Visualizing COVID-19 Mortality Rates and African-American Populations in the USA and Pennsylvania

Integrating youth participatory action research and health communication to inform youth and young adult covid-19 vaccine communication research

COVID-19 vaccination rates remain lower among adolescents compared with adults. Youth participatory action research (YPAR) offers opportunities to inform youth vaccine communication at the local and population level. However, few studies have integrated systematic health communication research with YPAR. In the current study, a diverse team of paid high school interns, undergraduate student mentors and communication researchers in West Philadelphia YPAR programs developed a theory-informed communication survey to measure teen COVID-19 vaccine beliefs, information sources and behavior. The survey was distributed locally and informed youth-created vaccine campaign messages. In addition, YPAR-derived survey measures complimented a qualitative online elicitation survey with US young adults. Responses were coded using inductive content analysis, informing measures for a subsequent population-level study of young adults. This research followed protocols approved by an Institutional Review Board. Applying a YPAR framework elevated youth voices in the study development process. Communication theory and methods aided the development of survey studies to advance both local YPAR program objectives and population-level research. Future implications are discussed.

African Americans Possessed High Prevalence of Comorbidities and Frequent Abdominal Symptoms, and Comprised A Disproportionate Share of Covid-19 Mortality among 9,873 Us- Hospitalized Patients Early in the Pandemic

Background and aim

Identifying clinical characteristics and outcomes of different ethnicities in the US may inform treatment for hospitalized COVID-19 patients. Aim of this study is to identify predictors of mortality among US races/ethnicities.

Design Setting and participants

We retrospectively analyzed de-identified data from 9,873 COVID-19 patients who were hospitalized at 15 US hospital centers in 11 states (March 2020-November 2020). Main Outcomes and Measures: The primary outcome was to identify predictors of mortality in hospitalized COVID-19 patients.

Results

Among the 9,873 patients, there were 64.1% African Americans (AA), 19.8% Caucasians, 10.4% Hispanics, and 5.7% Asians, with 50.7% female. Males showed higher in-hospital mortality (20.9% vs. 15.3%, p=0.001). Non- survivors were significantly older (67 vs. 61 years) than survivors. Patients in New York had the highest in-hospital mortality (OR=3.54 (3.03 - 4.14)). AA patients possessed higher prevalence of comorbidities, had longer hospital stay, higher ICU admission rates, increased requirement for mechanical ventilation and higher in-hospital mortality compared to other races/ethnicities. Gastrointestinal symptoms (GI), particularly diarrhea, were more common among minority patients. Among GI symptoms and laboratory findings, abdominal pain (5.3%, p=0.03), elevated AST (n=2653, 50.2%, p=<0.001, OR=2.18), bilirubin (n=577, 12.9%, p=0.01) and low albumin levels (n=361, 19.1%, p=0.03) were associated with mortality. Multivariate analysis (adjusted for age, sex, race, geographic location) indicates that patients with asthma, COPD, cardiac disease, hypertension, diabetes mellitus, immunocompromised status, shortness of breath and cough possess higher odds of in-hospital mortality. Among laboratory parameters, patients with lymphocytopenia (OR2=2.50), lymphocytosis (OR2=1.41), and elevations of serum CRP (OR2=4.19), CPK (OR2=1.43), LDH (OR2=2.10), troponin (OR2=2.91), ferritin (OR2=1.88), AST (OR2=2.18), D-dimer (OR2=2.75) are more prone to death. Patients on glucocorticoids (OR2=1.49) and mechanical ventilation (OR2=9.78) have higher in-hospital mortality.

Conclusion

These findings suggest that older age, male sex, AA race, and hospitalization in New York were associated with higher in-hospital mortality rates from COVID-19 in early pandemic stages. Other predictors of mortality included the presence of comorbidities, shortness of breath, cough elevated serum inflammatory markers, altered lymphocyte count, elevated AST, and low serum albumin. AA patients comprised a disproportionate share of COVID-19 death in the US during 2020 relative to other races/ethnicities.

Predictors of mortality in hospitalised patients with COVID-19: a 1-year case-control study

BACKGROUND

A paucity of predictive models assessing risk factors for COVID-19 mortality that extend beyond age and gender in Latino population is evident in the current academic literature.

