Factors Associated with COVID-Related Mortality: the Case of Texas

Two-part predictive modeling for COVID-19 cases and deaths in the U.S

COVID-19 prediction has been essential in the aid of prevention and control of the disease. The motivation of this case study is to develop predictive models for COVID-19 cases and deaths based on a cross-sectional data set with a total of 28,955 observations and 18 variables, which is compiled from 5 data sources from Kaggle. A two-part modeling framework, in which the first part is a logistic classifier and the second part includes machine learning or statistical smoothing methods, is introduced to model the highly skewed distribution of COVID-19 cases and deaths. We also aim to understand what factors are most relevant to COVID-19's occurrence and fatality. Evaluation criteria such as root mean squared error (RMSE) and mean absolute error (MAE) are used. We find that the two-part XGBoost model perform best with predicting the entire distribution of COVID-19 cases and deaths. The most important factors relevant to either COVID-19 cases or deaths include population and the rate of primary care physicians.

Parental Factors Associated with COVID-19 Vaccine Uptake for Children over 5 Years of Age in Texas

The COVID-19 vaccine is safe and effective for children, yet parental hesitancy towards vaccinating children against the virus persists. We conducted a telephone-administered weighted survey in Texas to examine parents' sociodemographic factors and medical conditions associated with COVID-19 vaccination intention for parents with unvaccinated children ages 5-17 years. We collected responses from 19,502 participants, of which 4879 were parents of children ages 5-17 years. We conducted multiple logistic regression with Lasso-selected variables to identify factors associated with children's vaccination status and parents' intention to vaccinate their children. From the unweighted sample, less than half of the parents (46.8%) had at least one unvaccinated child. These parents were more likely to be White, English-speaking, not concerned about illness, privately insured, and unvaccinated for COVID-19 themselves (p < 0.001). In the adjusted regression model, parents who were unvaccinated (vs. having COVID-19 booster, aOR = 28.6) and financially insecure (aOR = 1.46) had higher odds of having unvaccinated children. Parents who were Asian (aOR = 0.50), Black (aOR = 0.69), Spanish-speaking (aOR = 0.57), concerned about illness (aOR = 0.63), had heart disease (aOR = 0.41), and diabetes (aOR = 0.61) had lower odds of having unvaccinated children. Parents who were Asian, Black, Hispanic, Spanish-speaking, concerned about illness for others, and vaccine-boosted were more likely to have vaccination intention for their children (p < 0.001). Children's vaccination is essential to reduce COVID-19 transmission. It is important to raise awareness about the value of pediatric COVID-19 vaccination while considering parents' sociodemographic and medical circumstances.

Racism, health and pandemic: a narrative review of the relationship between black population and COVID-19 events in 2020

This study aimed to analyze how scientific publications described and interpreted findings about the relationship between the Black population and events linked to COVID-19 in 2020. Narrative review with systematic search, in which a survey was conducted on articles published in 2020 in the Scopus, Medline/PubMed, and Web of Science databases. Initially, 665 articles were found, and after reading and applying the eligible criteria, the final number of 45 articles was reached. Epidemiological, observational studies, secondary data and developed in the United States predominated. Four groupings and respective findings emerged from the synthesis of information extracted: Main events in the Black population - high number of deaths and mortality rate; Direct relationships - poor health, housing, and work conditions; Intermediate relationships - low income and anti-Black prejudice; Comprehensive relationships - structural racism and social determinants of health. The identification of racial health disparities is an important finding about the dynamics of the pandemic among the Black population. However, multicausal explanations were limited. It is necessary to mobilize critical theoretical resources from ethnic and health studies to qualify research in order to support global actions to combat the SARS-CoV-2 epidemic in this group.

