Spatialising urban health vulnerability: An analysisof NYC’s critical infrastructure during COVID-19

Urban Studies ◽  
2021 ◽  
pp. 004209802110443
Author(s):  
Gayatri Kawlra ◽  
Kazuki Sakamoto
Keyword(s):  
New York ◽  
New York City ◽  
Urban Health ◽  
York City ◽  
Open Space ◽  
Critical Infrastructure ◽  
Health Care Facilities ◽  
Supervised Machine Learning ◽  
Grocery Stores ◽  
Health Vulnerability

This paper examines how fragmentation of critical infrastructure impacts the spread of the coronavirus outbreak in New York City at the neighbourhood level. The location of transportation hubs, grocery stores, pharmacies, hospitals and parks plays an important role in shaping spatial disparities in virus spread. Using supervised machine learning and spatial regression modelling we examine how the geography of COVID-19 case rates is influenced by the spatial arrangement of four critical sectors of the built environment during the public health emergency in New York City: health care facilities, mobility networks, food and nutrition and open space. Our models suggest that an analysis of urban health vulnerability is incomplete without the inclusion of critical infrastructure metrics in dense urban geographies. Our findings show that COVID-19 risk at the zip code level is influenced by (1) socio-demographic vulnerability, (2) epidemiological risk, and (3) availability and access to critical infrastructure.

scholarly journals Addressing Urban Health in Detroit, New York City, and Seattle Through Community-Based Participatory Research Partnerships

2003 ◽  
Vol 93 (5) ◽  
pp. 803-811 ◽  
Author(s):  
Marilyn M. Metzler ◽  
Donna L. Higgins ◽  
Carolyn G. Beeker ◽  
Nicholas Freudenberg ◽  
Paula M. Lantz ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Participatory Research ◽  
Urban Health ◽  
York City ◽  
Community Based Participatory Research ◽  
Community Based ◽  
Research Partnerships

scholarly journals Using Dental Health Care Personnel During a Crisis

2021 ◽  
Vol 136 (2) ◽  
pp. 143-147
Author(s):  
Victor Badner ◽  
Mana Saraghi
Keyword(s):  
Health Care ◽  
New York ◽  
New York City ◽  
York City ◽  
Health Care Facilities ◽  
Health Care Personnel ◽  
Staff Members ◽  
Dental Staff ◽  
Wide Range ◽  
Step Down

The first few months of the coronavirus disease 2019 (COVID-19) pandemic challenged health care facilities worldwide in many ways. Inpatient and intensive care unit (ICU) beds were at a premium, and personnel shortages occurred during the initial peak of the pandemic. New York State was the hardest hit of all US states, with a high concentration of cases in New York City and, in particular, Bronx County. The governor of New York and leadership of hospitals in New York City called upon all available personnel to provide support and patient care during this health care crisis. This case study highlights the efforts of Jacobi Medical Center, located in the northeast Bronx, from March 1 through May 31, 2020, and its use of nontraditional health care personnel, including Department of Dentistry/OMFS (Oral and Maxillofacial Surgery) staff members, to provide a wide range of health care services. Dental staff members including ancillary personnel, residents, and attendings were redeployed and functioned throughout the facility. Dental anesthesiology residents provided medical services in support of their colleagues in a step-down COVID-19–dedicated ICU, providing intubation, ventilator management, and critical and palliative care. (Step-down units provide an intermediate level of care between ICUs and the general medical–surgical wards.) Clear communication of an acute need, a well-articulated mission, creative use of personnel, and dedicated staff members were evident during this challenging time. Although not routinely called upon to provide support in the medical and surgical inpatient areas, dental staff members may provide additional health care personnel during times of need.

scholarly journals Fostering food equity in an immigrant neighborhood of New York City during COVID-19

2020 ◽  
pp. 1-5
Author(s):  
Valerie Imbruce
Keyword(s):  
New York ◽  
New York City ◽  
Urban Space ◽  
York City ◽  
Grocery Stores ◽  
Production Distribution ◽  
Food Equity ◽  
The Right ◽  
The City ◽  
Immigrant Neighborhoods

Food equity includes the right to food that is cul­turally appropriate. Immigrant neighborhoods can be sites of contestation over who participates in the production, distribution, and consumption of food. Manhattan’s Chinatown is a good example of a neighborhood where food is central to its com­merce, cultural heritage, and reputation as a tourist destination. The coronavirus’ origin in China caused imme­diate material impact on Chinese restaurants and food purveyors in New York City as well as in other cities with major populations of Chinese people. Chinatown suffered disproportionate closures of its grocery stores, restaurants, and produce vendors due to COVID-19 as compared to other neighbor­hoods in NYC. The grassroots response to this crisis is a reminder that people have the power to use food to assert the society that they desire, to shape a highly contested urban space, and to claim their right to the city.