OBJECTIVES

To determine the associated factors with mortality, in addition to age and sex during the first year of the pandemic.

DESIGN

A case-control study with retrospective revision of clinical and paraclinical variables by systematic revision of clinical records was conducted. Multiple imputations by chained equation were implemented to account for missing variables. Classification and regression trees (CART) were estimated to evaluate the interaction of associated factors on admission and their role in predicting mortality during hospitalisation. No intervention was performed.

SETTING

High-complexity centre above 2640 m above sea level (masl) in Colombia.

PARTICIPANTS

A population sample of 564 patients admitted to the hospital with confirmed COVID-19 by PCR. Deceased patients (n=282) and a control group (n=282), matched by age, sex and month of admission, were included.

MAIN OUTCOME MEASURE

Mortality during hospitalisation.

MAIN RESULTS

After the imputation of datasets, CART analysis estimated 11 clinical profiles based on respiratory distress, haemoglobin, lactate dehydrogenase, partial pressure of oxygen to inspired partial pressure of oxygen ratio, chronic kidney disease, ferritin, creatinine and leucocytes on admission. The accuracy model for prediction was 80.4% (95% CI 71.8% to 87.3%), with an area under the curve of 78.8% (95% CI 69.63% to 87.93%).

CONCLUSIONS

This study discloses new interactions between clinical and paraclinical features beyond age and sex influencing mortality in COVID-19 patients. Furthermore, the predictive model could offer new clues for the personalised management of this condition in clinical settings.

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rates compared to other demographic groups. These disparities highlight the urgent need to examine the experiences, behaviors, and opinions of the African American population in relation to the COVID-19 pandemic. By understanding their unique challenges in navigating matters of health and well-being, we can work towards promoting health equity, eliminating disparities, and addressing persistent barriers to care. Since Twitter data has shown significant promise as a representation of human behavior and for opinion mining, this study leverages Twitter data published in 2020 to characterize the pandemic-related experiences of the United States' African American population using aspect-based sentiment analysis. Sentiment analysis is a common task in natural language processing that identifies the emotional tone (i.e., positive, negative, or neutral) of a text sample. Aspect-based sentiment analysis increases the granularity of sentiment analysis by also extracting the aspect for which sentiment is expressed. We developed a machine learning pipeline consisting of image and language-based classification models to filter out tweets not related to COVID-19 and those unlikely published by African American Twitter subscribers, leading to an analysis of nearly 4 million tweets. Overall, our results show that the majority of tweets had a negative tone, and that the days with larger numbers of published tweets often coincided with major U.S. events related to the pandemic as suggested by major news headlines (e.g., vaccine rollout). We also show how word usage evolved throughout the year (e.g., outbreak to pandemic and coronavirus to covid). This work also points to important issues like food insecurity and vaccine hesitation, along with exposing semantic relationships between words, such as covid and exhausted. As such, this work furthers understanding of how the nationwide progression of the pandemic may have impacted the narratives of African American Twitter users.

Associations of Combustible Cigarette, Electronic Cigarette, and Dual Use With COVID Infection and Severity in the U.S.: A Cross-sectional Analysis of the 2021 National Health Information Survey

Given the potential respiratory health risks, the association of COVID infection and the use of combustible cigarettes, electronic nicotine delivery systems (ENDS), and concurrent dual use is a priority for public health. Many published reports have not accounted for known covarying factors. This study sought to calculate adjusted odds ratios for self-reported COVID infection and disease severity as a function of smoking and ENDS use, while accounting for factors known to influence COVID infection and disease severity (i.e., age, sex, race and ethnicity, socioeconomic status and educational attainment, rural or urban environment, self-reported diabetes, COPD, coronary heart disease, and obesity status). Data from the 2021 U.S. National Health Interview Survey, a cross-sectional questionnaire design, were used to calculate both unadjusted and adjusted odds ratios for self-reported COVID infection and severity of symptoms. Results indicate that combustible cigarette use is associated with a lower likelihood of self-reported COVID infection relative to non-use of tobacco products (AOR = .64; 95% CI [.55, .74]), whereas ENDS use is associated with a higher likelihood of self-reported COVID infection (AOR = 1.30; 95% CI [1.04, 1.63]). There was no significant difference in COVID infection among dual users (ENDS and combustible use) when compared with non-users. Adjusting for covarying factors did not substantially change the results. There were no significant differences in COVID disease severity between those of varying smoking status. Future research should examine the relationship between smoking status and COVID infection and disease severity utilizing longitudinal study designs and non-self-report measures of smoking status (e.g., the biomarker cotinine), COVID infection (e.g., positive tests), and disease severity (e.g., hospitalizations, ventilator assistance, mortality, and ongoing symptoms of long COVID).

Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis

Background

Why is COVID-19 mortality higher in counties with a disproportionately large (>13.4%) share of Black residents (hereafter "Black counties") relative to others ("non-Black counties")? Existing literature points to six categories of determinants: (1) social distancing, (2) COVID-19 testing, (3) socioeconomic characteristics, (4) environmental characteristics, (5) prevalence of (pre-existing) chronic health conditions, and (6) demographic characteristics. The relative importance of these determinants has not yet been thoroughly examined.

Methods

We built a dataset consisting of 21 sub-indicators across the six categories of determinants for 3108 US counties and their COVID-19 mortality over the period of January 22, 2020-December 31, 2020. Applying the Gelbach's decomposition, we quantified which determinants were most (or least) associated with the COVID-19 mortality disparity between Black and non-Black counties.

Results

We find that COVID-19 death rates were 26 percent higher in Black counties compared to non-Black counties. This disparity was almost completely explained by the six categories of determinants included in our model. Decomposition analyses indicate that county-level demographic and population health characteristics explained most of this disparity. Among all sub-indicators considered, the greater proportion of females and smaller proportion of rural residents in Black counties were the two largest contributors to the COVID-19 mortality gap between Black and non-Black counties. Proportions of diabetic residents, uninsured residents, and the degree of income inequality also significantly contributed to the gap in COVID-19 mortality.

Conclusion

The COVID-19 mortality gap between Black and non-Black counties was largely explained by pre-pandemic differences in demographic and population health characteristics. Policies aiming to reduce the prevalence of chronic conditions and uninsured residents in Black counties would have helped narrow the COVID-19 mortality gap between Black and non-Black counties in 2020.

Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States

This article examines three spatiotemporal methods used for analyzing of infectious diseases, with a focus on COVID-19 in the United States. The methods considered include inverse distance weighting (IDW) interpolation, retrospective spatiotemporal scan statistics and Bayesian spatiotemporal models. The study covers a 12-month period from May 2020 to April 2021, including monthly data from 49 states or regions in the United States. The results show that the spread of COVID-19 pandemic increased rapidly to a high value in winter of 2020, followed by a brief decline that later reverted into another increase. Spatially, the COVID-19 epidemic in the United States exhibited a multi-centre, rapid spread character, with clustering areas represented by states such as New York, North Dakota, Texas and California. By demonstrating the applicability and limitations of different analytical tools in investigating the spatiotemporal dynamics of disease outbreaks, this study contributes to the broader field of epidemiology and helps improve strategies for responding to future major public health events.

Ethical Approaches to Vaccine Allocation and Administration in Carceral Settings, With a Focus on Youth

COVID-19 has disproportionately impacted Americans in carceral settings and secure facilities. A disproportionate number of persons who are confined to carceral settings and secure facilities are members of racial, ethnic, and socioeconomic groups who experience a significant burden of COVID-19 morbidity and mortality. The pandemic-related disparities experienced by minoritized and detained adult populations have received national attention, but the burden of COVID-19 risk among justice-involved youth has been largely absent from these national conversations. With more than 40,000 youth in carceral settings, their COVID-19 risks and prevention needs warrant specific consideration, especially as vaccine distribution programs expand. Youth have been assigned a lower priority status in most state vaccine allocation plans, but youth in carceral settings are at increased risk compared with their peers, raising important questions about how to ethically allocate and administer vaccines to them. In this article we examine ethical issues that arise in the health care of minors in carceral settings and identify an ethical model that could be used to reconsider the allocation of COVID-19 vaccines.

