Impact of Race and Socioeconomic Status on Outcomes in Patients Hospitalized with COVID-19

Examining Diabetes Status by the Social Determinants of Health Among Adults in Hawai'i

The social determinants of health (SDoH) influence health outcomes based on conditions from birth, growth, living, and age factors. Diabetes is a chronic condition, impacted by race, education, and income, which may lead to serious health consequences. In Hawai'i, approximately 11.2% of adults have been diagnosed with diabetes. The objective of this secondary cross-sectional study is to assess the relationship between the prevalence of diabetes and the social determinants of health among Hawai'i adults who participated in the Behavioral Risk Factor Surveillance System between 2018-2020. The prevalence of diabetes among adults was 11.0% (CI: 10.4-11.5%). Filipino, Japanese and Native Hawaiian adults had the highest prevalence of diabetes at 14.4% (CI: 12.7-16.2%), 14.2% (CI: 12.7-15.7%), and 13.2% (CI: 12.0-14.4%), respectively. Poverty level and education were significantly associated with diabetes status. Within employment categories, the adjusted odds ratio (AOR) for retired and unable to work adults were large at AOR: 1.51 (CI: 1.26-1.81) and AOR: 2.91 (CI: 2.28-3.72), respectively. SDoH can impact the development and management of diabetes. Understanding the role SDoH plays on diabetes status is crucial for promoting health equity, building community capacity, and improving diabetes management.

COVID-19 Related Knowledge, Attitudes, and Behaviors Among Black Men with Chronic Health Conditions: A Latent Profile Analysis

Research indicates that Black communities experienced disproportionately higher numbers of confirmed cases and fatalities throughout the COVID-19 pandemic with Black men experiencing marked reductions in life expectancy. Inequities were further magnified by known COVID-19 such as hypertension, diabetes, obesity, and higher prevalence of cardiovascular disease. The current project aimed to assess the knowledge, attitudes, and behaviors related to COVID-19 among Black men with chronic conditions. Specifically, we sought to determine whether COVID-19-related perspectives and behaviors impacted cross-sectional health outcomes. A national sample of Black men (N = 312) who self-reported at least one chronic disease responded to survey questions about their knowledge, attitude, and preventative behaviors (KAP) related to COVID-19. Analyses suggest that unique latent profiles based on COVID-19-related KAP differentially impacted participants' self-reported health and well-being for those low on KAP items. The discussion includes considerations on viral hygiene interventions, misinformation, stigma, and perceptions of discrimination.

Impact of SARS-CoV-2 Vaccine Rollout on Hispanic and Non-Hispanic Admission and Mortality Trends: An Interrupted Time Series Analysis

BACKGROUND

Challenges with SARS-CoV-2 vaccine prioritization, access, and hesitancy have influenced vaccination uptake.

RESEARCH QUESTION

Was the impact of SARS-CoV-2 vaccine rollout on COVID-19 monthly admission and mortality trends different between Hispanic and non-Hispanic populations?

STUDY DESIGN AND METHODS

We used interrupted time series analysis to conduct an ancillary study of the Viral Infection and Respiratory Illness Universal Study registry supplemented by electronic health record data from five participating Mayo Clinic sites in Florida, Arizona, Minnesota, and Wisconsin. We included hospitalized patients with COVID-19 admitted between April 2020 and December 2021. Our primary outcome was the impact of vaccine rollout on admission trends. Our secondary outcome was the impact of vaccine rollout on mortality trends.

RESULTS

This interrupted time series analysis includes 6,442 patients. Vaccine rollout was associated with improved monthly hospital admission trends among both Hispanic and non-Hispanic patients. Among Hispanic patients, pre-vaccine rollout, monthly admissions increased by 12.9% (95% CI, 8.1%-17.9%). Immediately after vaccine rollout, patient admissions declined by -66.3% (95% CI, -75.6% to -53.9%). Post-vaccine rollout, monthly admissions increased by 3.7% (95% CI, 0.2%-7.3%). Among non-Hispanic patients, pre-vaccine rollout, monthly admissions increased by 35.8% (95% CI, 33.4%-38.1%). Immediately after vaccine rollout, patient admissions declined by -75.2% (95% CI, -77.6% to -72.7%). Post-vaccine rollout, monthly admissions increased by 5.6% (95% CI, 4.5%-6.7%). These pre-vaccine rollout admission trends were significantly different (P < .001). Post-vaccine rollout, the change in admission trend was significantly different (P < .001). The associated beneficial impact from vaccine rollout on monthly hospital admission trends among Hispanic patients was significantly lower. The trend in monthly mortality rate was fourfold greater (worse) among Hispanic patients (8.3%; 95% CI, 3.6%-13.4%) vs non-Hispanic patients (2.2%; 95% CI, 0.6%-3.8%), but this was not shown to be related to vaccine rollout.

