Endless fascination.

Each of us fortunate enough to have had a career in experimental science has a tale to tell, often one with surprising twists and turns, full of lessons that can help guide those embarking on a similar journey. At the very least, a well-written recounting of a career can be entertaining. I offer my memory's version of my career in immunology and hope the readers will find it of value or at least of interest.

Knowledge about others reduces one's own sense of anonymity.

Social ties often seem symmetric, but they need not be1-5. For example, a person might know a stranger better than the stranger knows them. We explored whether people overlook these asymmetries and what consequences that might have for people's perceptions and actions. Here we show that when people know more about others, they think others know more about them. Across nine laboratory experiments, when participants learned more about a stranger, they felt as if the stranger also knew them better, and they acted as if the stranger was more attuned to their actions. As a result, participants were more honest around known strangers. We tested this further with a field experiment in New York City, in which we provided residents with mundane information about neighbourhood police officers. We found that the intervention shifted residents' perceptions of officers' knowledge of illegal activity, and it may even have reduced crime. It appears that our sense of anonymity depends not only on what people know about us but also on what we know about them.

Hematology and oncology clinical care during the coronavirus disease 2019 pandemic.

New York City has been at the epicenter of the coronavirus disease 2019 (COVID-19) pandemic that has already infected over a million people and resulted in more than 70,000 deaths as of early May 2020 in the United States alone. This rapid and enormous influx of patients into the health care system has had profound effects on all aspects of health care, including the care of patients with cancer. In this report, the authors highlight the transformation they underwent within the Division of Hematology and Medical Oncology as they prepared for the COVID-19 crisis in New York City. Under stressful and uncertain conditions, some of the many changes they enacted within their division included developing a regular line of communication among division leaders to ensure the development and implementation of a restructuring strategy, completely reconfiguring the inpatient and outpatient units, rapidly developing the ability to perform telemedicine video visits, and creating new COVID-rule-out and COVID-positive clinics for their patients. These changes allowed them to manage the storm while minimizing the disruption of important continuity of care to their patients with cancer. The authors hope that their experiences will be helpful to other oncology practices about to experience their own individual COVID-19 crises.

Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City.

In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first detected in China and has since caused a pandemic of coronavirus disease 2019 (COVID-19). The first case of COVID-19 in New York City was officially confirmed on 1 March 2020 followed by a severe local epidemic1. Here, to understand seroprevalence dynamics, we conduct a retrospective, repeated cross-sectional analysis of anti-SARS-CoV-2 spike antibodies in weekly intervals from the beginning of February to July 2020 using more than 10,000 plasma samples from patients at Mount Sinai Hospital in New York City. We describe the dynamics of seroprevalence in an 'urgent care' group, which is enriched in cases of COVID-19 during the epidemic, and a 'routine care' group, which more closely represents the general population. Seroprevalence increased at different rates in both groups; seropositive samples were found as early as mid-February, and levelled out at slightly above 20% in both groups after the epidemic wave subsided by the end of May. From May to July, seroprevalence remained stable, suggesting lasting antibody levels in the population. Our data suggest that SARS-CoV-2 was introduced in New York City earlier than previously documented and describe the dynamics of seroconversion over the full course of the first wave of the pandemic in a major metropolitan area.

Utilizing big data without domain knowledge impacts public health decision-making.

New data sources and AI methods for extracting information are increasingly abundant and relevant to decision-making across societal applications. A notable example is street view imagery, available in over 100 countries, and purported to inform built environment interventions (e.g., adding sidewalks) for community health outcomes. However, biases can arise when decision-making does not account for data robustness or relies on spurious correlations. To investigate this risk, we analyzed 2.02 million Google Street View (GSV) images alongside health, demographic, and socioeconomic data from New York City. Findings demonstrate robustness challenges; built environment characteristics inferred from GSV labels at the intracity level often do not align with ground truth. Moreover, as average individual-level behavior of physical inactivity significantly mediates the impact of built environment features by census tract, intervention on features measured by GSV would be misestimated without proper model specification and consideration of this mediation mechanism. Using a causal framework accounting for these mediators, we determined that intervening by improving 10% of samples in the two lowest tertiles of physical inactivity would lead to a 4.17 (95% CI 3.84-4.55) or 17.2 (95% CI 14.4-21.3) times greater decrease in the prevalence of obesity or diabetes, respectively, compared to the same proportional intervention on the number of crosswalks by census tract. This study highlights critical issues of robustness and model specification in using emergent data sources, showing the data may not measure what is intended, and ignoring mediators can result in biased intervention effect estimates.

Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

The role of socio-economic disparities in the relative success and persistence of SARS-CoV-2 variants in New York City in early 2021.

Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.1-like genomes and pre-existing immunity (seropositivity) in NYC neighborhoods. In the context of varying seroprevalence we described socio-economic profiles of neighborhoods and performed migration and lineage persistence analyses using a Bayesian phylogeographical framework. Seropositivity was greater in areas with high poverty and a larger proportion of Black and Hispanic or Latino residents. Seropositivity was positively correlated with the proportion of Iota-E484K and Iota genomes, and negatively correlated with the proportion of Alpha and B.1-like genomes. The proportion of persisting Alpha lineages declined over time in locations with high seroprevalence, whereas the proportion of persisting Iota-E484K lineages remained the same in high seroprevalence areas. During the second wave, the geographic variation of standing immunity, due to disproportionate disease burden during the first wave of SARS-CoV-2 in NYC, allowed for the immune evasive Iota-E484K variant, but not the more transmissible Alpha variant, to circulate in locations with high pre-existing immunity.

Detection of clade 2.3.4.4b highly pathogenic H5N1 influenza virus in New York City.

Highly pathogenic avian influenza viruses of the H5N1 clade 2.3.4.4b were detected in North America in the winter of 2021/2022. These viruses have spread across the Americas, causing morbidity and mortality in both wild and domestic birds as well as some mammalian species, including cattle. Many surveillance programs for wildlife as well as commercial poultry operations have detected these viruses. In this study, we conducted surveillance of avian species in the urban environment in New York City. We detected highly pathogenic H5N1 viruses in six samples from four different bird species and performed whole-genome sequencing. Sequencing analysis showed the presence of multiple different genotypes. Our work highlights that the interface between animals and humans that may give rise to zoonotic infections or even pandemics is not limited to rural environments and commercial poultry operations but extends into the heart of our urban centers.IMPORTANCEWhile surveillance programs for avian influenza viruses are often focused on migratory routes and their associated stop-over locations or commercial poultry operations, many bird species-including migratory birds-frequent or live in urban green spaces and wetlands. This brings them into contact with a highly dense population of humans and pets, providing an extensive urban animal-human interface in which the general public may have little awareness of circulating infectious diseases. This study focuses on virus surveillance of this interface, combined with culturally responsive science education and community outreach.

Variant-specific introduction and dispersal dynamics of SARS-CoV-2 in New York City - from Alpha to Omicron.

Since the latter part of 2020, SARS-CoV-2 evolution has been characterised by the emergence of viral variants associated with distinct biological characteristics. While the main research focus has centred on the ability of new variants to increase in frequency and impact the effective reproductive number of the virus, less attention has been placed on their relative ability to establish transmission chains and to spread through a geographic area. Here, we describe a phylogeographic approach to estimate and compare the introduction and dispersal dynamics of the main SARS-CoV-2 variants - Alpha, Iota, Delta, and Omicron - that circulated in the New York City area between 2020 and 2022. Notably, our results indicate that Delta had a lower ability to establish sustained transmission chains in the NYC area and that Omicron (BA.1) was the variant fastest to disseminate across the study area. The analytical approach presented here complements non-spatially-explicit analytical approaches that seek a better understanding of the epidemiological differences that exist among successive SARS-CoV-2 variants of concern.

