York City Research Articles

Advancing urban climate adaptation through knowledge exchange: A case study of New York City

Cities are experiencing increasingly extreme and longer-lasting hazards due to climate change. In response, urban decision-makers use climate assessments to inform their adaptation programs. To effectively inform planning, climate assessments must be responsive to community priorities and align with information needs. However, there are few empirical studies evaluating the co-production and exchange of climate information within climate assessment processes. To address this gap, we evaluated the Climate Knowledge Exchange (CKE) piloted in 2020 by the Mayor's Office of Climate and Environmental Justice (then the Mayor's Office of Resiliency) in New York City. The CKE is an ongoing engagement process that asked: What are the research gaps and barriers to adaptation in New York City and how can we design inclusive approaches to knowledge exchange that advance equitable adaptation? To answer this question, we facilitated group discussions, distributed surveys, and reviewed adaptation plans to assess the state of climate knowledge. The findings indicate a need for contextually and culturally sensitive approaches to the co-development of actionable knowledge. Additionally, there is a need to reduce barriers to equitable adaptation and to advance the practice of climate-informed decision-making. Our findings advance understanding of the potential role of climate knowledge exchange in adaptation planning.

Measuring the social effects of urban logistics facilities development, the case of New York city

ABSTRACT With customers expecting near-immediate deliveries, there has been a growth of heterogeneous networks of proximity logistics facilities within urban centers. Although resulting in higher operational efficiency, this trend challenges traditional planning paradigms and generates externalities for communities. This research provides an approach to analyze the effects of facility development in communities, using the case of New York City. Published information and public data sources are used to identify the location and type of facilities. Census data allows the calculation of existing vulnerability near the identified areas, and labor indicators present local trends in proximity-logistics-related sectors. Results show that logistics facilities are in areas where the population is vulnerable. However, new warehouse trends do not follow this tendency and can escape zoning codes. As a result, the quest for faster deliveries challenges existing planning processes. Job changes vary by location and over time, demonstrating inconsistency and sometimes volatility in worker effects.

A (Dis)orderly Progression: The Lasting Impact of Pandemic on Community-Based Organizations

ABSTRACT Community-based organizations (CBOs) serving older ethnic minority adults, especially older immigrants, are vital to satisfy their complex social, health, and behavioral health needs. This study uses organizational theories and a case study approach to examine how the organizational responses to the multifaceted impact of the COVID-19 pandemic and progress beyond the pandemic-related responses. Four CBOs serving older Chinese immigrants in New York City were examined. Results indicate that driven by unmet psychosocial needs of older Chinese immigrants and public health measures, CBOs modified practice protocols and established (or strengthened) collaborative relationships with medical providers and other CBOs. COVID-19 responses include CBOs’ transformations in organizational structures (e.g. collaboration) and operational activities (e.g. telehealth). Successful transformations of CBOs were primarily due to prior adaptiveness to integrated care reform and assured needed resources before the pandemic; the transformation reflected orderly organizational progress rather than a temporary management strategy.

Community design of the Brooklyn Health Equity Index

Abstract Health equity drives quality care. Few reliable metrics that capture patients’ perceptions of health equity exist. We report on the development of a patient-centered metric for health systems change in central Brooklyn, which stands out as an outlier in New York City with a disproportionate burden of poverty, disease, and death. A community-engaged, sequential, mixed-methods research design was used. Qualitative interviews were conducted with 80 community and health care stakeholders across central Brooklyn. Candidate items were derived from qualitative themes and examined for face, interpretive validity, and language. Interitem reliability and confirmatory factor analysis was assessed using data collected via text and automated discharge calls among 368 patients from a local hospital. Qualitative data analysis informed the content of 11 draft questions covering 3 broad domains: trust-building, provider appreciation of social determinants of health, and experiences of discrimination. Psychometric testing resulted in a Cronbach's alpha of 0.774 and led to deletion of 1 item, resulting in a 10-item Brooklyn Health Equity Index (BKHI). The 10-item BKHI is a novel, brief, and reliable measure that captures patients’ perceptions of inequities and offers a real-time measure for health systems and payors to monitor progress toward advancing health equity.