Symptomatic, clinical and biomarker associations for mortality in hospitalized COVID-19 patients enriched for African Americans

BACKGROUND AND AIMS

Initial reports on US COVID-19 showed different outcomes in different races. In this study we use a diverse large cohort of hospitalized COVID-19 patients to determine predictors of mortality.

METHODS

We analyzed data from hospitalized COVID-19 patients (n = 5852) between March 2020- August 2020 from 8 hospitals across the US. Demographics, comorbidities, symptoms and laboratory data were collected.

RESULTS

The cohort contained 3,662 (61.7%) African Americans (AA), 286 (5%) American Latinx (LAT), 1,407 (23.9%), European Americans (EA), and 93 (1.5%) American Asians (AS). Survivors and non-survivors mean ages in years were 58 and 68 for AA, 58 and 77 for EA, 44 and 61 for LAT, and 51 and 63 for AS. Mortality rates for AA, LAT, EA and AS were 14.8, 7.3, 16.3 and 2.2%. Mortality increased among patients with the following characteristics: age, male gender, New York region, cardiac disease, COPD, diabetes mellitus, hypertension, history of cancer, immunosuppression, elevated lymphocytes, CRP, ferritin, D-Dimer, creatinine, troponin, and procalcitonin. Use of mechanical ventilation (p = 0.001), shortness of breath (SOB) (p < 0.01), fatigue (p = 0.04), diarrhea (p = 0.02), and increased AST (p < 0.01), significantly correlated with death in multivariate analysis. Male sex and EA and AA race/ethnicity had higher frequency of death. Diarrhea was among the most common GI symptom amongst AAs (6.8%). When adjusting for comorbidities, significant variables among the demographics of study population were age (over 45 years old), male sex, EA, and patients hospitalized in New York. When adjusting for disease severity, significant variables were age over 65 years old, male sex, EA as well as having SOB, elevated CRP and D-dimer. Glucocorticoid usage was associated with an increased risk of COVID-19 death in our cohort.

CONCLUSION

Among this large cohort of hospitalized COVID-19 patients enriched for African Americans, our study findings may reflect the extent of systemic organ involvement by SARS-CoV-2 and subsequent progression to multi-system organ failure. High mortality in AA in comparison with LAT is likely related to high frequency of comorbidities and older age among AA. Glucocorticoids should be used carefully considering the poor outcomes associated with it. Special focus in treating patients with elevated liver enzymes and other inflammatory biomarkers such as CRP, troponin, ferritin, procalcitonin, and D-dimer are required to prevent poor outcomes.

Black-White Risk Differentials in Pediatric COVID-19 Hospitalization and Intensive Care Unit Admissions in the USA

Purpose

The COVID-19 morbidity with SARS-CoV-2 as a causative pathogenic microbe remains a pandemic with children experiencing less mortality but with severe manifestations. The current study aimed to assess SARS-CoV-2 cumulative incidence, COVID-19 hospitalization, and ICU admission with respect to racial differentials.

Materials and Methods

A cross-sectional nonexperimental epidemiologic design was used to examine pediatric COVID-19 data from CDC during 2020. The variables assessed were ICU admissions, hospitalization, sex, race, and region. The Chi-Square (X²) statistic was used to examine the independence of the variables by race, while the binomial regression model was used to predict racial risk differentials in hospitalization and ICU admissions.

Results

The pediatric COVID-19 data observed the cumulative incidence of hospitalization to be 96,376, while ICU admission was 12,448. Racial differences were observed in hospitalization, ICU admissions, sex, and region. With respect to COVID-19 hospitalization, Black/African American (AA) children were two times as likely to be hospitalized compared to their White counterparts, prevalence risk ratio (pRR) = 2.20, 99% confidence interval (CI = 2.12–2.28). Similarly, Asians were 45% more likely to be hospitalized relative to their White counterparts, pRR = 1.45, 99% CI = 1.32–1.60. Regarding ICU admission, there was a disproportionate racial burden, implying excess ICU admission among Black/AA children relative to their White counterparts, pRR = 5.18, 99% CI = 4.44–6.04. Likewise, Asian children were 3 times as likely to be admitted to the ICU compared to their White counterparts, pRR = 3.36, 99% CI = 2.37–4.77. Additionally, American Indians/Alaska Natives were 2 times as likely to be admitted to ICU, pRR = 2.54, 99% CI = 0.82–7.85.

