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Diffusion segregation and the disproportionate incidence of COVID-19 in African American communities.

ABSTRACT: One of the most concerning aspects of the ongoing COVID-19 pandemic is that it disproportionately affects people from some specific ethnic and socio-economic minorities. In particular, since from the beginning of the pandemic it has been clear that people from Black and African American backgrounds seem to be hit especially hard by the virus, creating a substantial infection gap. The observed abnormal impact on these ethnic groups could probably be due to the co-occurrence of other known risk factors, including co-morbidity, poverty, level of education, access to healthcare, residential segregation and response to cures, although those factors do not seem able to explain fully and in depth the excess incidence of infections and deaths among African Americans. Here, we introduce the concept of diffusion segregation, that is the extent to which a given group of people is internally clustered or exposed to other groups, as a result of mobility and commuting habits. By analysing census and mobility data on major US cities, we found that the weekly excess COVID-19 incidence and mortality in African American communities at the beginning of the COVID-19 pandemic is significantly associated with their level of diffusion segregation. The results confirm that knowing where people commute to, rather than where they live, is potentially much more important to contain and curb the spreading of infectious diseases.

SUBMITTER: Bassolas A

PROVIDER: S-EPMC7879774 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Diffusion segregation and the disproportionate incidence of COVID-19 in African American communities.

Bassolas Aleix A Sousa Sandro S Nicosia Vincenzo V

Journal of the Royal Society, Interface 20210127 174

One of the most concerning aspects of the ongoing COVID-19 pandemic is that it disproportionately affects people from some specific ethnic and socio-economic minorities. In particular, since from the beginning of the pandemic it has been clear that people from Black and African American backgrounds seem to be hit especially hard by the virus, creating a substantial infection gap. The observed abnormal impact on these ethnic groups could probably be due to the co-occurrence of other known risk fa ...[more]

PMID: 33499765

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Project description:ImportanceThe novel Coronavirus Disease 2019 (COVID-19), declared a pandemic in March 2020, may present with disproportionately higher rates in underrepresented racial/ethnic minority populations in the United States, including African American communities who have traditionally been over-represented in negative health outcomes.Study objectiveTo understand the impact of the density of African American communities (defined as the percentage of African Americans in a county) on COVID-19 prevalence and death rate within the three most populous counties in each U.S. state and territory (n=152). Design: An ecological study using linear regression was employed for the study.SettingThe top three most populous counties of each U.S. state and territory were included in analyses for a final sample size of n=152 counties.ParticipantsConfirmed COVID-19 cases and deaths that were accumulated between January 22, 2020 and April 12, 2020 in each of the three most populous counties in each U.S. state and territory were included.Main outcome measuresLinear regression was used to determine the association between African American density and COVID-19 prevalence (defined as the percentage of cases for the county population), and death rate (defined as number of deaths per 100,000 population). The models were adjusted for median age and poverty.ResultsThere was a direct association between African American density and COVID-19 prevalence; COVID-19 prevalence increased 5% for every 1% increase in county AA density (p<.01). There was also an association between county AA density and COVID-19 deaths, such; the death rate increased 2 per 100,000 for every percentage increase in county AA density (p=.02).ConclusionThese study findings indicate that communities with a high African American density have been disproportionately burdened with COVID-19. Further study is needed to indicate if this burden is related to environmental factors or individual factors such as types of employment or comorbidities that members of these community have.

Project description:Abstract Epidemiological data across the United States of America illustrate health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. However, limited information is available from prospective observational studies in hospitalized patients, particularly for American Indian or Alaska Native (AI/AN) populations. Here, we present risk factors associated with severe COVID-19 and mortality in patients (4/2020–12/2021, n = 475) at the University of New Mexico Hospital. Data were collected on patient demographics, infection duration, laboratory measures, comorbidities, treatment(s), major clinical events, and in-hospital mortality. Severe disease was defined by COVID-related intensive care unit requirements and/or death. The cohort was stratified by self-reported race/ethnicity: AI/AN (30.7%), Hispanic (47.0%), non-Hispanic White (NHW, 18.5%), and Other (4.0%, not included in statistical comparisons). Despite similar timing of infection and comparable comorbidities, admission characteristics for AI/AN patients included younger age (P = 0.02), higher invasive mechanical ventilation requirements (P = 0.0001), and laboratory values indicative of more severe disease. Throughout hospitalization, the AI/AN group also experienced elevated invasive mechanical ventilation (P < 0.0001), shock (P = 0.01), encephalopathy (P = 0.02), and severe COVID-19 (P = 0.0002), consistent with longer hospitalization (P < 0.0001). Self-reported AI/AN race/ethnicity emerged as the highest risk factor for severe COVID-19 (OR = 3.19; 95% CI = 1.70–6.01; P = 0.0003) and was a predictor of in-hospital mortality (OR = 2.35; 95% CI = 1.12–4.92; P = 0.02). Results from this study highlight the disproportionate impact of COVID-19 on hospitalized AI/AN patients, who experienced more severe illness and associated mortality, compared to Hispanic and NHW patients, even when accounting for symptom onset and comorbid conditions. These findings underscore the need for interventions and resources to address health disparities in the COVID-19 pandemic.