COVID-19-related mortality in Texas border counties vs non-border counties

The state of Texas ranked second in total cases of coronavirus disease 2019 (COVID-19) in the United States during the pandemic. Counties near the US-Mexico border were severely impacted by the pandemic. Mortality and long-term consequences from COVID-19 are associated with comorbidities, illness severity, and patient demographics. However, differences in outcomes between border and non-border counties are unknown. In this retrospective observational study, data were obtained for analysis from the Texas hospital inpatient discharge public use data file from 2020 to 2021 for adult patients with COVID-19 based on the associated international classification of disease 10 codes. Patients were categorized into border or non-border counties. The clinical outcomes included mortality, length of stay, mortality risk, illness severity, and intensive care unit (ICU) or critical care unit (CCU) admissions. Cost differences between border and non-border counties were analyzed. Age, gender, race, ethnicity, admission type, location, and year of diagnosis were covariates. A total of 1,745,312 patients were included in this analysis. 25% of COVID-19 patients admitted in Texas were from border counties. Patient mortality was 5.35% in border counties compared to 3.87% in non-border counties (p = 0.003). In border counties, 36.51% and 32.96% of patients required ICU and CCU admissions compared to 32.96% and 10.72%, respectively in non-border counties. Border counties had significantly higher risk of mortality (relative risk (RR) = 1.26; 95% CI: 1.09-1.46, p = 0.002), ICU admission (RR = 1.15; 95% CI: 1.15; 95% CI: 1.01-1.32, p = 0.038), CCU admission (RR = 2.87; 95% CI: 1.93, 4.27, p < 0.001), and ICU/CCU admission (RR = 1.28; 95% CI: 1.10, 1.48, p < 0.001) which reflects health disparities in the management of COVID-19 in border counties of Texas.

Understanding the Experiences of Latinx LGBTQ Texans at the Beginning of the COVID-19 Pandemic

Marginalized communities have been disproportionately affected by COVID-19, including both racial/ethnic minority and sexual minority populations. To date, there has been little research examining the impact of the COVID-19 pandemic at the intersections of marginalized identities. Furthermore, available national data on COVID-19 outcomes may obscure our understanding of region-specific outcomes, particularly in the U.S. South. Using an intersectional approach, we explore differences in worries over COVID-19, preventative behaviors, and COVID-19 outcomes in the early months of the pandemic in a diverse sample of LGBTQ people (N = 1076) living in Texas. Our findings indicated that LGBTQ Latinx people in Texas reported more COVID-19 related worries and adverse outcomes than non-Latinx LGBTQ people. These findings are in line with previous research that found that the increased risk to Latinx and LGBTQ populations in public health crises is often overlooked and can be attributed to many factors such as socioeconomic status, occupational propensity, disparities in physical health, and barriers to healthcare access. Furthermore, our findings suggest the necessity of utilizing an intersectional approach when examining the disproportionate burden marginalized communities face in public health crises.

COVID-19 pandemic and socio-environmental inequality: A narrative review

Background and Aims

The COVID-19 pandemic has provided preliminary evidence of the existence of health, social, and environmental inequalities. This inequality encompasses inadequate access to safe water, clean air, and wastewater management, as well as limited socioeconomic and educational opportunities. These issues have not received sufficient attention during the pandemic. The purpose of this narrative review is to provide a comprehensive summary and analysis of the existing literature on a specific topic, ultimately leading to a conclusion based on the evidence presented.

Methods

The search methodology for this study involved conducting comprehensive searches of scientific databases, including PubMed, ScienceDirect, LILACS, and Google Scholar, from 2019 to 2023. The study focused on a specific theme and its relevant aspects related to global environmental health and society. Keywords such as COVID-19, inequities, and environmental health were used for searching. Additionally, the Boolean operator "AND" was used to combine these descriptors.

Results

Unequal exposure to air pollution has been reported in Africa, as well as in large parts of Asia and Latin America, according to the data that has been obtained. The pandemic has also resulted in a surge in healthcare waste generation, exacerbating the environmental impact of solid waste. Furthermore, there is evidence indicating significant disparities in the severe lack of access to sanitation services between developing nations and low-income regions. The issues related to water availability, accessibility, and quality are subject to debate. It has been reported that SARS-CoV-2 is present not only in untreated/raw water, but also in water bodies that act as reservoirs. Moreover, insufficient education, poverty, and low household income have been identified as the most significant risk factors for COVID-19 infection and mortality.

Conclusion

It is evident that addressing socio-environmental inequality and striving to narrow the gap by prioritizing vulnerable populations are imperative.

