (IQR 51, 79) and 2.5% were 0-17 years old. Overall, 52% were male and 11%, 10%, and 61% were Black, White, and Hispanic, respectively. An estimated 1-4% of adults in age groups >65 years living in the surveillance area were hospitalized (Table). From 2020 to 2021, the overall population-based annual incidence rate and annual incidence rates in age groups 50-64, 65-74, 75-84, and ≥85 years decreased. While not significant, the incidence rate increased in patients 0-14 years. Conclusion These population-based incidence rates provide unique insights into the SARS-CoV-2 burden in a predefined surveillance area in NYC which served as the epicenter of the first U.S. wave of the pandemic. While incidence rates decreased in those >50 years old, rates were largely unchanged in those < 50 years old suggesting that younger adults and children had continued and potentially increased exposures to SARS-CoV-2 and/or lower vaccination rates than older adults during the second full year of the pandemic. Such incidence data can measure the impact of mitigation strategies. Disclosures Lisa Saiman, MD MPH, Merck & Co., Inc,: Grant/Research Support|Merck & Co., Inc,: Member, DSMB|Pfizer, Inc: Member, DSMB Edward E. Walsh, MD, Icosavax: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Merck: Honoraria|Moderna: Advisor/Consultant|Pfizer: Grant/Research Support Angela R. Branche, MD, Cyanvac: Grant/Research Support|GSK: Advisor/Consultant|Janssen: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Grant/Research Support Julia A. Schillinger, MD, MSc, Merck & Co.: Employee, Stocks and Bonds MATTHEW R. PHILLIPS, MPH, Merck & Co., Inc., Rahway, NJ, USA: Employee|Merck & Co., Inc., Rahway, NJ, USA: Stocks/Bonds Lynn Finelli, DrPH, MS, Merck&Co: Stocks/Bonds

Multicultural commodification in New York City’s culinary field: resistance among Mexican Indigenous chefs

ABSTRACT This article is situated in the intersections of Indigenous, migration, and food studies. The article is guided by the questions: How have New York City (NYC) media used Mexican Indigeneity to promote multicultural commodification? How do self-ascribed Mexican Indigenous chefs used their Indigeneity as a form of resistance? To answer these questions, I undertook participant observation in NYC, conducted semi-structured interviews, and analyzed food reviews from NYC media. In this piece I claim that NYC media has branded the city as multicultural. Nevertheless, the simplified narratives of racialized culinary cultures have mainly benefitted consumers and NYC branding. The trajectories of the two Mexican Indigenous chefs studied here show the ways in which these chefs challenged multicultural commodification.

Ghost-Stitching American Politics

Ghost-Stitching American Politics

Church Closings Were Associated with Higher COVID-19 Infection Rates: Implications for Community Health Equity.

This study investigates the changes in physical church closings years 2013 to 2019 in New York City (NYC), Philadelphia, and Baltimore and the association with COVID-19 infection rates. We applied Bayesian spatial binomial models to analyze confirmed cases of COVID-19 as of February 28, 2022, in each city at the zip code-level. A one unit increase in the number of churches closed corresponded to a 5% higher COVID-19 infection rate, in NYC (rate ratio = 1.05, 95% credible interval = 1.02-1.08%), where the association was significant. Church closings appears to be an important indicator of neighborhood social vulnerability. Church closings should be routinely monitored as a structural determinant of community health and to advance health equity.

Spatial attribution of aircraft mass balance experiment CO2 estimations for policy-relevant boundaries: New York City