INTERPRETATION

SARS-CoV-2 vaccine rollout was associated with improved COVID-19 admission trends among non-Hispanic vs Hispanic patients. Vaccine rollout was not shown to influence mortality trends in either group, which were four times higher among Hispanic patients. Improved vaccine rollout may have reduced disparities in admission trends for Hispanic patients, but other factors influenced their mortality trends.

Disparities in COVID-19 Hospitalization at the Intersection of Race and Ethnicity and Income

BACKGROUND

Existing studies have elucidated racial and ethnic disparities in COVID-19 hospitalizations, but few have examined disparities at the intersection of race and ethnicity and income.

METHODS

We used a population-based probability survey of non-institutionalized adults in Michigan with a polymerase chain reaction-positive SARS-CoV-2 test before November 16, 2020. We categorized respondents by race and ethnicity and annual household income: low-income (< $50,000) Non-Hispanic (NH) Black, high-income (≥ $50,000) NH Black, low-income Hispanic, high-income Hispanic, low-income NH White, and high-income NH White. We used modified Poisson regression models, adjusting for sex, age group, survey mode, and sample wave, to estimate COVID-19 hospitalization prevalence ratios by race and ethnicity and income.

RESULTS

Over half of the analytic sample (n = 1593) was female (54.9%) and age 45 or older (52.5%), with 14.5% hospitalized for COVID-19. Hospitalization was most prevalent among low-income (32.9%) and high-income (31.2%) Non-Hispanic (NH) Black adults, followed by low-income NH White (15.3%), low-income Hispanic (12.9%), high-income NH White (9.6%), and high-income Hispanic adults (8.8%). In adjusted models, NH Black adults, regardless of income (low-income prevalence ratio [PR]: 1.86, 95% CI: 1.36-2.54; high-income PR: 1.57, 95% CI: 1.07-2.31), and low-income NH White adults (PR: 1.52, 95% CI: 1.12-2.07), had higher prevalence of hospitalization compared to high-income NH White adults. We observed no significant difference in the prevalence of hospitalization among Hispanic adults relative to high-income NH White adults.

CONCLUSIONS

We observed disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income for NH Black adults and low-income NH White adults relative to high-income NH White adults, but not for Hispanic adults.

Association between Patient Race and Ethnicity and Use of Invasive Ventilation in the United States

Rationale: Outcomes for people with respiratory failure in the United States vary by patient race and ethnicity. Invasive ventilation is an important treatment initiated based on expert opinion. It is unknown whether the use of invasive ventilation varies by patient race and ethnicity. Objectives: To measure 1) the association between patient race and ethnicity and the use of invasive ventilation; and 2) the change in 28-day mortality mediated by any association. Methods: We performed a multicenter cohort study of nonintubated adults receiving oxygen within 24 hours of intensive care admission using the Medical Information Mart for Intensive Care IV (MIMIC-IV, 2008-2019) and Phillips eICU (eICU, 2014-2015) databases from the United States. We modeled the association between patient race and ethnicity (Asian, Black, Hispanic, White) and invasive ventilation rate using a Bayesian multistate model that adjusted for baseline and time-varying covariates, calculated hazard ratios (HRs), and estimated 28-day hospital mortality changes mediated by differential invasive ventilation use. We reported posterior means and 95% credible intervals (CrIs). Results: We studied 38,258 patients, 52% (20,032) from MIMIC-IV and 48% (18,226) from eICU: 2% Asian (892), 11% Black (4,289), 5% Hispanic (1,964), and 81% White (31,113). Invasive ventilation occurred in 9.2% (3,511), and 7.5% (2,869) died. The adjusted rate of invasive ventilation was lower in Asian (HR, 0.82; CrI, 0.70-0.95), Black (HR, 0.78; CrI, 0.71-0.86), and Hispanic (HR, 0.70; CrI, 0.61-0.79) patients compared with White patients. For the average patient, lower rates of invasive ventilation did not mediate differences in 28-day mortality. For a patient on high-flow nasal cannula with inspired oxygen fraction of 1.0, the odds ratios for mortality if invasive ventilation rates were equal to the rate for White patients were 0.97 (CrI, 0.91-1.03) for Asian patients, 0.96 (CrI, 0.91-1.03) for Black patients, and 0.94 (CrI, 0.89-1.01) for Hispanic patients. Conclusions: Asian, Black, and Hispanic patients had lower rates of invasive ventilation than White patients. These decreases did not mediate harm for the average patient, but we could not rule out harm for patients with more severe hypoxemia.