Multimorbidity and social determinants of health in the US prior to the COVID-19 pandemic and implications for health outcomes: a cross-sectional analysis based on NHANES 2017-2018

Multimorbidity increases the risk of all-cause mortality, and along with age, is an independent risk factor for severe disease and mortality from COVID-19. Inequities in the social determinants of health contributed to increased mortality from COVID-19 among disadvantaged populations. This study aimed to evaluate the prevalence of multimorbid conditions and associations with the social determinants of health in the US prior to the pandemic.Methods Data from the 2017-18 cycle of NHANES were used to determine the prevalence of 13 chronic conditions, and the prevalence of having 0, 1, or 2 or more of those conditions, among the US adult population aged ≥ 20 years. Multimorbidity was defined as having 2 or more of these conditions. Data were stratified according to demographic, socioeconomic and indicators of health access, and analyses including logistic regression, performed to determine the factors associated with multimorbidity.Results The prevalence of multimorbidity was 58.4% (95% CI 55.2 to 61.7). Multimorbidity was strongly associated with age and was highly prevalent among those aged 20-29 years at 22.2% (95% CI 16.9 to 27.6) and continued to increase with older age. The prevalence of multimorbidity was highest in those defined as Other or multiple races (66.9%), followed in decreasing frequency by rates among non-Hispanic Whites (61.2%), non-Hispanic Blacks (57.4%), Hispanic (52.0%) and Asian (41.3%) groups.Logistic regression showed a statistically significant relationship between multimorbidity and age, as expected. Asian race was associated with a reduced likelihood of 2 or more chronic conditions (OR 0.4; 95% CI 0.35 to 0.57; P < 0.0001). Socioeconomic factors were related to multimorbidity. Being above the poverty level (OR 0.64; 95% CI 0.46 to 0.91, p = 0.013); and a lack of regular access to health care (OR 0.61 (95% CI 0.42 to 0.88, p = 0.008) were both associated with a reduced likelihood of multimorbidity. Furthermore, there was a borderline association between not having health insurance and reduced likelihood of multimorbidity (OR 0.63; 95% CI 0.40 to 1.0; p = 0.053).Conclusions There are high levels of multimorbidity in the US adult population, evident from young adulthood and increasing with age. Cardiometabolic causes of multimorbidity were highly prevalent, especially obesity, hyperlipidemia, hypertension, and diabetes; conditions subsequently found to be associated with severe disease and death from COVID-19. A lack of access to care was paradoxically associated with reduced likelihood of comorbidity, likely linked to underdiagnosis of chronic conditions. Obesity, poverty, and lack of access to healthcare are factors related to multimorbidity and were also relevant to the health impact of the COVID-19 pandemic, that must be addressed through comprehensive social and public policy measures. More research is needed on the etiology and determinants of multimorbidity, on those affected, patterns of co-morbidity, and implications for individual health and impact on health systems and society to promote optimal outcomes. Comprehensive public health policies are needed to tackle multimorbidity and reduce disparities in the social determinants of health, as well as to provide universal access to healthcare.

Demographic and Psychosocial Correlates of COVID-19 Vaccination Status among a Statewide Sample in Texas

The COVID-19 pandemic has been a global public health concern since early 2020 and has required local and state-level responses in the United States. There were several Food and Drug Administration (FDA) approved vaccines available for the prevention of COVID-19 as of August 2022, yet not all states have achieved high vaccination coverage. Texas is a particularly unique state with a history of opposing vaccination mandates, as well as a large and ethnically/racially diverse population. This study explored the demographic and psychosocial correlates of COVID-19 vaccinations among a statewide sample in Texas. A quota sample of 1089 individuals was surveyed online from June-July 2022. The primary outcome in this study was COVID-19 vaccination status (fully vaccinated, partially vaccinated, or unvaccinated) and included independent variables related to demographics, COVID-19 infection/vaccine attitudes and beliefs, and challenges related to the COVID-19 pandemic. Hispanic/Latinx individuals were more likely than non-Hispanic White individuals to be partially vaccinated as opposed to unvaccinated. Higher education levels and confidence that the FDA would ensure a safe COVID-19 vaccine were strongly associated with a higher likelihood of being fully vaccinated. In addition, some challenges brought on by the pandemic and concerns about becoming infected or infecting others were associated with a higher likelihood of being partially or fully vaccinated. These findings emphasize the need to further investigate the interaction between individual and contextual factors in improving COVID-19 vaccination rates, especially among vulnerable and disadvantaged populations.