To effectively address the unprecedented acceleration of climate change, cities across the United States are leading efforts to reduce greenhouse gas emissions. Coherent, aggressive, and lasting mitigation policies in controlling carbon emissions are beginning to be adopted to help strengthen climate resilience across different sectors. However, evaluating the effectiveness of current climate legislation requires careful monitoring of emissions through measurable and verifiable means to inform policy decisions. As a part of this effort, we developed a new method to spatially allocate aircraft-based mass balance carbon dioxide (CO2) emissions. In this work, we conducted 7 aircraft flights, performed downwind of New York City (NYC) to quantify CO2 emissions during the nongrowing seasons between 2018 and 2020. We used an ensemble of emission inventories and transport models to calculate the fraction of enhancements (Φ) produced by sources within the policy-relevant boundaries of the 5 NYC boroughs and then applied that to the bulk emissions calculated using the mass balance approach. We derived a campaign-averaged source-apportioned mass balance CO2 emission rate of (57 ± 24) (1σ) kmol/s for NYC. We evaluated the performance of this approach against other top-down methods for NYC including inventory scaling and inverse modeling, with our mean emissions estimate resulting in a 6.5% difference from the average emission rate reported by the 2 complementary approaches. By combining mass balance and transport model approaches, we improve upon traditional mass balance experiment methods to enable quantification of emissions in complex emission environments. We conducted an assessment using an ensemble of emission inventories and transport models to determine the sources of variability in the final calculated emission rates. Our findings indicate that the choice of inventory accounted for 2.0% of the variability in the emission estimates and that the atmospheric transport model contributed 3.9% at the campaign level. Additionally, on average, at the daily scale, the transport model contributed 7.6% and the inventory accounted for 14.1%. The daily flight-to-flight variability contributed a significant portion, at 42.1%. This approach provides a solution to the difficulty of interpreting aircraft-based mass balance results in complex emission environments.

Neighborhood Food Accessibility and Health Disparity: Examining the Impact of COVID-19 Using Spatial Models

COVID-19 exacerbated food system vulnerabilities globally. This study assesses the impact of shock events on food accessibility in New York City (NYC) by examining its association with neighborhood characteristics between 2019 and 2020. We model food accessibility using socioeconomic and built environment factors, adjusting for spatial effects with spatial econometric models and geographically weighted regression (GWR). Our spatial modeling methods reveal diverging relationships between minority racial/ethnic groups and food accessibility, as well as a negative change in the effect of income. Overall, our results indicate that food accessibility worsened or polarized during the pandemic, suggesting the need for improved network connectivity and smaller-scale food stores to achieve equitable and resilient food systems.

Overdose Prevention Centers, Crime, and Disorder in New York City

The first government-sanctioned overdose prevention centers (OPCs) in the US opened in New York City (NYC) in November 2021 amid concerns that they may increase crime and disorder, representing a significant political challenge to OPCs. To identify whether opening the first 2 government-sanctioned OPCs in the US was associated with changes in crime and disorder. In this cohort study, difference-in-differences Poisson regression models were used to compare crime, residents' requests for assistance for emergencies and nuisance complaints, and police enforcement in the vicinity of NYC's 2 OPCs with those around 17 other syringe service programs that did not offer overdose prevention services from January 1, 2019, through December 31, 2022. Changes in the volume of crimes reported by the public or observed by police; arrests for drug possession and weapons; 911 calls and 311 calls regarding crime, public nuisances, and medical events; and summonses issued by police for criminal infractions in both the immediate vicinity of the sites (ie, a hexagonal area spanning about 6 city blocks) and their wider neighborhoods (ie, a tesselated 3-hexagon array spanning about 18 city blocks). No significant changes were detected in violent crimes or property crimes recorded by police, 911 calls for crime or medical incidents, or 311 calls regarding drug use or unsanitary conditions observed in the vicinity of the OPCs. There was a significant decline in low-level drug enforcement, as reflected by a reduction in arrests for drug possession near the OPCs of 82.7% (95% CI, -89.9% to -70.4%) and a reduction in their broader neighborhoods of 74.5% (95% CI, -87.0% to -50.0%). Significant declines in criminal court summonses issued in the immediate vicinity by 87.9% (95% CI, -91.9% to -81.9%) and in the neighborhoods around the OPCs by 59.7% (95% CI, -73.8% to -38.0%) were observed. Reductions in enforcement were consistent with the city government's support for the 2 OPCs, which may have resulted in a desire not to deter clients from using the sites by fear of arrest for drug possession. In this difference-in-differences cohort study, the first 2 government-sanctioned OPCs in the US were not associated with significant changes in measures of crime or disorder. These observations suggest the expansion of OPCs can be managed without negative crime or disorder outcomes.