Drug Overdose Mortality by Usual Occupation and Industry: 46 U.S. States and New York City, 2020.

Objective-This report describes deaths from drug overdoses in 2020 in U.S. residents in 46 states and New York City by usual occupation and industry. Methods-Frequencies, death rates, and proportionate mortality ratios (PMRs) are presented using the 2020 National Vital Statistics System mortality data file. Data were restricted to decedents aged 16-64 for rates and 15-64 for PMRs with usual occupations and industries in the paid civilian workforce. Age-standardized drug overdose death rates were estimated for usual occupation and industry groups overall, and age-adjusted drug overdose PMRs were estimated for each usual occupation and industry group overall and by sex, race and Hispanic-origin group, type of drug, and drug overdose intent. Age-adjusted drug overdose PMRs were also estimated for individual occupations and industries. Results-Drug overdose mortality varied by usual occupation and industry. Workers in the construction and extraction occupation group (162.6 deaths per 100,000 workers, 95% confidence interval: 155.8-169.4) and construction industry group (130.9, 126.0-135.8) had the highest drug overdose death rates. The highest group-level drug overdose PMRs were observed in decedents in the construction and extraction occupation group and the construction industry group (145.4, 143.6-147.1 and 144.9, 143.2-146.5, respectively). Differences in drug overdose PMRs by usual occupation and industry group were observed within each sex, within each race and Hispanicorigin group, by drug type, and by drug overdose intent. Among individual occupations and industries, the highest drug overdose PMRs were observed in decedents who worked as fishers and related fishing occupations and in fishing, hunting, and trapping industries (193.1, 166.8-222.4 and 186.5, 161.7-214.1, respectively). Conclusions-Variation in drug overdose death rates and PMRs by usual occupation and industry in 2020 demonstrates the disproportionate burden of the ongoing drug overdose crisis on certain sectors of the U.S. workforce.

Surveillance strategies for the detection of new pathogen variants across epidemiological contexts.

Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden. Improvements in detection times and reduction of undetected infections were driven primarily by increases in the number of sequenced samples. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies of pandemic respiratory pathogens.

Normal Lung Function and Mortality in World Trade Center Responders and National Health and Nutrition Examination Survey III Participants.

Rationale: Low FEV1 is a biomarker of increased mortality. The association of normal lung function and mortality is not well described. Objectives: To evaluate the FEV1-mortality association among participants with normal lung function. Methods: A total of 10,999 Fire Department of the City of New York (FDNY) responders and 10,901 Third National Health and Nutrition Examination Survey (NHANES III) participants, aged 18-65 years with FEV1 ⩾80% predicted, were analyzed, with FEV1 percent predicted calculated using Global Lung Function Initiative Global race-neutral reference equations. Mortality data were obtained from linkages to the National Death Index. Cox proportional hazards models estimated the association between FEV1 and all-cause mortality, controlling for age, sex, race/ethnicity, smoking history, and, for FDNY, work assignment. Cohorts were followed for a maximum of 20.3 years. Measurements and Main Results: We observed 504 deaths (4.6%) of 10,999 for FDNY and 1,237 deaths (9.4% [weighted]) of 10,901 for NHANES III. Relative to FEV1 ⩾120% predicted, mortality was significantly higher for FEV1 100-109%, 90-99%, and 80-89% predicted in the FDNY cohort. In the NHANES III cohort, mortality was significantly higher for FEV1 90-99% and 80-89% predicted. Each 10% higher predicted FEV1 was associated with 15% (hazard ratio, 0.85; 95% confidence interval, 0.80-0.91) and 23% (hazard ratio, 0.77; 95% confidence interval, 0.71-0.84) lower mortality for FDNY and NHANES III, respectively. Conclusions: In both cohorts, higher FEV1 is associated with lower mortality, suggesting higher FEV1 is a biomarker of better health. These findings demonstrate that a single cross-sectional measurement of FEV1 is predictive of mortality over two decades, even when FEV1 is in the normal range.