Using Digital Storytelling and Social Media to Combat COVID-19 Vaccine Hesitancy: A Public Service Social Marketing Campaign.

Disparities in vaccine confidence and uptake among racial and ethnic minorities have resulted in a disproportionate burden of COVID-19 in these populations. Social media campaigns have shown promise in public health promotion and behavioral interventions. In January 2022, an academic-community partnership launched #Vax4Community, a 6-month social media campaign centered around the use of digital storytelling videos. The campaign purpose was to decrease vaccine hesitancy, combat vaccine misinformation and disinformation, and increase vaccine confidence within three distinct target communities: the justice-involved population, South Asian residents, and public housing youth in the metropolitan area of New York City (NYC). Our approach included the production and dissemination of digital storytelling videos featuring personal vaccine experiences from target populations. We evaluated key performance indicators (KPIs) of the campaign, including post impressions, reach and engagement across social media platforms, and shares from partner organizations. Overall, we received 1,910,662 post impressions, 699,722 unique users reached, and 2,880 post engagements across Instagram, Facebook, LinkedIn, and Twitter, and 147 shares from 48 partner organizations. Social media campaigns require strategic design in branding, messaging and outreach channels and could serve as an important tool to disseminate emotionally relatable content and trusted information to prime target populations to respond more optimally to public health interventions. The purpose of this paper is to describe the process of creating and disseminating these digital stories and the KPIs of the social media campaign.

Optimizing the microbial community composition in anaerobic digesters to improve biogas yields from food waste

Methods: Food waste collected from local restaurants and households in New York city will be used in this study. The food waste will be characterized to analyze its composition. Batch anaerobic digesters will be inoculated with microbial communities from existing food waste digesters. DNA analysis using 16S rRNA gene sequencing will be done to show the initial microbial consortia. Various perturbations will be applied to the digesters including changes in temperature, pH, feeding rates, mixing intensities to select for microbial populations yielding higher biogas production. Biogas production will be monitored over time. DNA analysis will be repeated after perturbation to analyze changes in the microbial community structure. Results: Preliminary results show Food waste characterized was found to contain 35% proteins, 45% carbohydrates and 20% fats. The initial microbial consortia in the digesters was dominated by bacteria from the genera Clostridium, Bacteroides and Methanothermobacter. Increasing feeding rates led to a 40% increase in biogas yields. Microbial analysis indicated a shift in populations with Clostridium becoming the most abundant genus. Decreasing pH from 7 to 6.5 further enhanced biogas by 25% with Clostridium and Syntrophomonas becoming dominant. Discussion: The study demonstrates that optimizing operational conditions can effectively manipulate the microbial communities in anaerobic digesters processing food waste. By applying selective pressures, populations better suited to degrade the local food waste and produce higher methane yields can be enriched. Further experiments will aim to construct stable, optimized consortia through controlled perturbation for robust and efficient food waste digestion. The approach holds promise for improving biogas production from food waste globally

StreetTalk: exploring energy insecurity in New York City using a novel street intercept interview and social media dissemination method

This study introduces StreetTalk, an original qualitative research methodology inspired by social media influencers, to investigate perceptions and experiences of energy insecurity among New York City (NYC) residents. Briefly, energy insecurity is defined as difficulty meeting household energy needs due to affordability, housing quality, outages and coping strategies. This present study employs dynamic short-form interviews with 34 participants from all five NYC boroughs of diverse economic, and racial/ethnic backgrounds. Thematic analysis of video-recorded interviews revealed six major energy insecurity-related categories: (1) conservation and trade-offs, (2) physical inefficiencies, (3) thermal agency, (4) response to the bill, (5) disappointment and distrust in energy-related authorities, and (6) desire for and barriers to clean energy adoption. These themes provide insight into NYC residents’ experiences with energy insecurity and are consistent with prior research. Beyond new scholarly insights, this study introduces StreetTalk, an innovative qualitative research methodology emphasizing rapid data collection and dissemination through social media platforms, including TikTok, Instagram, Facebook, and YouTube (@hotandcold_nyc). Taking advantage of modern technology and modes of communication, the research team was able to effectively break down barriers to academic research consumption as the videos achieved substantial engagement, with almost 200,000 views and impressions within the first year of launching this novel street-based data collection and social media dissemination campaign.