Racial Disparities in Breast Cancer Presentation and Diagnosis in COVID-Era Central Texas

INTRODUCTION

The COVID-19 pandemic has significantly impacted the diagnosis of breast cancer (BC). With a large Hispanic/Latinx population, early revocation of mask mandates, and lower vaccination rate than many other states, this study explores the relationship between COVID-19 and the presentation and diagnosis of BC patients in the unique socio-politico-economic context of Central Texas.

METHODS

This study is a retrospective review of the Seton Medical Center Austin tumor registry for BC patients from March 1, 2019 to March 2, 2021. We compared demographics, insurance status, clinical and pathologic stage, and time from diagnosis to intervention between "pre-COVID" (March 1, 2019- March 1, 2020) and "post-COVID" (March 2, 2020-March 2, 2021). We utilized descriptive, univariate, and multivariable logistic regression statistics.

RESULTS

There were 781 patients diagnosed with BC, with 113 fewer post-COVID compared to pre-COVID. The proportion of Black patients diagnosed with BC decreased post-COVID compared with pre-COVID (10.1%-4.5%, P = 0.002). When adjusting for other factors, uninsured and underinsured patients had increased odds of presenting with late-stage BC (odds ratio:5.40, P < 0.001). There was also an association between presenting with stage 2 or greater BC and delayed time-to-intervention.

CONCLUSIONS

Although fewer women overall were diagnosed with BC post-COVID, the return to baseline diagnoses has yet to be seen. We identified a pandemic-related decrease in BC diagnoses in Black women and increased odds of late-stage cancer among uninsured patients, suggesting a disparate relationship between COVID-19 and health care access and affordability. Outreach and screening efforts should address strategies to engage Black and uninsured patients.

The COVID-19 pandemic: asthma control, tobacco use, and mental health among African American and Latinx college students

OBJECTIVE

This study investigated the impact of COVID-19 on tobacco use and mental health in US African American and Latinx college students with asthma. Associations among asthma control, tobacco use, and mental health were also examined.

METHODS

105 African American and Latinx college students with asthma (18-23 years) completed two online questionnaires (June 2019-March 2020 for Time 1; August 2020-October 2020 for Time 2). Participants completed the Epidemic-Pandemic Impacts Inventory (measure of COVID-19 impact), Asthma Control Test, Generalized Anxiety Disorder scale, Patient Health Questionnaire (measure of depression), Perceived Stress Scale, and items related to tobacco use.

RESULTS

Asthma control improved (t = -3.326, p = 0.001) from Time 1 to 2, and e-vapor product use decreased (χ²₁₀₄ = 6.572, p = 0.010). COVID-19 impact was positively associated with students' symptoms of anxiety, depression, and perceived stress (B = 0.201, p < 0.001; B = 0.179, p < 0.001; and B = 0.199, p = 0.001, respectively) at Time 2. These results remained significant with the Benjamini-Hochberg correction. Asthma control at Time 1 was negatively associated with anxiety symptoms at Time 2 (B = -0.418, p = 0.023); however, associations with perceived stress (B = -0.514, p = 0.019) and all other tobacco product use (B = -0.233, p = 0.030) did not remain significant with the Benjamini-Hochberg correction.

CONCLUSIONS

As hypothesized, a higher COVID-19 impact score was associated with students endorsing more mental health symptoms. Better control of asthma symptoms before the pandemic predicted fewer anxiety symptoms during the pandemic.

An Analysis of COVID-19 Mortality During the Dominancy of Alpha, Delta, and Omicron in the USA

BACKGROUND

The objective of the study was to measure the risk of death due to COVID-19 in relation to individuals' characteristics, and severity of their disease during the dominant periods of Alpha, Delta, and Omicron variants have influenced mortality rates.

METHODS

This study was conducted using COVID-19 Centers for Disease Control and Prevention (CDC) Case Surveillance Public Data Taskforce for 57 states, and United States territories between January 1, 2020 and March 20, 2022. Multivariable binary Hyperbolastic regression of type I was used to analyzes the data.

RESULTS

Seniors and ICU-admitted patients had the highest risk of death. For each additional percent increase in fully vaccinated individuals, the odds of death deceased by 1%. The odds of death prior to vaccine availability, compared to post vaccine availability, was 1.27. When comparing the time periods each variant was dominant, the odds of death was 3.45-fold higher during Delta compared to Alpha. All predictor variables had P-values ≤.001.