Project description:BackgroundThe CoVID-19 pandemic underscored effects of community resources on the built environment, health and health outcomes. The purpose of this study was to conduct community-engaged research and examine aspects of health, and access to healthcare from the voices of community members, as a foundation for improving health equity through the built environment.MethodsThis study utilized a convergent mixed methods design that included surveys and semi-structured interviews conducted from July 2021 to August 2022 to examine the impact of limited community resources, such as community health clinics on participants during the CoVID-19 pandemic. A convenient sample of 345 male and female African American participants represented five zip codes (21215, 21216, 21217, 21223, and 21229) in with the highest impact from CoVID 19, in Baltimore, Maryland. Quantitative and qualitative data were integrated to describe how the two types supported one another in health, healthcare and healthcare access.ResultsMore than half of all participants reported satisfaction with overall health, quality of healthcare provided and access to health care services. However, results indicated extreme differences in factors related to health and wellness after, as comparted to before the onset of the pandemic, Semi-structured interviews, expanded on overall community health, highlighting that overall satisfaction with health does not equal satisfaction with health-related resources and suggested participants felt frustrated and left out of much-needed community health resources to improve health and mental health services for all ages, nutrition services and community activities that make communities thrive. Data integration provided a more realistic view of what participants really experience, due to the expanded analysis of semi-structured interviews, and indicated quantitative and qualitative data did not always support each other.ConclusionsFuture research to improve the built environment, and to address historic health inequities, will require ongoing community engagement to better understand community needs. This study results encourage ongoing research to expand resources for community-engaged research and interventions. Researchers must remain cognoscente of changing needs, and persistent disparities that can only be addressed if policies, supported by these results, are introduced to make equitable investments to forge an environment where healthy communities thrive.

Project description:IntroductionPreviously estimated effects of social distancing do not account for changes in individual behavior before the implementation of stay-at-home policies or model this behavior in relation to the burden of disease. This study aims to assess the asynchrony between individual behavior and government stay-at-home orders, quantify the true impact of social distancing using mobility data, and explore the sociodemographic variables linked to variation in social distancing practices.MethodsThis study was a retrospective investigation that leveraged mobility data to quantify the time to behavioral change in relation to the initial presence of COVID-19 and the implementation of government stay-at-home orders. The impact of social distancing that accounts for both individual behavior and testing data was calculated using generalized mixed models. The role of sociodemographics in accounting for variation in social distancing behavior was modeled using a 10-fold cross-validated elastic net (linear machine learning model). Analysis was conducted in April?July 2020.ResultsAcross all the 1,124 counties included in this analysis, individuals began to socially distance at a median of 5 days (IQR=3-8) after 10 cumulative cases of COVID-19 were confirmed in their state, with state governments taking a median of 15 days (IQR=12-19) to enact stay-at-home orders. Overall, people began social distancing at a median of 12 days (IQR=8-17) before their state enacted stay-at-home orders. Of the 16 studies included in the review, 13 exclusively used government dates as a proxy for social distancing behavior, and none accounted for both testing and mobility. Using government stay-at-home dates as a proxy for social distancing (10.2% decrease in the number of daily cases) accounted for only 55% of the true impact of the intervention when compared with estimates using mobility (18.6% reduction). Using 10-fold cross-validation, 23 of 43 sociodemographic variables were significantly and independently predictive of variation in individual social distancing, with delays corresponding to an increase in a county's proportion of people without a high school diploma and proportion of racial and ethnic minorities.ConclusionsThis retrospective analysis of mobility patterns found that social distancing behavior occurred well before the onset of government stay-at-home dates. This asynchrony leads to the underestimation of the impact of social distancing. Sociodemographic characteristics associated with delays in social distancing can help explain the disproportionate case burden and mortality among vulnerable communities.

Dataset Information

Diffusion segregation and the disproportionate incidence of COVID-19 in African American communities.

Publications

Diffusion segregation and the disproportionate incidence of COVID-19 in African American communities.

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