A sequential transit network design algorithm with optimal learning under correlated beliefs

Mobility service route design requires demand information to operate in a service region. Transit planners and operators can access various data sources including household travel survey data and mobile device location logs. However, when implementing a mobility system with emerging technologies, estimating demand becomes harder because of limited data resulting in uncertainty. This study proposes an artificial intelligence-driven algorithm that combines sequential transit network design with optimal learning to address the operation under limited data. An operator gradually expands its route system to avoid risks from inconsistency between designed routes and actual travel demand. At the same time, observed information is archived to update the knowledge that the operator currently uses. Three learning policies are compared within the algorithm: multi-armed bandit, knowledge gradient, and knowledge gradient with correlated beliefs. For validation, a new route system is designed on an artificial network based on public use microdata areas in New York City. Prior knowledge is reproduced from the regional household travel survey data. The results suggest that exploration considering correlations can achieve better performance compared to greedy choices and other independent belief-based techniques in general. In future work, the problem may incorporate more complexities such as demand elasticity to travel time, no limitations to the number of transfers, and costs for expansion.

Lessons Learned from the Launch and Implementation of the COVID-19 Contact Tracing Program in New York City: a Qualitative Study.

On June 1, 2020, NYC Health + Hospitals, in partnership with the NYC Department of Health and Mental Hygiene, other city agencies, and a large network of community partners, launched the New York City Test & Trace (T2) COVID-19 response program to identify and isolate cases, reduce transmission through contact tracing, and provide support to residents during isolation or quarantine periods. In this paper, we describe lessons learned with respect to planning and implementation of case notification and contact tracing. Our findings are based on extensive document review and analysis of 74 key informant interviews with T2 leadership and frontline staff, cases, and contacts conducted between January and September 2022. Interviews elicited respondent background, history of program development, program leadership and structure, goals of the program, program evolution, staffing, data systems, elements of community engagement, trust with community, program reach, timeliness, equity, general barriers and challenges, general facilitators and best practices, and recommendations/improvement for the program. Facilitators and barriers revealed in the interviews primarily revolved around hiring and managing staff, data and technology, and quality of interactions with the public. Based on these facilitators and barriers, we identify suggestions to support effective planning and response for future case notification and contact tracing programs, including recommendations for planning during latent periods, case management and data systems, and processes for outreach to cases and contacts.

Evaluation of the New York City COVID-19 case investigation and contact tracing program: a cascade of care analysis

BackgroundNew York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country’s largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a “cascade of care” approach.MethodsThis cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the “cascade of care” was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case’s date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact.ResultsA total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and < 1 day to notify contacts.ConclusionsT2 provided a large volume of NYC residents with timely notification and monitoring. Engagement in the program was lower for contacts than cases, with the largest gap coming from inability to reach individuals during call attempts. To strengthen future test-and-trace efforts, strategies are needed to encourage acceptance of local contact tracer outreach attempts.