CONCLUSION

There was a noticeable difference in the odds of death among subcategories of age, race/ethnicity, sex, PMCs, hospitalization, ICU, vaccine availability, variant, and percent of fully vaccinated individuals.

What have we learned about socioeconomic inequalities in the spread of COVID-19? A systematic review

This article aims to provide a better understanding of the associations between groups of socioeconomic variables and confirmed cases of COVID-19. The focus is on cross-continental differences of reported positive, negative, unclear, or no associations. A systematic review of the literature is conducted on the Web of Science and SCOPUS databases. Our search identifies 314 eligible studies published on or before 31 December 2021. We detect nine groups of frequently used socioeconomic variables and results are presented by region of the world (Africa, Asia, Europe, Middle East, North American and South America). The review expands to describe the most used statistical and modelling techniques as well as inclusion of additional dimensions such as demographic, healthcare weather and mobility. Meanwhile findings agree on the generalized positive impact of population density, per capita GDP and urban areas on transmission of infections, contradictory results have been found concerning to educational level and income.

Characterization of persons with reported SARS-CoV-2 infection in the Oklahoma City tri-county area: Evidence from the first 12 months of transmission

Background

To describe characteristics, hospitalization, and death for reported cases of SARS-CoV-2 infection in the Oklahoma City tri-county area.

Methods

We extracted notified cases of SARS-CoV-2 infection for our study area and used descriptive statistics and modeling to examine case characteristics and calculate the odds of hospitalization and death in relation to a range of explanatory variables.

Results

Between March 12th, 2020 and February 28th, 2021, 124,925 cases of SARS-CoV-2 infection were reported from the study region. Being male, White or Black/African American, aged 50 years or older, presenting with apnea, cough, and shortness of breath, and having diabetes was associated with increased odds of hospitalization. The odds of dying were significantly associated with being Black/African American, presenting with cough and fever, having kidney disease and diabetes and being aged 70 years or older.

Conclusions

The first cohort analysis of SARS-CoV-2 positive individuals in the Oklahoma City tri-county area confirms comorbidities and age as important predictors of COVID-19 hospitalization or death. As a novel aspect, we show that early symptoms of breathing difficulties in particular are associated with hospitalization and death. Initial case assessment and SARS-CoV-2 guidelines should continue to focus on age, comorbidities, and early symptoms.

A systematic review of racial/ethnic and socioeconomic disparities in COVID-19

BACKGROUND

Preliminary evidence from the COVID-19 pandemic shows the presence of health disparities, especially in terms of morbidity and mortality. This study aimed to systematically review the evidence on the association of racial/ethnic and socioeconomic status (SES) with health outcomes and access to healthcare services during the COVID-19 pandemic.

METHODS

We retrieved published evidence from late December 2019 through March 1, 2021. The target population was the population of the countries during the COVID-19 pandemic. The exposures were defined as belonging to racial/ethnic minority groups and/or low SES. The primary outcomes of interest include (1) death from COVID-19, (2) COVID-19 incidence/infection, (3) COVID-19 hospitalization, (4) ICU admission, (5) need for mechanical ventilation, (6) confirmed diagnosis, and (7) access to testing. We systematically synthesized the findings from different studies and provided a narrative explanation of the results.

RESULTS

After removing the duplicate results and screening for relevant titles and abstracts, 77 studies were selected for full-text review. Finally, 52 studies were included in the review. The majority of the studies were from the United States (37 studies). Despite the significant incongruity among the studies, most of them showed that racial/ethnic minority groups had higher risks of COVID-19 infection and hospitalization, confirmed diagnosis, and death. Additionally, most of the studies cited factors such as low level of education, poverty, poor housing conditions, low household income, speaking in a language other than the national language in a country, and living in overcrowded households as risk factors of COVID-19 incidence/infection, death, and confirmed diagnosis. However, findings in terms of the association of lack of health insurance coverage and unemployment with the outcome measures as well as the association of requiring mechanical ventilation, ICU admission, and access to testing for COVID-19 with race/ethnicity were limited and inconsistent.

CONCLUSION

It is evident that racial/ethnic minority groups and those from low SES are more vulnerable to COVID-19; therefore, public health policymakers, practitioners, and clinicians should be aware of these inequalities and strive to narrow the gap by focusing on vulnerable populations. This systematic review also revealed a major incongruity in the definition of the racial/ethnic minority groups and SES among the studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020190105.