Rapid surveillance of New York City healthcare center egress behaviors during the 2020 COVID-19 lockdown

This rapid response surveillance project was funded by the National Science Foundation (NSF) to collect “perishable” data on egress behaviors and neighborhood conditions surrounding healthcare centers (HCCs) in New York City (NYC) during the initial NYC COVID-19 PAUSE ordinance from March 22nd to May 19th, 2020. Anonymized data on NYC HCC egress behaviors were collected by observational field workers using phone-based mapping applications. Each egress trip record includes the day of week, time of day, destination category type, along with an array of behavioral outcome categories, ambient weather conditions and socio-economic factors. Egress trajectories with precise estimates of distance traveled and the spatial dispersion or “spread” around each HCC were added via post-processing. The data collection and cleaning process resulted in 5,030 individual egress records from 18 facilities over a 9-week period.

Change of urban park usage as a response to the COVID-19 global pandemic

Urban parks became critical for maintaining the well-being of urban residents during the COVID-19 global pandemic. To examine the impact of COVID-19 on urban park usage, we selected New York City (NYC) and used SafeGraph mobility data, which was collected from a large sample of mobile phone users, to assess the change in park visits and travel distance to a park based on 1) park type, 2) the income level of the visitor census block group (visitor CBG) and 3) that of the park census block group (park CBG). All analyses were adjusted for the impact of temperature on park visitation, and we focused primarily on visits made by NYC residents. Overall, for the eight most popular park types in NYC, visits dropped by 49.2% from 2019 to 2020. The peak reduction in visits occurred in April 2020. Visits to all park types, excluding Nature Areas, decreased from March to December 2020 as compared to 2019. Parks located in higher-income CBGs tended to have lower reductions in visits, with this pattern being primarily driven by large parks, including Flagship Parks, Community Parks and Nature Areas. All types of parks saw significant decreases in distance traveled to visit them, with the exception of the Jointly Operated Playground, Playground, and Nature Area park types. Visitors originating from lower-income CBGs traveled shorter distances to parks and had less reduction in travel distances compared to those from higher-income CBGs. Furthermore, both before and during the pandemic, people tended to travel a greater distance to parks located in high-income CBGs compared to those in low-income CBGs. Finally, multiple types of parks proved crucial destinations for NYC residents during the pandemic. This included Nature Areas to which the visits remained stable, along with Recreation Field/Courts which had relatively small decreases in visits, especially for lower-income communities. Results from this study can support future park planning by shedding light on the different uses of certain park types before and during a global crisis, when access to these facilities can help alleviate the human well-being consequences of “lockdown” policies.

Effects of Air Pollution on Respiratory Events and Pain Crises Among Children with Sickle Cell Disease in New York City

Introduction: Sickle cell disease (SCD) has the highest U.S. disease burden among Black and Hispanic populations, who more commonly live in urban areas with poor ambient air quality. The effect of air pollution exposure and social environmental factors on health outcomes in SCD have not been extensively studied, especially among children, and may further contribute to health disparities. Objectives: This study aims to examine the associations between air pollution exposure and acute respiratory and pain events and to determine whether neighborhood-level social disadvantage would modify their associations. Methods: We collected retrospective data on unscheduled outpatient visits, emergency department (ED) visits, and hospital admissions for respiratory events (i.e., respiratory tract infections, asthma exacerbation, acute chest syndrome) and vaso-occlusive pain crises requiring hospitalization (VOCs) for children with SCD in a tertiary care center in New York City (NYC) from 2015-2018. A total of 114 children with SCD (Table 1) were included in this study and had between 1-4 annual repeated measures of annual average air pollutants (i.e., black carbon (BC), fine particulate matter (PM 2.5), and nitrogen dioxide (NO 2)) with a total of 425 visits. Using home addresses, modeled data from the NYC Community Air Survey data were used to estimate street-level, annual average exposure to air pollution. The area deprivation index (ADI), a composite index of neighborhood-level social disadvantage, was dichotomized at the upper tertile (higher vs lower). Multivariable Poisson regression in generalized estimating equation (GEE) models were used to estimate relative risks (RR), after adjusting for potential covariates. Results: Overall, there were no significant associations between air pollution levels and acute respiratory and pain events among children with SCD. When stratified by ADI, increased exposure to PM 2.5 and NO 2, but not BC, was significantly associated with more frequent respiratory outpatient and ED visits among children residing in higher ADI neighborhoods (RR (95%CI)= 1.13 (1.00, 1.28) and 1.43 (1.01, 2.02) for PM 2.5 and NO 2, respectively, p<0.05 for all), but not among those in lower ADI neighborhoods (P-value for interaction=0.2 and 0.02 for PM 2.5 and NO 2, respectively) (Figure 1). Associations of air pollution with hospital admissions and VOCs were not observed for neither high ADI nor low ADI neighborhoods (p-value>0.05). Conclusions: Exposure to air pollutants increased respiratory complications among children living in deprived neighborhoods.