Modeling the impacts of park access on health outcomes: A utility-based accessibility approach

2020 ◽  
pp. 239980832097402
Author(s):  
Gregory S Macfarlane ◽  
Nico Boyd ◽  
John E Taylor ◽  
Kari Watkins
Keyword(s):  
Physical Activity ◽  
New York ◽  
New York City ◽  
Health Outcomes ◽  
York City ◽  
Open Space ◽  
Choice Theory ◽  
Negative Relationship ◽  
Space Data ◽  
The Impact

Recent research has underscored the potential for public green spaces to influence individual and societal health outcomes, but empirical measurements of such influences have yielded mixed results to date, with particular disagreement surrounding how access to parks ought to be defined while controlling for alternate explanations. In this paper, we apply a comprehensive measure of park accessibility drawn from random utility choice theory, which avoids arbitrary assertions of proximity while incorporating potentially numerous amenities and attributes of both the parks and the population. We apply this utility-based accessibility measure to correlate Census tract-level obesity and physical activity rate estimates from the Centers for Disease Control and Prevention’s 500 Cities project with tract-level American Community Survey socioeconomic data in New York City, paired with geographic open space data from New York City. Controlling for the socioeconomic variables and spatially correlated error terms, we show a positive and significant relationship between park access and physical activity rates. The data also suggest a negative relationship between park access and obesity rates, beyond what is expected through physical activity and socioeconomics. In doing so, this research contributes a more comprehensive modeling approach for measuring the impact of park access on health, and may improve our understanding of the role parks and access to them can serve in furthering public health objectives.

scholarly journals Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City

2021 ◽  
Vol 10 (16) ◽  
pp. 3523
Author(s):  
Jason Zucker ◽  
Angela Gomez-Simmonds ◽  
Lawrence J. Purpura ◽  
Sherif Shoucri ◽  
Elijah LaSota ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Supervised Machine Learning ◽  
Symptom Duration ◽  
Control Analysis ◽  
Care Hospital ◽  
Cart Analysis ◽  
Poor Outcome ◽  
Increased Risk

Background: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. Methods: We performed a nested case–control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were used to identify predictors of poor outcome. Results: Patients presenting to the hospital earlier in their disease course were older, had more comorbidities, and a greater proportion decompensated (<4 days, 41%; 4–8 days, 31%; >8 days, 26%). The first recorded oxygen delivery method was the most important predictor of decompensation overall in CART analysis. In patients with symptoms for <4, 4–8, and >8 days, requiring at least non-rebreather, age ≥ 63 years, and neutrophil/lymphocyte ratio ≥ 5.1; requiring at least non-rebreather, IL-6 ≥ 24.7 pg/mL, and D-dimer ≥ 2.4 µg/mL; and IL-6 ≥ 64.3 pg/mL, requiring non-rebreather, and CRP ≥ 152.5 mg/mL in predictive models were independently associated with poor outcome, respectively. Conclusion: Symptom duration in tandem with initial clinical and laboratory markers can be used to identify patients with COVID-19 at increased risk for poor outcomes.

Critical infrastructure interdependence in New York City during Hurricane Sandy

2016 ◽  
Vol 7 (2) ◽  
pp. 133-143 ◽  
Author(s):  
Masahiko Haraguchi ◽  
Soojun Kim
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Critical Infrastructure ◽  
Hurricane Sandy ◽  
Electricity Sector ◽  
Gis Mapping ◽  
Critical Infrastructures ◽  
Content Type ◽  
The Impact

Purpose This study aims to investigate the impact of Hurricane Sandy from the perspective of interdependence among different sectors of critical infrastructure in New York City and to assess the interconnected nature of risks posed by such a hurricane. Design/methodology/approach This study uses indirect damages of each sector to estimate the degree of functional interdependence among the sectors. The study examines the impact of the hurricane on different critical infrastructures by combining hazard maps of actual inundation areas with maps of critical infrastructure. The direct damages of each sector are calculated from the inundation areas in the flood map. The indirect damages are estimated by considering the areas that were not inundated but affected by Sandy through the interconnected infrastructure. Findings The electricity sector was the key sector to propagate risks to other sectors. The examination of new initiatives to increase the resilience of critical infrastructures in New York City after Sandy reveals that these initiatives focus primarily on building hard infrastructures to decrease direct damages. They understate the importance of interdependent risk across sectors. Future disaster risk reduction strategies must address interdependent infrastructures to reduce indirect damages. Originality/value This paper focuses on estimating the direct and indirect damages caused by Hurricane Sandy in each critical infrastructure sector, using GIS mapping techniques. It also introduces a Bayesian network as a tool to analyze critical infrastructure interdependence.

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