COVID-19, Race/Ethnicity, and Age: the Role of Telemedicine to Close the Gaps on Health Disparities

The novel COVID-19 outbreak is a major public health challenge that quickly turned into an economic recession of great proportions. This pandemic poses a trade-off between health and the economy where social distancing, quarantines, and isolation shut down demand and supply chains across the USA. This paper analyzes the impact of COVID-19 on illness and death among older adults and communities of color with low socioeconomic status in New York City. To achieve this goal, fractional logit models are used to capture changes in the novel virus’ morbidity and mortality rates at the neighborhood level. Median income, race/ethnicity, age, household crowding, and socially interactive employment explained the disproportionate exposure and fatalities across the city. We also employ a variable related to telehealth/telemedicine to sustain that technology goods along with government intervention as a provider of social goods can ameliorate existing health disparities. There is a need for evidence-based data on the economic costs and social benefits of COVID-19 relief programs.

Association of Race and Ethnicity with COVID-19 Test Positivity and Hospitalization Is Mediated by Socioeconomic Factors

Rationale: Black race and Hispanic ethnicity are associated with increased risks for coronavirus disease (COVID-19) infection and severity. It is purported that socioeconomic factors may drive this association, but data supporting this assertion are sparse. Objectives: To evaluate whether socioeconomic factors mediate the association of race/ethnicity with COVID-19 incidence and outcomes. Methods: We conducted a retrospective cohort study of adults tested for (cohort 1) or hospitalized with (cohort 2) COVID-19 between March 1, 2020, and July 23, 2020, at the University of Miami Hospital and Clinics. Our primary exposure was race/ethnicity. We considered socioeconomic factors as potential mediators of our exposure's association with outcomes. We used standard statistics to describe our cohorts and multivariable regression modeling to identify associations of race/ethnicity with our primary outcomes, one for each cohort, of test positivity (cohort 1) and hospital mortality (cohort 2). We performed a mediation analysis to see whether household income, population density, and household size mediated the association of race/ethnicity with outcomes. Results: Our cohorts included 15,473 patients tested (29.0% non-Hispanic White, 48.1% Hispanic White, 15.0% non-Hispanic Black, 1.7% Hispanic Black, and 1.6% other) and 295 patients hospitalized (9.2% non-Hispanic White, 56.9% Hispanic White, 21.4% non-Hispanic Black, 2.4% Hispanic Black, and 10.2% other). Among those tested, 1,256 patients (8.1%) tested positive, and, of the hospitalized patients, 47 (15.9%) died. After adjustment for demographics, race/ethnicity was associated with test positivity-odds-ratio (95% confidence interval [CI]) versus non-Hispanic White for Non-Hispanic Black: 3.21 (2.60-3.96), Hispanic White: 2.72 (2.28-3.26), and Hispanic Black: 3.55 (2.33-5.28). Population density mediated this association (percentage mediated, 17%; 95% CI, 11-31%), as did median income (27%; 95% CI, 18-52%) and household size (20%; 95% CI, 12-45%). There was no association between race/ethnicity and mortality, although this analysis was underpowered. Conclusions: Black race and Hispanic ethnicity are associated with an increased odds of COVID-19 positivity. This association is substantially mediated by socioeconomic factors.

Demographics, politics, and health factors predict mask wearing during the COVID-19 pandemic: a cross-sectional study

BACKGROUND

Wearing a protective face covering can reduce the spread of COVID-19, but Americans' compliance with wearing a mask is uneven. The purpose of this study is to examine the association between health determinants (Health Behaviors, Clinical Care, Social and Economic Conditions, and the Physical Environment) and mask wearing at the county level.

METHODS

Data were collected from publicly available sources, including the County Health Rankings and the New York Times. The dependent variable was the percent of county residents who reported frequently or always wearing a mask when in public. County demographics and voting patterns served as controls. Two-levels random effects regression models were used to examine the study hypotheses.

RESULTS

Results indicate that, after considering the effects of the controls, Health Behaviors were positively associated with mask wearing, the Physical Environment held a negative association, and Clinical Care and Social and Behavioral Factors were unrelated.