Community transmission of SARS-CoV-2 during the Delta wave in New York City

BackgroundUnderstanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood.MethodsUsing high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread.ResultsWe find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing.ConclusionsThe Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

Rifampin Mono-Resistant Tuberculosis in New York City, 2010-2021: A Retrospective Case Series.

Although relatively rare, rifampin mono-resistant tuberculosis (RMR TB) poses important challenges to effective TB treatment and control. Information on the burden of RMR TB and treatment outcomes is needed to inform diagnosis and management. Standardized variables were collected from the New York City (NYC) tuberculosis surveillance system for patients treated for RMR TB in NYC during 2010-2021. Of 7097 TB cases reported in 2010-2021, 31 (<1%) were treated clinically as RMR TB. Five (16%) of these patients had HIV. Seventeen patients (55%) had TB that was rifampin-resistant by both molecular and phenotypic drug susceptibility testing; 2 (6%) had rifampin resistance by phenotypic tests, and molecular tests were not done; and 12 (39%) were identified based only on molecular tests. Among these 12, 7 were rifampin-sensitive by phenotypic tests, and phenotypic testing could not be done for the other 5. Ten of the 31 (32%) were diagnosed in 2010-2015; the other 21 (including 10/12 diagnosed by molecular tests alone) were diagnosed in 2016-2021. Of the 31 patients, 21 (68%) completed treatment (median treatment duration of 18 months). Although the interval between tuberculosis treatment initiation and change to a non-rifamycin-containing regimen decreased significantly during the study period, the overall duration of treatment did not decrease significantly between 2010 and 2021. Molecular drug susceptibility tests identified cases of RMR TB that were not detected by phenotypic testing and helped enable timely adjustment of tuberculosis treatment regimens. Short-course regimens are needed to reduce duration of treatment for RMR TB.

“¿Y tu novio? Where’s Your Boyfriend?”: A Cultural-Ecological Analysis of Latinas’ Narratives of Teen Dating Experiences

There is a dearth of research examining the dating experiences of Latina teens—a large and rapidly growing population in the U.S. that reports high rates of teen dating violence. The purpose of this qualitative research was to explore Latinas’ teen dating experiences and the familial and sociocultural factors that impact them using a cultural-ecological perspective. Twenty-five first-, second-, and third-generation immigrant Latinas between the ages of 18 and 23 participated in the research. A purposive sample was drawn from the New York City (NYC) metropolitan area. We applied a critical narrative inquiry methodology to conduct in-depth narrative interviews with participants, following protocols approved by the IRB. We employed an inductive and iterative analytic process that combined holistic- and categorical-content approaches to identify themes within and across narratives. We identified the following themes: (1) cultural expectations and norms, (2) parents’ rules and expectations, (3) covert relationships, and (4) violence and control. This study’s findings highlight the importance of considering the cultural-ecological context in examinations of Latina teens’ dating experiences, with particular attention to how gendered power dynamics shape Latina teens’ dating experiences across multiple levels.

A non-local grouping tensor train decomposition model for travel demand analysis concerning categorical independent variables

