Neighborhood conditions and the initial outbreak of COVID-19: the case of Louisiana

Abstract

The early outbreak of coronavirus disease-2019 (COVID)-19 became associated with various ‘hot spots’ in the USA, particularly in large cities. However, despite the widespread nature of the outbreak, much of what is known about the virus’ impact and clusters is understood either for individuals, or at the state level. This paper assesses the predictors of outbreaks at the neighborhood level. Using data from the Louisiana Department of Health, we use spatial regression models to analyze the case count through 3 May 2020 and its relationship to individual and geographic neighborhood characteristics at the census tract level. We find a particularly strong and large correlation between race and COVID-19 cases, robust to model specification and spatial autocorrelation. In addition, neighborhoods with lower rates of poverty and those with fewer residents over 70 have fewer cases. Policy makers should adjust testing strategies to better service the hardest hit populations, particularly minorities and the elderly. In addition, the results are greater evidence of the impact of systemic issues on health, which require a long-term strategy for redress.

Seroprevalence of Novel Coronavirus SARS-CoV-2 at a Community Hospital Emergency Department and Outpatient Laboratory in Northern Orange County, California

“…However, the percent of the population that identifies as Hispanic/Latino in origin is 34% [7]. Previous reports have shown that racial minorities such as African American and Hispanics are disproportionately affected by COVID-19 as an association has been observed with these groups and acquisition of SARS-CoV-2 infection [8][9][10]. Data from the CDC Morbidity and Mortality Weekly Report from February to June 2020 only included one county in California, which may not be representative of other counties within the state [8].…”

The interplay of policy, behavior, and socioeconomic conditions in early COVID-19 epidemiology in Georgia

“…Counties with a larger share of residents who were Black or living below the poverty line experienced more cases and/or deaths, a pattern that may reflect disparities and systemic injustices connected to racism in healthcare, housing, and occupation in Georgia and across the United States. 6,8,21,35 These covariates may also indicate counties that have larger populations of workers who are unable to work from home and lack sufficient workplace protections. 12,36,37 Counties with lower median household income had higher mobility, potentially supporting this hypothesis (Supplement: Table S5, Fig.…”

“…20 For example, counties with low median household income and educational attainment and high unemployment and poverty rates are predicted to have larger working class populations who were limited in their ability to practice nonpharmaceutical interventions, while high housing density and air pollution may also indicate more urbanized areas with more rapid early spread. 21,22 Identifying predictors of worse early outbreaks and reduced ability to follow nonpharmaceutical interventions could guide future responses to emerging infectious diseases and inform ongoing COVID-19 response strategies.…”

Neighborhood-level Racial/Ethnic and Economic Inequities in COVID-19 Burden Within Urban Areas in the US and Canada

“…Studies to date have focused on particular cities individually, especially those that emerged as the first hotspots in the US (Benitez et al, 2020;Cordes and Castro, 2020;Lieberman-Cribbin et al, 2020, pp. 1-;Maroko et al, 2020;van Holm et al, 2020). In the past few months, many local jurisdictions have started disseminating case, death and testing data at postal-code level or for other small geographic areas.…”