CONCLUSIONS

Results indicate that patterns of healthy behaviors can help predict compliance with public health mandates that can help reduce the spread of COVID-19. From an instutitional theory perspective, the data suggest counties develop collective values and norms around health. Thus, public health officials can seek to alter governance structures and normative behaviors to improve healthy behaviors.

COVID-19 fatalities by zip codes and socioeconomic indicators across various U.S. regions

Background

There is a paucity of literature addressing COVID-19 case-fatality ratios (CFR) by zip code (ZC). We aim to analyze trends in COVID-19 CFR, population density, and socioeconomic status (SES) indicators (unemployment, median household income) to identify ZCs heavily burdened by COVID-19.

Methods

Cross-sectional study to investigate the US prevalence of COVD-19 fatalities by ZC and SES. CFRs were calculated from state/county Departments of Health. Inclusion criteria were counties that reported cases/deaths by ZC and a CFR≥2%. This study was reported in line with the STROCSS criteria.

Results

609/1,853 ZCs, spanning 327 counties in 7 states had CFRs ≥2%. A significant positive correlation was found between the CFR and median household income (Pearson correlation:0.107; 95% CI [289.1,1937.9]; p < 0.001). No significant correlations exist between the CFR, and population/mi (Sen-Crowe et al., 2020) [2] or unemployment rate. Significant associations exist between the CFR and young males and elderly females without public insurance. CFR was inversely associated with persons aged <44 and individuals aged ≥65. The percentage of nursing homes (NHs) within cities residing within high CFR ZCs range from 8.7% to 67.6%.

Conclusion

Significant positive association was found between the CFR and median household income. Population/mi (Sen-Crowe et al., 2020) [2] and unemployment rates, did not correlate to CFR. NHs were heavily distributed in high CFR zip codes. We recommend the targeted vaccination of zip codes with a large proportion of long-term care facilities. Finally, we recommend for improved screening and safety guidelines for vulnerable populations (e.g nursing home residents) and established protocols for when there is evidence of substantial infectious spread.

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First national sampling of COVID-19 Case Fatality Ratio (CFR) at the zip code level.

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Population density and unemployment rate did not correlate to COVID-19 CFR.

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Significant positive correlation was found between CFR and median household income.

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Nursing homes were concentrated in zip codes with high COVID-19 CFR.

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States should make COVID-19 data available at the zip code level.

Elevated COVID19 mortality risk in detroit area hospitals among patients from census tracts with extreme socioeconomic vulnerability

BACKGROUND

the incidence of novel coronavirus disease (COVID19) is elevated in areas with heightened socioeconomic vulnerability. Early reports from US hospitals also implicated social disadvantage and chronic disease history as COVID19 mortality risk factors. However, the relationship between race and COVID19 mortality remains unclear.

METHODS

we examined in-hospital COVID19 mortality risk factors in a multi-hospital tertiary health care system that serves greater Detroit, Michigan, a predominantly African American city with high rates of poverty and chronic disease. Consecutive adult patients who presented to emergency departments and tested positive for COVID19 from 3/11/2020 through 4/18/2020 were included. Using log-binomial regression, we assessed the relationship between in-hospital mortality and residence in census tracts that were flagged for extreme socioeconomic vulnerability, patient-level demographics, and clinical comorbidities.

FINDINGS

a total of 1,015 adults tested positive for COVID19 during the study period; 80% identified as Black people, 52% were male and 53% were ≥ 65 years of age. The median body mass index was 30•4 and the median Charlson Comorbidity Index score was 4. Patients from census tracts that were flagged for vulnerability related to socioeconomic status had a higher mortality rate than their peers who resided in less vulnerable census tracts (β 0.26, standard error (SE) 0.11, degrees of freedom (df) 378, t-value (t) 2.27, exp(β) 1.29, p-value 0.02). Adjustment for age category, Black race, sex and/or the Charlson Comorbidity Index score category reduced the magnitude of association by less than 10% [exp(β) 1.29 vs. 1.21]. Black race [p = 0.38] and sex [p = 0.62] were not associated with mortality in this sample.

INTERPRETATION

people who lived in areas flagged for extreme socioeconomic vulnerability had elevated mortality risk in our predominantly African-American cohort of COVID19 patients who were able to seek hospital care during the so-called 'first wave' of the pandemic. By contrast, Black race was not associated with mortality in our sample.