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

The disease burden of sickle cell disease (SCD) is highest among U.S. Black and Hispanic populations, who are often disproportionately represented in communities with poor air quality. There is limited data on the effects of air pollution exposure and social environmental factors on health outcomes in children with SCD. The objective of our study was to examine the associations between air pollution exposure and acute respiratory and vaso-occlusive pain crises (VOCs), and further study the associations stratifying by asthma status and neighborhood disadvantages. We conducted a retrospective study collecting data on outpatient sick and ED visits, and hospital admissions for respiratory events (i.e., respiratory tract infections, asthma exacerbation, acute chest syndrome), and hospitalizations for VOCs among children with SCD in a tertiary care center in New York City (NYC) from 2015-2018. Modeled data from the NYC Community Air Survey data using home addresses estimated street-level, annual-average exposure to air pollution (i.e., black carbon (BC), fine particulate matter (PM2.5), and nitrogen dioxide (NO2)). The area deprivation index (ADI): continuous national ranking percentile (1-100) was used, representing a composite index for neighborhood-level social disadvantage. We further dichotomized study participants at the upper tertile (high vs. low ADI). Multivariable Poisson regression in generalized estimating equation (GEE) models were used to estimate relative risks (RR), after adjusting for potential covariates. A total of 114 children with SCD were included in this study and had between 1-4 annual repeated measures of annual average air pollutants over a total of 425 visits. Overall, there were no significant associations between air pollution levels and acute respiratory and VOCs among children with SCD and when stratified by asthma status. We found significant interactions between air pollution levels and the continuous ADI variable on respiratory outpatient and frequent respiratory outpatient/ED visits (p<0.1). When stratified by high ADI, increased exposure to PM2.5 was significantly associated with more frequent respiratory outpatient/ED visits among children residing in higher ADI neighborhoods (RR (95% CI)= 1.13 (1.01, 1.27), p<0.05), but not among those in lower ADI neighborhoods. Increased exposure to NO2 was associated with more outpatient respiratory events for children in high ADI neighborhoods (RR (95%CI= 2.74 (1.24, 6.08), p<0.05), compared with low ADI neighborhoods. Air pollution exposures increased respiratory complications among children with SCD living in deprived neighborhoods.

David Kahn, in remembrance: an INS special forum

ABSTRACT David Kahn was one of America’s leading experts on the history of cryptology, the art and science of breaking the communications codes, ciphers, and secret writing of hostile nations and terrorist organizations – a vital intelligence tradecraft for anticipating potentially dangerous operations of foreign adversaries. As both a journalist and a professional historian, he pursued scholarly interests in cryptology as well as modern German history. His most well-known book, entitled The Codebreakers, influenced the field of cryptology and attracted many young readers to this intelligence profession. Kahn wrote many other studies on the topic and founded the journal Cryptologia. He received an array of honors for his work, including induction into the National Security Agency’s Cryptologic Hall of Fame. In addition, Kahn was a popular social fixture at prestigious clubs in New York City and a member of several boards of editors devoted to Intelligence Studies, including this journal.

Implications for neurosurgery of medical schools leaving the United States News and World Report.

Ranked lists are a highly praised method of assessment in America. Whether it's a list of the top national sports teams, the best restaurants in New York City, or as in this case, the strongest educational institutions, we look to rankings to scrutinize, evaluate, and compare. Unfortunately, not all rankings offer insightful and valuable information. Many use metrics that fall short of an accurate representation of the desired outcome. The U.S. News & World Report (USNWR), one of the most widely regarded rankings of educational institutions, has recently been under the spotlight as several major medical schools have removed themselves from candidate lists. The current USNWR Medical School's rankings are regarded as having a narrow perspective in that the metrics perpetuate a less diverse medical community and fail to recognize worthy institutions that choose to champion a well-rounded student experience. The authors, along with the many others, fear this may deliver a skewed vision of what the USNWR tries to measure: the excellence of a medical education.

Generating sparse origin–destination flows on shared mobility networks using probabilistic graph neural networks

Shared mobility services, such as bike sharing, have gained immense popularity and emerged as an integral part of sustainable urban mobility solutions. The planning of such systems requires forecasting the potential origin–destination (OD) flows between mobility sites (e.g., bike sharing stations) within the proposed network. Existing methods primarily focus on mobility flows between large regions, and do not generalize well to detailed planning applications due to the high spatial resolution required, with increased uncertainty and data sparsity. This study proposes a zero-inflated negative binomial graph neural network (ZINB-GNN) to generate sparse OD flows while capturing complex spatial dependencies. To reflect sparsity, OD flows are modeled as following ZINB distributions parameterized via feed-forward networks. To capture spatial dependencies, localized graphs are constructed to represent proximity between OD pairs, with spatial features encoded using GNNs. ZINB-GNN is validated through a case study of the bike sharing system in New York City. The results verify its prowess in both prediction accuracy and uncertainty quantification under real-world network expansion scenarios. We also demonstrate its interpretability by revealing important factors affecting OD flows. These findings can directly inform the planning of bike sharing systems, and the methodology may be adapted for other shared mobility systems.

