skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Pandemic Injustice: Spatial and Social Distributions of COVID-19 in the US Epicenter
We examine the uneven social and spatial distributions of COVID-19 and their relationships with indicators of social vulnerability in the U.S. epicenter, New York City (NYC). As of July 17th, 2020, NYC, despite having only 2.5% of the U.S. population, has [Formula: see text]6% of all confirmed cases, and [Formula: see text]16% of all deaths, making it a key learning ground for the social dynamics of the disease. Our analysis focuses on the multiple potential social, economic, and demographic drivers of disproportionate impacts in COVID-19 cases and deaths, as well as population rates of testing. Findings show that immediate impacts of COVID-19 largely fall along lines of race and class. Indicators of poverty, race, disability, language isolation, rent burden, unemployment, lack of health insurance, and housing crowding all significantly drive spatial patterns in prevalence of COVID-19 testing, confirmed cases, death rates, and severity. Income in particular has a consistent negative relationship with rates of death and disease severity. The largest differences in social vulnerability indicators are also driven by populations of people of color, poverty, housing crowding, and rates of disability. Results highlight the need for targeted responses to address injustice of COVID-19 cases and deaths, importance of recovery strategies that account for differential vulnerability, and provide an analytical approach for advancing research to examine potential similar injustice of COVID-19 in other U.S. cities. Significance Statement Communities around the world have variable success in mitigating the social impacts of COVID-19, with many urban areas being hit particularly hard. Analysis of social vulnerability to COVID-19 in the NYC, the U.S. national epicenter, shows strongly disproportionate impacts of the pandemic on low income populations and communities of color. Results highlight the class and racial inequities of the coronavirus pandemic in NYC, and the need to unpack the drivers of social vulnerability. To that aim, we provide a replicable framework for examining patterns of uneven social vulnerability to COVID-19- using publicly available data which can be readily applied in other study regions, especially within the U.S.A. This study is important to inform public and policy debate over strategies for short- and long-term responses that address the injustice of disproportionate impacts of COVID-19. Although similar studies examining social vulnerability and equity dimensions of the COVID-19 outbreak in cities across the U.S. have been conducted (Cordes and Castro 2020, Kim and Bostwick 2002, Gaynor and Wilson 2020; Wang et al. 2020; Choi and Unwin 2020), this study provides a more comprehensive analysis in NYC that extends previous contributions to use the highest resolution spatial units for data aggregation (ZCTAs). We also include mortality and severity rates as key indicators and provide a replicable framework that draws from the Centers for Disease Control and Prevention’s Social Vulnerability indicators for communities in NYC.  more » « less
Award ID(s):
1934933
PAR ID:
10223542
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Journal of Extreme Events
ISSN:
2345-7376
Page Range / eLocation ID:
2150007
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; (, Science Advances)
    null (Ed.)
    Assessing the effects of early nonpharmaceutical interventions on coronavirus disease 2019 (COVID-19) spread is crucial for understanding and planning future control measures to combat the pandemic. We use observations of reported infections and deaths, human mobility data, and a metapopulation transmission model to quantify changes in disease transmission rates in U.S. counties from 15 March to 3 May 2020. We find that marked, asynchronous reductions of the basic reproductive number occurred throughout the United States in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same measures been implemented 1 to 2 weeks earlier, substantial cases and deaths could have been averted and that delayed responses to future increased incidence will facilitate a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive control in combatting the COVID-19 pandemic. 
    more » « less
  2. ; ; (, Journal of Urban Health)
    Abstract Overdose deaths involving fentanyl represent a major public health crisis in the USA. This study investigates the spatiotemporal dynamics of fentanyl-involved deaths before, during, and after the COVID-19 pandemic and examines how sociodemographic factors influence these deaths across geographic regions. Using a retrospective ecological approach, we analyzed data on ZIP code-level fentanyl-related deaths in Cook County, IL, between 2018 and 2023, obtained from the Medical Examiner’s Office and linked with sociodemographic data from the American Community Survey. We first mapped area-level death rates to assess their distribution and then conducted global and local clustering analyses to identify spatial autocorrelations and the locations of high- or low-death-rate areas. A geographically weighted Poisson regression (GWPR) model evaluated the associations between area-level fentanyl-related death rates and the area-level proportion of young adults, males, and individuals with at least a college degree, disability rate, and poverty rate. Spatial analyses found stronger spatial autocorrelations during (2020–2021) and after (2022–2023) the pandemic. Initially, high death rates were concentrated in the downtown area of Chicago, and they expanded to the surrounding areas during and after the pandemic. The GWPR model revealed that an increase in the area-level proportions of poverty, disability, and young adult residents increased the fentanyl-related death rates in most of the areas. Our findings highlight the urgent need to address the evolving dynamics of fentanyl-related overdoses through tailored public health interventions that account for the unique socioeconomic determinants of different regions. Importantly, a comprehensive approach to addressing differences in overdose death rates and their risk factors will be crucial to mitigating this public health crisis. 
    more » « less
  3. ; ; ; ; ; ; ; ; ; ; et al (, Health Data Science)
    null (Ed.)
    Background . New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. Methods . We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. Results . A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. Conclusions . Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources. 
    more » « less
  4. ; ; ; ; ; ; (, International Journal of Infection Control)
    The coronavirus disease 2019 (COVID-19) has caused devastating public health, economic, political, and societal crises. We performed a comparison study of COVID-19 outbreaks in states with Republican governors versus states with Democratic governors in the United States between April 2020 and February 2021. This research study shows that 1) states with Democratic governors had tested more people for COVID-19 and have higher testing rates than those with Republican governors; 2) states with Democratic governors had more confirmed cases for COVID-19 from April 12 until the end of July 2020, as well as from early December 2020 to February 22 2021, and had higher test positivity rates from April 12 until late June 2020, and the states with Republican governors had more confirmed cases from August to early December 2020 and had higher test positivity rates since late June 2020; 3) states with Democratic governors had more deaths for COVID-19 and higher mortality rates than those with Republican governors; 4) more people recovered in states with Democratic governors until early July 2020, while the recovery rate of states with Republican governors is similar to that of states with Democratic governors in May 2020 and higher than that of states with Democratic governors in April 2020 and between June 2020 to February 22 2021. We conclude that our data suggest that states with Republican governors controlled COVID-19 better as they had lower mortality rates and similar or higher recovery rates. States with Democratic governors first had higher test positivity rates until late June 2020 but had lower test positivity rates after July 2020. As of February 2021, the pandemic was still spreading as the daily numbers of confirmed cases and deaths were still high, although the test positivity and mortality rates started to stabilize in spring 2021. This study provides a direct description for the status and performance of handling COVID-19 in the states with Republican governors versus states with Democratic governors, and provides insights for future research, policy making, resource distribution, and administration. 
    more » « less
  5. ; ; ; (, SIAM Conference on Applied and Computational Discrete Algorithms)
    Coronavirus Disease 2019 (Covid-19) is an ongoing outbreak and the latest threat to global health. It is imperative to understand the implications of social interaction on Covid-19 indicators in order to help formulate policies and guidelines by governments and local authorities. We present a case-study of curating state-level Covid-19 indicators such as Active Cases, Deaths, Hospitalization Rate, etc. for the United States. We also curate open source domestic US air travel data and present its impact on Covid-19 indicators. We perform a time-series analysis of the dataset using Independent Temporal Motif (ITeM) to find weekly trends in the data. We publish the dataset and the results for further exploration by the research community. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email