Concentrated incarceration and the public-housing-to-prison pipeline in New York City neighborhoods.

Using public housing developments as a strategic site, our research documents a distinct pathway linking disadvantaged context to incarceration-the public-housing-to-prison pipeline. Focusing on New York City Housing Authority (NYCHA) housing developments as a case study, we find that incarceration rates in NYCHA tracts are 4.6 times higher than those in non-NYCHA tracts. More strikingly, 94% of NYCHA tracts report rates above the median value for non-NYCHA tracts. Moreover, 17% of New York State's incarcerated population originated from just 372 NYCHA tracts. Compared with non-NYCHA tracts, NYCHA tracts had higher shares of Black residents and were significantly more disadvantaged. This NYCHA disadvantage in concentrated incarceration is also robust at different spatial scales. Our findings have implications for policies and programs to disrupt community-based pipelines to prison.

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas.

Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic's first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered superspreading events (SSEs). Although mass gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.

Trajectory analysis of rhinitis in a birth cohort from lower-income New York City neighborhoods.

BACKGROUND: Rhinitis is a prevalent, chronic nasal condition associated with asthma. However, its developmental trajectories remain poorly characterized. OBJECTIVE: We sought to describe the course of rhinitis from infancy to adolescence and the association between identified phenotypes, asthma-related symptoms, and physician-diagnosed asthma. METHODS: We collected rhinitis data from questionnaires repeated across 22 time points among 688 children from infancy to age 11 years and used latent class mixed modeling (LCMM) to identify phenotypes. Once children were between ages 5 and 12, a study physician determined asthma diagnosis. We collected information on the following asthma symptoms: any wheeze, exercise-induced wheeze, nighttime coughing, and emergency department visits. For each, we used LCMM to identify symptom phenotypes. Using logistic regression, we described the association between rhinitis phenotype and asthma diagnosis and each symptom overall and stratified by atopic predisposition and sex. RESULTS: LCMM identified 5 rhinitis trajectory groups: never/infrequent; transient; late onset, infrequent; late onset, frequent; and persistent. LCMM identified 2 trajectories for each symptom, classified as frequent and never/infrequent. Participants with persistent and late onset, frequent phenotypes were more likely to be diagnosed with asthma and to have the frequent phenotype for all symptoms (P < .01). We identified interaction between seroatopy and rhinitis phenotype for physician-diagnosed asthma (P = .04) and exercise-induced wheeze (P = .08). Severe seroatopy was more common among children with late onset, frequent and persistent rhinitis, with nearly 25% of these 2 groups exhibiting sensitivity to 4 or 5 of the 5 allergens tested. CONCLUSIONS: In this prospective, population-based birth cohort, persistent and late onset, frequent rhinitis phenotypes were associated with increased risk of asthma diagnosis and symptoms during adolescence.

Integrating Data Across Multiple Sites in the Northeastern United States to Examine Associations Between a Prenatal Metal Mixture and Child Cognition.

We applied a novel hierarchical Bayesian weighted quantile sum (HBWQS) regression to combine data across 3 study sites to examine associations between prenatal exposure to metals and cognitive functioning in childhood. Data from 326 mother-child dyads enrolled in an ongoing cohort study, the Programming of Intergenerational Stress Mechanisms (PRISM) Study, based in New York, New York (recruitment in 2013-2020) and Boston, Massachusetts (recruitment 2011-2013), and the First Thousand Days of Life (FTDL) cohort study (recruitment 2012-2019), based in northern Virginia, were used. Arsenic, cadmium, manganese, lead, and antimony were measured in urine collected during pregnancy. Cognitive functioning was assessed in children aged 3-11 years using the National Institutes of Health Toolbox Cognition Battery. The HBWQS regression showed a negative association between the urinary metal mixture and the Cognition Early Childhood Composite Score in the PRISM New York City (ß = -3.67, 95% credible interval (CrI): -7.61, -0.01) and FTDL (ß = -3.76, 95% CrI: -7.66, -0.24) samples, with a similar trend in the PRISM Boston sample (ß = -3.24, 95% CrI: -6.77, 0.144). We did not detect these associations in traditionally pooled models. HBWQS regression allowed us to account for site heterogeneity and detect associations between prenatal metal-mixture exposure and cognitive outcomes in childhood. Given the ubiquity of metals exposure, interventions aimed at reducing prenatal exposure may improve cognitive outcomes in children. This article is part of a Special Collection on Environmental Epidemiology.