The COVID-19 Disparities Grant: A Lesson in Radical Place-Based Investment to Overcome COVID-19-Related Health Disparities.

The COVID-19 pandemic highlighted and exacerbated health inequities in New York City (NYC) given the disproportionate risk, morbidity, and mortality related to COVID-19 experienced by communities of color with lower household income. To facilitate long-term community recovery from COVID-19, the NYC Department of Health and Mental Hygiene established the Public Health Corp, a partnership with community-based organizations staffed by community health workers in neighborhoods disproportionately impacted by COVID-19. (Am J Public Health. Published online ahead of print August 28, 2024:e1-e4. https://doi.org/10.2105/AJPH.2024.307766).

Overcoming engagement shortfalls and financial constraints in Small and Medium Enterprises (SMES) social media advertising through cost-effective Instagram strategies in Lagos and New York City

This research explores the challenges faced by Small and Medium Enterprises (SMEs) in leveraging social media advertising, with a focus on engagement shortfalls and financial constraints. The study compares the strategies employed by SMEs in Lagos, Nigeria, and New York City, USA, to overcome these challenges, highlighting the impact of these strategies on business growth and customer loyalty. Through a cross-cultural analysis, this research identifies cost-effective practices that can enhance social media engagement and optimize advertising expenditures for SMEs in diverse economic environments. The findings reveal that while social media platforms offer significant opportunities for SMEs, success is often hindered by limited resources, inadequate content strategies, and the rapidly changing dynamics of social media platforms. This study provides actionable insights for SMEs seeking to maximize their social media presence, offering recommendations for improving engagement and overcoming financial barriers. Keywords: Social Media Advertising, Small and Medium scale Enterprises (SMEs), Engagement Shortfalls, Financial Constraints, Cross-Cultural Study, Lagos, Nigeria and New York City, USA, Cost-Effective Strategies.

Examining human mobility changes during COVID-19 across socioeconomic groups: a comparative analysis of San Diego County and New York City

The COVID-19 pandemic brought unprecedented changes to various aspects of daily life, profoundly affecting human mobility. These changes in mobility patterns were not uniform, as numerous factors, including public health measures, socioeconomic status, and urban infrastructure, influenced them. This study examines human mobility changes during COVID-19 in San Diego County and New York City, employing Latent Profile Analysis (LPA) and various network measures to analyze connectivity and socioeconomic status (SES) within these regions. While many COVID-19 and mobility studies have revealed overall reductions in mobility or changes in mobility patterns, they often fail to specify ’where’ these changes occur and lack a detailed understanding of the relationship between SES and mobility changes. This creates a significant research gap in understanding the spatial and socioeconomic dimensions of mobility changes during the pandemic. This study aims to address this gap by providing a comprehensive analysis of how mobility patterns varied across different socioeconomic groups during the pandemic. By comparing mobility patterns before and during the pandemic, we aim to shed light on how this unprecedented event impacted different communities. Our research contributes to the literature by employing network science to examine COVID-19’s impact on human mobility, integrating SES variables into the analysis of mobility networks. This approach provides a detailed understanding of how social and economic factors influence movement patterns and urban connectivity, highlighting disparities in mobility and access across different socioeconomic groups. The results identify areas functioning as hubs or bridges and illustrate how these roles changed during COVID-19, revealing existing societal inequalities. Specifically, we observed that urban parks and rural areas with national parks became significant mobility hubs during the pandemic, while affluent areas with high educational attainment saw a decline in centrality measures, indicating a shift in urban mobility dynamics and exacerbating pre-existing socioeconomic disparities.