Conclusion

Racial disparities were observed in COVID-19 hospitalization and ICU admission among the US children, with Black/AA children being disproportionately affected, implying health equity transformation.

COVID-19 Disparities and Vaccine Hesitancy in Black Americans: What Ethical Lessons Can Be Learned?

OBJECTIVE

This state of the art review focuses on bioethical questions and considerations from research findings and methodological issues, including design and recruitment of participants, in studies related to COVID-19 vaccine hesitation in Black individuals. Ethical concerns identified were applied to otolaryngology with recommendations for improving health inequities within subspecialties.

DATA SOURCES

An internet search through PubMed, CINAHL, and socINDEX was conducted to identify articles on COVID-19 vaccine hesitation among the Black population between 2020 and 2021.

REVIEW METHODS

A systematic review approach was taken to search and analyze the research on this topic, which was coupled with expert analysis in identifying and classifying vital ethical considerations.

CONCLUSIONS

The most common COVID-19 vaccine hesitation factors were related to the development of the vaccine, mistrust toward government agencies, and misconceptions about safety and side effects. These findings raised bioethical concerns around mistrust of information, low health literacy, insufficient numbers of Black participants in medical research, and the unique positions of health professionals as trusted sources. These bioethical considerations can be applied in otolaryngology and other health-related areas to aid the public in making informed medical decisions regarding treatments, which may reduce health inequalities among Black Americans and other racial and ethnic minority groups.

IMPLICATIONS FOR PRACTICE

Addressing ethical questions by decreasing mistrust, tailoring information for specific populations, increasing minority representation in research, and using health professionals as primary sources for communicating health information and recommendations may improve relationships with Black communities and increase acceptance of new knowledge and therapies such as COVID-19 vaccination.

COVID-19 Modulates Inflammatory and Renal Markers That May Predict Hospital Outcomes among African American Males

Background and Objectives: African Americans and males have elevated risks of infection, hospitalization, and death from SARS-CoV-2 in comparison with other populations. We report immune responses and renal injury markers in African American male patients hospitalized for COVID-19. Methods: This was a single-center, retrospective study of 56 COVID-19 infected hospitalized African American males 50+ years of age selected from among non-intensive care unit (ICU) and ICU status patients. Demographics, hospitalization-related variables, and medical history were collected from electronic medical records. Plasma samples collected close to admission (≤2 days) were evaluated for cytokines and renal markers; results were compared to a control group (n = 31) and related to COVID-19 in-hospital mortality. Results: Among COVID-19 patients, eight (14.2%) suffered in-hospital mortality; seven (23.3%) in the ICU and one (3.8%) among non-ICU patients. Interleukin (IL)-18 and IL-33 were elevated at admission in COVID-19 patients in comparison with controls. IL-6, IL-18, MCP-1/CCL2, MIP-1α/CCL3, IL-33, GST, and osteopontin were upregulated at admission in ICU patients in comparison with controls. In addition to clinical factors, MCP-1 and GST may provide incremental value for risk prediction of COVID-19 in-hospital mortality. Conclusions: Qualitatively similar inflammatory responses were observed in comparison to other populations reported in the literature, suggesting non-immunologic factors may account for outcome differences. Further, we provide initial evidence for cytokine and renal toxicity markers as prognostic factors for COVID-19 in-hospital mortality among African American males.