Characterizing "collateral damage" in men and women with metastatic breast cancer (mBC) from diverse racial and ethnic backgrounds in New York City.

PURPOSE: Patients from diverse racial, ethnic, and socio-economic backgrounds may be particularly vulnerable to experiencing undue social and financial burdens ("collateral damage") from a metastatic breast cancer (mBC) diagnosis; however, these challenges have not been well explored in diverse populations. METHODS: From May 2022 to May 2023, English- or Spanish-speaking adults with mBC treated at four New York-Presbyterian (NYP) sites were invited to complete a survey that assessed collateral damage, social determinants of health, physical and psychosocial well-being, and patient-provider communication. Fisher's exact and the Kruskal-Wallis rank-sum tests assessed differences by race and ethnicity. RESULTS: Of 87 respondents, 14% identified as Hispanic, 28% non-Hispanic Black (NHB), 41% non-Hispanic White (NHW), 7% Asian American Pacific Islander (AAPI), and 10% other/multiracial. While 100% of Hispanic, NHW, and AAPI participants reported stable housing, 29% of NHB participants were worried about losing housing (p = 0.002). Forty-two percent of Hispanic and 46% of NHB participants (vs. 8%, NHW and 0%, AAPI, p = 0.005) were food insecure; 18% of Hispanic and 17% of NHB adults indicated lack of reliable transportation in the last year (vs. 0%, NHW/AAPI, p = 0.033). Participants were generally satisfied with the quality of communication that they had with their healthcare providers and overall physical and mental well-being were modestly poorer relative to healthy population norms. CONCLUSIONS: In our study, NHB and Hispanic mBC patients reported higher levels of financial concern and were more likely to experience food and transportation insecurity compared to NHW patients. Systematically connecting patients with resources to address unmet needs should be prioritized to identify feasible approaches to support economically vulnerable patients following an mBC diagnosis.

Colorectal cancer screening: results from the World Trade Center Health Registry cohort.

PURPOSE: Little is known about colorectal cancer screening in 9/11 World Trade Center (WTC)-exposed populations. We utilized survey data from the WTC Health Registry (WTCHR) to examine associations between enrollees' characteristics and colorectal cancer (CRC) screening. METHODS: We studied 22,061 enrollees aged 50-75 who completed the WTCHR follow-up survey in 2015-2016. Those with a history of CRC were excluded. Screening was defined as a self-reported, routine colonoscopy or sigmoidoscopy during the 12-month period prior to the survey. Multivariable log binomial regression identified factors associated with screening in the 12 months preceding the survey. We also stratified by age group. RESULTS: Of 22,061 enrollees, 23% were screened, with largely similar rates across age groups. Higher screening percentages were seen in selected groups including non-Hispanic Black enrollees (26.4%), males (24.3%), those married/living with a partner (24.1%), those with a higher household income (≥ $150 k, 25.4%), those who received services from the WTC Health Program (25.6%), and those with greater perceived social support (24.4%). On multivariable analyses, non-Hispanic Black enrollees [adjusted relative risk (aRR) = 1.30, 95% confidence interval (CI) 1.19-1.42] were significantly more likely to report screening, even after stratifying by age group. Hispanic enrollees, those with a higher household income, those with increased perceived social support, and those with diagnosed medical conditions under 70 years old were also associated with screening. CONCLUSION: We found that non-Hispanic Black compared with non-Hispanic White enrollees were more likely to obtain screening for CRC. Continued efforts to promote health and wellness of WTC-exposed population is essential.