REAL ESTATE, PHOTOGRAPHY, AND CAPITALIST ABSTRACTION. ON EDGAR MARTINS’ THIS IS NOT A HOUSE, DANIEL SHEA’S 43-35 10TH STREET, AND LEWIS BUSH’S METROPOLE

The paper analyses three photographic bodies of work — Edgar Martins’ This Is Not a House, Daniel Shea’s 43-35 10th Street, and Lewis Bush’s Metropole — looking at various aspects of the real estate market: real estate collapse and the 2008 financial crisis in the USA, as well as real estate boom and gentrification in New York City and London. The case studies depict the real estate industry as an example of how invisible and abstract market processes shape visible and concrete domains of everyday life, such as, income inequalities, social relationships, or public space aesthetics. The artists in question use photography as a tool to deconstruct the abstractions of neoliberal capitalism through an attempt to visualise the invisible. By examining the three case studies in the light of economic theory on the real estate market, the paper defines links between neoliberal capitalism and the medium of photography using the idea of abstraction, and shows how photography is used to dissect the complexity of economic processes taking place within the realm of neoliberal capitalism.

SARS-CoV-2 infection in synanthropic rats from Guayaquil city (Ecuador) during COVID-19 pandemic: A proxy to prevent wild reservoirs in the tropics

Human-to-animal reverse transmission of SARS-CoV-2 is a risk for new reservoirs' emergence and new variants' evolution. SARS-CoV-2 infection of synanthropic rodents in urban settings has been reported during COVID-19 in New York and Mexico cities. In this study, we addressed the potential transmission of SARS-CoV-2 to synanthropic rats in the city of Guayaquil (Ecuador) during the COVID-19 pandemic. A total number of 234 rats were collected and analyzed for SARS-CoV-2 detection by RT-qPCR. A positivity rate of 6 % (14 rats) was found, and SARS-CoV-2 infection was confirmed by Sanger sequencing of the viral genome. Our results confirm the potential risk of synanthropic rats as reservoirs for SARS-CoV-2 infection. This is worrisome for low and middle income countries like Ecuador, where pest and waste control in urban settings is challenging. Moreover, the risk of spillover to wild fauna is a concern in Guayaquil, where synanthropic fauna includes raccoons or coatis and forest patches with a wild population of felids or primates existing within the city limits. In this context, SARS-CoV-2 sentinel surveillance of synanthropic rodents could serve as a proxy for a One Health approach to prevent the emergence of new wild reservoirs.

Navigating a "Good Death" During COVID-19: Understanding Real-Time End-of-Life Care Structures, Processes, and Outcomes Through Clinical Notes.

The coronavirus disease 2019 (COVID-19) pandemic severely disrupted hospice care, yet there is little research regarding how widespread disruptions affected clinician and family decision-making. We aimed to understand how the pandemic affected structures, processes, and outcomes of end-of-life care. Retrospective narrative chart review of electronic health records of 61 patients referred and admitted to hospice from 3 New York City geriatrics practices who died between March 1, 2020, and March 31, 2021. We linked longitudinal, unstructured medical, and hospice electronic health record notes to create a real-time, multiperspective trajectory of patients' interactions with providers using directed content analysis. Most patients had dementia and were enrolled in hospice for 11 days. Care processes were shaped by structural factors (staffing, supplies, and governmental/institutional policies), and outcomes were prioritized by care teams and families (protecting safety, maintaining high-touch care, honoring patient values, and supporting patients emotionally and spiritually). Processes used to achieve these outcomes were decision-making, care delivery, supporting a "good death," and emotional and spiritual support. Care processes were negotiated throughout the end of life, with clinicians and families making in-the-moment decisions. Some adaptations were effective but also placed extraordinary pressure on paid and family caregivers. Healthcare teams' and families' goals to meet patients' end-of-life priorities can be supported by ongoing assessment of patient goals and process changes needed to support them, stronger structural supports for paid and family caregivers, incentivizing relationships across primary care and hospice teams, and extending social work and spiritual care.