Cluster Analysis reveals Socioeconomic Disparities among Elective Spine Surgery Patients

This work demonstrates the use of cluster analysis in detecting fair and unbiased novel discoveries. Given a sample population of elective spinal fusion patients, we identify two overarching subgroups driven by insurance type. The Medicare group, associated with lower socioeconomic status, exhibited an over-representation of negative risk factors. The findings provide a compelling depiction of the interwoven socioeconomic and racial disparities present within the healthcare system, highlighting their consequential effects on health inequalities. The results are intended to guide design of fair and precise machine learning models based on intentional integration of population stratification.

Upper airway and tracheostomy management in patients with COVID-19: A long-term acute care hospital (LTACH)

OBJECTIVE

Describe the tracheostomy and ventilation management of patients admitted due to COVID-19 as facilitated by speech language pathologists (SLPs) and otolaryngologists within the long-term acute care hospital (LTACH) setting.

STUDY DESIGN

Retrospective cohort study.

SETTING

Long-term acute care hospital.

SUBJECTS AND METHODS

A retrospective chart review was conducted on all patients admitted to RML Specialty Hospital for respiratory failure secondary to COVID-19 from April 1, 2020 to November 30, 2021. Demographic information, laryngeal findings, and tracheostomy management was reviewed. Descriptive statistics and chi-square analysis were performed.

RESULTS

Amongst the 213 subjects, 80.0 % arrived on mechanical ventilation. 23.0 % required otolaryngology consultation during LTACH stay due to poor Passy Muir Valve (PMV) or tracheostomy capping tolerance. 35 (71.4 %) of those consulted had abnormal laryngeal findings on exam with subglottic/tracheal stenosis and laryngeal edema being most common at 38.8 % and 20.4 %, respectively. 28.6 % of those with laryngeal findings were decannulated by discharge. Mechanical ventilator weaning and decannulation success were 86.6 % and 62.5 %, respectively. No association (p > 0.05) between number of intubations and abnormal laryngeal findings were found. No association (p > 0.05) between number of intubations or prone-positioning and decannulation success at discharge were found.

CONCLUSION

LTACHs can serve a specific role in upper airway rehabilitation and tracheostomy care in the post COVID-19 period. SLPs and otolaryngologists should be involved in the care of these patients to help facilitate decannulation and return to normal laryngeal function.

Neighborhood Factors Associated with COVID-19 Cases in California

BACKGROUND

There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups.

OBJECTIVE

To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 case rates in California.

DESIGN

Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences.

MAIN MEASURES

All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development.

KEY RESULTS

The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego.

CONCLUSION

Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

A study of factors affecting the length of hospital stay (LOS) of COVID-19 patients: A qualitative evidence in Iranian hospital

BACKGROUND

The present study aimed to identify the administrators' and physicians' experiences and viewpoints about the factors affecting the length of stay (LOS) of COVID-19 patients and provide valid operational evidence.

MATERIALS AND METHODS

The current study was carried out qualitatively and phenomenologically on experts, officials, and administrators of hospitals in 2021. Purposeful sampling was performed with the maximum diversity. To achieve a comprehensive view, snowball sampling was conducted. Twenty-one experts in the field of healthcare and emerging diseases participated in this study. Semi-structured interviews were used to collect the data. The study sites were universities of medical sciences and hospitals of the Ministry of Health of Iran. The interview questions included questions about the factors affecting the LOS and strategies for controlling the LOS of COVID-19 patients in infectious units. Text analysis was performed through the content analysis method in MAXQDA-10 software.

