Assessing capacity to social distance and neighborhood-level health disparities during the COVID-19 pandemic

Carrión, Daniel; Colicino, Elena; Nf, Pedretti; Kb, Arfer; Rush, Johnathan; DeFelice, Nicholas; Ac, Just

doi:10.1101/2020.06.02.20120790

Cited by 33 publications

(41 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the results may not be generalizable to areas where public transportation is not available, especially in rural Louisiana. In New York, Carrion et al reported higher subway ridership among individuals who reside in neighborhoods where COVID-19 cases were higher [24]. Utility disruption is another risk factor that potentially increases the individual's risk of contracting COVID-19.…”

Section: Plos Onementioning

confidence: 99%

“…Those who reside in deprived neighborhoods, defined by low income and education, higher unemployment, and substandard living conditions, have a greater risk of poor health outcomes such as obesity, diabetes, cancer, and heart diseases [21][22][23]. Higher incidence and mortality from COVID-19 have also been observed in low-income or deprived neighborhoods [24][25][26]. A study conducted by Bilal et al reported a 36% higher incidence of COVID-19 infection in deprived neighborhoods compared to less deprived neighborhoods [25].…”

Section: Introductionmentioning

confidence: 99%

“…Deprived neighborhoods are correlated with health risk behaviors, overcrowding, less social cohesion, and higher levels of environmental pollutants and have been identified as critical social determinants of health [34][35][36][37]. Low socioeconomic status (SES), often regarded as a fundamental cause of disease, has been shown to increase the risk of COVID-19 because it impacts access to fundamental resources that an individual or a neighborhood may require to avoid COVID-19 [24,38].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The effect of area deprivation on COVID-19 risk in Louisiana

Oral

Straif-Bourgeois

et al. 2020

PLoS ONE

View full text Add to dashboard Cite

Background Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana. Methods The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The data were extracted from the American Community Survey (ACS) 2018. The neighborhoods were categorized into quintiles as well as low and high deprivation. The publicly available COVID-19 cumulative case counts by census tract were obtained from the Louisiana Department of Health website on July 31, 2020. Descriptive and Poisson regression analyses were performed. Results Neighborhoods in Louisiana were substantially different with respect to deprivation. The ADI ranged from 136.00 for the most deprived neighborhood and –33.87 in the least deprived neighborhood. We observed that individuals residing in the most deprived neighborhoods had almost a 40% higher risk of COVID-19 compared to those residing in the least deprived neighborhoods. Conclusion While the majority of previous studies were focused on very limited socio-environmental factors such as crowding and income, this study used a composite area-based deprivation index to examine the role of neighborhood environment on COVID-19. We observed a positive relationship between neighborhood deprivation and COVID-19 risk in Louisiana. The study findings can be utilized to promote public health preventions measures besides social distancing, wearing a mask while in public and frequent handwashing in vulnerable neighborhoods with greater deprivation.

show abstract

Section: Plos Onementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The effect of area deprivation on COVID-19 risk in Louisiana

Oral

Straif-Bourgeois

et al. 2020

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Some of these differences reflect the living and social conditions faced by racial/ethnic minorities. For instance, institutional racism that produced residential segregation may increase the likelihood that racial/ethnic minorities live in densely populated areas with substandard and crowded housing conditions impede social distancing [ 7 , 8 ]. A recent analysis suggested that counties that are predominately black have three times the infection rate of COVID-19 compared to white majority counties [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases

Nguyen

Huang

Kumar

et al. 2020

IJERPH

View full text Add to dashboard Cite

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents’ risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

show abstract

“…As a member of the largest public hospital network in the United States, we used resource sharing across public hospitals to balance patient load from disproportionately affected facilities in Queens and Brooklyn (Table 1 ). These were hospitals catering to communities that were affected in a disproportionate manner ( 42 ). This was done in a coordinated manner, with information regarding institution’s ICU capacity being shared in a seamless manner ( Supplement 1 , http://links.lww.com/CCX/A284 ).…”

Section: Discussionmentioning

confidence: 99%