Comparison of clinical and echocardiographic features of first and second waves of COVID-19 at a large, tertiary medical center serving a predominantly African American patient population

As clinicians have gained experience in treating patients with the novel SARS-CoV-2 (COVID-19) virus, mortality rates for patients with acute COVID-19 infection have decreased. The Centers for Disease Control (CDC) has identified the African American population as having increased risk of COVID-19 associated mortality, however little is known about echocardiographic markers associated with increased mortality in this patient population. We aimed to compare the clinical and echocardiographic features of a predominantly African American patient cohort hospitalized with acute COVID-19 infection during the first (March–June 2020) and second (September–December 2020) waves of the COVID-19 pandemic, and to investigate which parameters are most strongly associated with composite all-cause mortality. We performed consecutive transthoracic echocardiograms (TTEs) on 105 patients admitted with acute COVID-19 infection during the first wave and 129 patients admitted during the second wave. TTE parameters including left ventricular ejection fraction (LVEF), left ventricular global longitudinal strain (LVGLS), right ventricular global longitudinal strain (RVGLS), right ventricular free-wall strain (RVFWS), and right ventricular basal diameter (RVBD) were compared between the two groups. Clinical and demographic characteristics including underlying co-morbidities, biomarkers, in-hospital treatment regimens, and outcomes were collected and analyzed. Univariable and multivariable analyses were performed to determine variables associated with all-cause mortality. There were no significant differences between the two waves in terms of age, gender, BMI, or race. Overall all-cause mortality was 35.2% for the first wave compared to 14.7% for the second wave (p < 0.001). Previous medical conditions were similar between the two waves with the exception of underlying lung disease (41.9% vs. 29.5%, p = 0.047). Echocardiographic parameters were significantly more abnormal in the first wave compared to the second: LVGLS (− 17.1 ± 5.0 vs. − 18.9 ± 4.8, p = 0.02), RVGLS (− 15.7 ± 5.9% vs. − 19.0 ± 5.9%, p < 0.001), RVFWS (− 19.5 ± 6.8% vs. − 23.2 ± 6.9%, p = 0.001), and RVBD (4.5 ± 0.8 vs. 3.9 ± 0.7 cm, p < 0.001). Stepwise multivariable logistic analysis showed mechanical ventilation, RVFWS, and RVGLS to be independently associated with mortality. In a predominantly African American patient population on the south side of Chicago, the clinical and echocardiographic features of patients hospitalized with acute COVID-19 infection demonstrated marked improvement from the first to the second wave of the pandemic, with a significant decrease in all-cause mortality. Possible explanations include implementation of evidence-based therapies, changes in echocardiographic practices, and behavioral changes in our patient population. Mechanical ventilation and right-sided strain-based markers were independently associated with mortality.

Actual Racial/Ethnic Disparities in COVID-19 Mortality for the Non-Hispanic Black Compared to Non-Hispanic White Population in 353 US Counties and Their Association with Structural Racism

Introduction

Although disparities in COVID-19 mortality have been documented at the national and state levels, no previous study has quantified such disparities at the county level by explicitly measuring race-specific COVID-19 death rates. In this paper, we quantify the racial/ethnic disparities in COVID-19 mortality between the non-Hispanic Black and non-Hispanic White populations at the county level by estimating age-adjusted, race-specific death rates.

Methods

Using COVID-19 case data from the Centers for Disease Control and Prevention, we calculated crude and indirect age-adjusted COVID-19 mortality rates for the non-Hispanic White and non-Hispanic Black populations in each of 353 counties for the period February 2, 2020, through January 30, 2021. Using linear regression analysis, we examined the relationship between several county-level measures of structural racism and the observed differences in racial disparities in COVID-19 mortality across counties.

Results

Ninety-three percent of the counties in our study experienced higher death rates among the Black compared to the White population, with an average ratio of Black to White death rates of 1.9 and a 17.5-fold difference between the disparity in the lowest and highest counties. Three traditional measures of structural racism were significantly related to the magnitude of the Black-White racial disparity in COVID-19 mortality rates across counties.

Conclusions

There are large disparities in COVID-19 mortality rates between the Black and White populations at the county level, there are profound differences in the level of these disparities, and those differences are directly related to the level of structural racism in a given county.