With the booming of transportation big data, plenty of spatial and temporal features become available for developing travel demand analysis models. However, existing machine learning based travel demand fitting models could face significant model complexity issues once there are multiple discrete/categorical independent variables. This paper embeds a non-local grouping (clustering) process into the tensor train decomposition (NLG-TTD) to characterize the higher-order and nonlinear relationship between categorical variables and travel demand. That is, the transportation dataset with multiple discrete/categorical independent variables and travel demand is treated as a multi-mode tensor, wherein levels of a discrete/categorical variable are regarded as indexes of a mode in the tensor, leading to a “regression on index”. The proposed NLG-TTD model divides the full tensor into non-local sub-tensors, clusters sub-tensors with similarity, conducts tensor train decomposition (TTD) within each cluster, and aggregates cluster-specific learning results. Compared with a conventional TTD that generally works on image completions, NLG-TTD can reveal non-Euclidean and non-linear patterns between categorical/discrete levels in independent variables. It is expected to discover similar travel demand patterns among categorical levels and provide high-level goodness-of-fit. For numerical studies, we use bike-sharing usage data and metro demand data in New York City (NYC), in which several widely-used machine learning models are trained for comparison. The results demonstrate the good performance of the proposed model. Moreover, we apply the NLG-TTD model to analyze and predict the impact of land use shifts on travel demand.

"Be honest and gain trust": a population health study to understand the factors associated with building trust in local government related to COVID-19 and vaccination in three historically disinvested neighborhoods in New York City.

Distrust in government among people of color is a response to generations of systemic racism that have produced preventable health inequities. Higher levels of trust in government are associated with better adherence to government guidelines and policies during emergencies, but factors associated with trust and potential actions to increase trust in local government are not well understood. The COVID-19 Community Recovery study sampled participants from the New York City (NYC) Department of Health and Mental Hygiene's NYC Health Panel, a probability-based survey panel who complete health surveys periodically. Participants who lived in one of three historically disinvested communities in NYC where the NYC Department of Health and Mental Hygiene has dedicated resources to reduce health inequities were included. The cross-sectional survey was fielded from September 30 to November 4, 2021 and could be self-administered online or conducted via CATI (Computer Assisted Telephone Interviewing) in English, Spanish, and Simplified Chinese (Mandarin and Cantonese by phone). Demographic data were summarized by descriptive statistics. Crude and adjusted logistic regression analyses were used to assess factors predictive of trust in local government as a source of information about COVID-19 vaccines. Open-ended responses about strengthening residents' trust in local government were coded using an iteratively generated codebook. In total, 46% of respondents indicated NYC local government was a trusted source of information about COVID-19 vaccines, relatively high compared to other sources. In bivariate analyses, race/ethnicity, age group, educational attainment, length of time living in NYC, and household income were significantly associated with identifying NYC government as a trusted source of information about COVID-19 vaccines. In multivariable logistic regression, no variables remained significant predictors of selecting local government as a trusted source of information. Key recommendations for local government agencies to build residents' trust include communicating clearly and honestly, addressing socioeconomic challenges, and enhancing public COVID-19 protection measures. Study findings demonstrate that nearly half of residents in three historically divested NYC communities consider local government to be a trusted source of information about COVID-19 vaccines. Strategies to increase trust in local government can help reduce community transmission of COVID-19 and protect public health.

Staff resilience and innovation essential to New York City diabetes prevention programs going virtual during COVID-19 pandemic lockdowns

BackgroundCOVID-19 lockdowns in March 2020 forced National Diabetes Prevention Programs (DPPs) to pause, cancel or reformulate. This qualitative study sought to (a) document if/how New York City(NYC) DPPs adapted and served participants during lockdowns, and (b) identify successes and challenges to operating programs during the lockdowns and restrictions on social gathering.MethodsResearchers contacted 47 CDC-registered DPPs in NYC. Eleven DPP directors, lifestyle coaches, and coordinators involved in program implementation completed 1-hour semi-structured virtual interviews and received a $50 gift card. Interviews were recorded, transcribed, and analyzed using Grounded Theory (Dedoose, Version 9).ResultsInterviewees represented 7 organization types: public hospitals, weight loss programs, healthcare centers, community-based organizations, health insurance companies, faith-based DPPs, and federally qualified health centers. DPPs served participants in 4 of 5 NYC boroughs. Six organizations provided DPP services during lockdowns by going virtual. Successes and challenges related to staffing, resource allocation, virtual data tracking, and participant engagement. Most programs were successful due to resilient, dedicated, and extraordinarily innovative staff.ConclusionThe pandemic highlighted opportunities for successful virtual DPPs in urban settings, and the need for more robust funding, staff support, and technical assistance for sustainability and scalability of the DPP.