RESULTS

Based on the experts' viewpoints, several factors affected the LOS in COVID-19 patients. These factors were divided into five clinical, preclinical, economic, social, and management subcategories. The proposed solutions included policy solutions (supportive policies, development of home care services, training and culture building, and establishment of clinical guidelines) and operational solutions (drug management, promotion of equipment and facilities, telehealth or telemedicine services, and promotion of clinical and support processes).

CONCLUSION

One of the main tasks of hospital administrators is identifying the factors affecting the reduction of LOS. Among these factors, clinical and management factors in the hospital are more important and need more planning and attention by hospital officials.

Racial, socioeconomic, and neighborhood characteristics in relation to COVID-19 severity of illness for adolescents and young adults

This study tests the hypotheses that insurance status, race and ethnicity, and neighborhood characteristics are associated with hospital admission and severe health outcomes (Intensive Care Unit [ICU] admission and oxygen assistance) for youth and young adults who present to the emergency department (ED) with COVID-19 in a single, academic health system in Illinois, Rush University System for Health (RUSH). Demographic and clinical data from the electronic health record were collected for all 13- to 24-y-old patients seen at RUSH who tested positive for COVID-19 between March 2020 and 2021. Individual-level and neighborhood characteristics were analyzed to determine their association with hospital admission and severe health outcomes through generalized estimating equations. As of March 2021, 1,057 patients were seen in the ED within RUSH in which non-Hispanic White (odds ratio [OR], 2.96; 95% CI, 1.61-5.46; P = 0.001) and Hispanic (OR, 3.34; 95% CI, 1.84-6.10; P < 0.001) adolescents and youth were more likely to be admitted to the hospital compared with non-Hispanic Black/other adolescents and youth. Patients with public insurance or who were uninsured were less likely to be admitted to the ICU compared with those with private insurance (OR, 0.24; 95% CI, 0.09-0.64; P = 0.004). None of the neighborhood characteristics were significantly associated with hospital admission or severe health outcomes after adjusting for covariates. Our findings demonstrated that race and ethnicity were related to hospitalization, while insurance was associated with presentation severity due to COVID-19 for adolescents and young adults. These findings can aid public health investigators in understanding COVID-19 disparities among adolescents and young adults.

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

Purpose

The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary MIDRC dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC).

Approach

The Jensen-Shannon distance (JSD), a measure of similarity of two distributions, was used to longitudinally measure the representativeness of the distribution of (1) all unique patients in the MIDRC data to the 2020 US Census and (2) all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the combination of race and ethnicity.

Results

Representativeness of the MIDRC data by ethnicity and the combination of race and ethnicity was impacted by the percentage of CDC case counts for which this was not reported. The distributions by sex and race have retained their level of representativeness over time.

Conclusion

The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as the number of contributing institutions and overall number of subjects have grown. The use of metrics, such as the JSD support measurement of representativeness, is one step needed for fair and generalizable AI algorithm development.

Contribution of vaccinations to reducing socioeconomic disparities in COVID-19 deaths across U.S. counties

PURPOSE

Although increasing vaccine uptake is a key strategy to minimize Coronavirus Disease 2019 (COVID-19) deaths, evidence of the role of vaccination rates in attenuating the socioeconomic disparity in COVID-19 deaths is limited. We thus aimed to quantify the extent to which vaccination rates contribute to the association between U.S. county-level poverty rates and COVID-19 mortality rates.

METHODS

This nationwide study analyzed data on 3142 U.S. counties. We conducted mediation analyses to calculate the proportions eliminated (PE) of the association between poverty rate and COVID-19 deaths per 100,000 population by setting the COVID-19 vaccination rate (the proportion of fully vaccinated individuals as of December 31, 2021) to different observed values.