A Cross-Sectional Study of SARS-CoV-2 Seroprevalence between Fall 2020 and February 2021 in Allegheny County, Western Pennsylvania, USA

Seroprevalence studies are important for understanding the dynamics of local virus transmission and evaluating community immunity. To assess the seroprevalence for SARS-CoV-2 in Allegheny County, an urban/suburban county in Western PA, 393 human blood samples collected in Fall 2020 and February 2021 were examined for spike protein receptor-binding domain (RBD) and nucleocapsid protein (N) antibodies. All RBD-positive samples were evaluated for virus-specific neutralization activity. Our results showed a seroprevalence of 5.5% by RBD ELISA, 4.5% by N ELISA, and 2.5% for both in Fall 2020, which increased to 24.7% by RBD ELISA, 14.9% by N ELISA, and 12.9% for both in February 2021. Neutralization titer was significantly correlated with RBD titer but not with N titer. Using these two assays, we were able to distinguish infected from vaccinated individuals. In the February cohort, higher median income and white race were associated with serological findings consistent with vaccination. This study demonstrates a 4.5-fold increase in SARS-CoV-2 seroprevalence from Fall 2020 to February 2021 in Allegheny County, PA, due to increased incidence of both natural disease and vaccination. Future seroprevalence studies will need to include the effect of vaccination on assay results and incorporate non-vaccine antigens in serological assessments.

Can cilia provide an entry gateway for SARS-CoV-2 to human ciliated cells?

A worldwide coronavirus pandemic is in full swing and, at the time of writing, there are only few treatments that have been successful in clinical trials, but no effective antiviral treatment has been approved. Because of its lethality, it is important to understand the current strain's effects and mechanisms not only in the respiratory system but also in other affected organ systems as well. Past coronavirus outbreaks caused by SARS-CoV and MERS-CoV inflicted life-threatening acute kidney injuries (AKI) on their hosts leading to significant mortality rates, which went somewhat overlooked in the face of the severe respiratory effects. Recent evidence has emphasized renal involvement in SARS-CoV-2, stressing that kidneys are damaged in patients with COVID-19. The mechanism by which this virus inflicts AKI is still unclear, but evidence from other coronavirus strains may hold some clues. Two theories exist for the proposed mechanism of AKI: 1) the AKI is a secondary effect to reduced blood and oxygen levels causing hyperinflammation and 2) the AKI is due to cytotoxic effects. Kidneys express angiotensin-converting enzyme-2 (ACE2), the confirmed SARS-CoV-2 target receptor as well as collectrin, an ACE2 homologue that localizes to the primary cilium, an organelle historically targeted by coronaviruses. Although the available literature suggests that kidney damage is leading to higher mortality rates in patients with COVID-19, especially in those with preexisting kidney and cardiovascular diseases, the pathogenesis of COVID-19 is still being investigated. Here, we present brief literature review supporting our proposed hypothesis of a possible link between SARS-CoV-2 cellular infection and cilia.

Actual Racial/Ethnic Disparities in COVID-19 Mortality for the Non-Hispanic Black Compared to Non-Hispanic White Population in 35 US States and Their Association with Structural Racism

Introduction

While the increased burden of COVID-19 among the Black population has been recognized, most attempts to quantify the extent of this racial disparity have not taken the age distribution of the population into account. In this paper, we determine the Black–White disparity in COVID-19 mortality rates across 35 states using direct age standardization. We then explore the relationship between structural racism and differences in the magnitude of this disparity across states.

Methods

Using data from the Centers for Disease Control and Prevention, we calculated both crude and age-adjusted COVID-19 mortality rates for the non-Hispanic White and non-Hispanic Black populations in each state. We explored the relationship between a state-level structural racism index and the observed differences in the racial disparities in COVID-19 mortality across states. We explored the potential mediating effects of disparities in exposure based on occupation, underlying medical conditions, and health care access.

Results

Relying upon crude death rate ratios resulted in a substantial underestimation of the true magnitude of the Black–White disparity in COVID-19 mortality rates. The structural racism index was a robust predictor of the observed racial disparities. Each standard deviation increase in the racism index was associated with an increase of 0.26 in the ratio of COVID-19 mortality rates among the Black compared to the White population.

Conclusions

Structural racism should be considered a root cause of the Black–White disparity in COVID-19 mortality. Dismantling the long-standing systems of racial oppression is critical to adequately address both the downstream and upstream causes of racial inequities in the disease burden of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40615-021-01028-1.