RESULTS

Adjusted for county-level characteristics, we estimate an additional 25.3 COVID-19 deaths per 100,000 population for each 10% increase in a county's poverty rate. When we set the vaccination rate at its maximum, 90th percentile, and 75th percentile of the observed values, the PE was estimated to be 81% (P < .001), 37% (P < .001), and 21% (P < .001), respectively.

CONCLUSIONS

Higher county-level poverty rates and lower vaccination rates were associated with greater COVID-19 mortality rates in the United States. Aggressive interventions to increase vaccine uptake could substantially reduce the social disparity in COVID-19 mortality.

Disadvantaged Students Utilize School Campus and Its Resources More Than Non-disadvantaged Students

Introduction Disadvantaged populations were disproportionately affected by the COVID-19 pandemic, both in the medical and educational settings. Lower-income families often do not have a laptop/desktop computer, adequate internet connection, or a dedicated study space. This unfortunately contributed to poorer academic performance during distance learning. To combat this, the Kirk Kerkorian School of Medicine (KKSOM) did not close down campus during the pandemic. This study analyzes the utilization of campus and live Zoom lectures by KKSOM students and its impact on educational outcomes. Methods We sent an Institutional Review Board (IRB)-approved survey to KKSOM students and asked about study locations, Zoom lecture attendance, and relationship quality during the pandemic. The class of 2024 had a unique experience as they were first-year students during the start of the COVID-19 pandemic and the transition to online learning. However, they always had access to campus and technological resources. We compared the survey scores from a Qualtrics electronic survey and the National Board of Medical Examiners (NBME) scores of students who self-indicated disadvantaged status, first-generation, underrepresented minority, and lower socioeconomic status to those who did not meet these criteria. Data analysis was done using SPSS software version 28.0.1.1 (IBM Corp., Armonk, NY). Results  First-generation students studied on campus more frequently than their counterparts (31% versus 20%, p < 0.05) and less at home in general (55.4% versus 67.5%, p < 0.05). Lower socioeconomic status (SES) students attended live Zoom lectures more often as well (56.6% versus 43.1%, p < 0.05). Lastly, no significant differences were found between disadvantaged and non-disadvantaged groups for the class of 2024 in the NBME exam scores or relationship quality scores. Conclusion Our results suggest that students from disadvantaged backgrounds spend more time studying on campus than at home. Additionally, during the COVID-19 pandemic, they attended live Zoom lectures more often than their non-disadvantaged counterparts. Access to campus was not restricted for KKSOM students during the pandemic. This may be one explanation for the lack of disparity between disadvantaged and non-disadvantaged students with regard to academic performance and relationship quality. This makes a strong argument for the importance of campus accessibility for the success of students, especially those from disadvantaged backgrounds.

Barriers and shortcomings in access to cardiovascular management and prevention for familial hypercholesterolemia during the COVID-19 pandemic

Familial hypercholesterolemia (FH) is a hereditary condition caused by mutations in the lipid pathway. The goal in managing FH is to reduce circulating low-density lipoprotein cholesterol and, therefore, reduce the risk of developing atherosclerotic cardiovascular disease (ASCVD). Because FH patients were considered high risk groups due to an increased susceptible for contracting COVID-19 infection, we hypothesized whether the effects of the pandemic hindered access to cardiovascular care. In this review, we conducted a literature search in databases Pubmed/Medline and ScienceDirect. We included a comprehensive analysis of findings from articles in English related and summarized the effects of the pandemic on cardiovascular care through direct and indirect effects. During the COVID-19 pandemic, FH patients presented with worse outcomes and prognosis, especially those that have suffered from early ASCVD. This caused avoidance in seeking care due to fear of transmission. The pandemic severely impacted consultations with lipidologists and cardiologists, causing a decline in lipid profile evaluations. Low socioeconomic communities and ethnic minorities were hit the hardest with job displacements and lacked healthcare coverage respectively, leading to treatment nonadherence. Lock-down restrictions promoted sedentary lifestyles and intake of fatty meals, but it is unclear whether these factors attenuated cardiovascular risk in FH. To prevent early atherogenesis in FH patients, universal screening programs, telemedicine, and lifestyle interventions are important recommendations that could improve outcomes in FH patients. However, the need to research in depth on the disproportionate impact within different subgroups should be the forefront of FH research.

Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska

The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities' capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities' ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world.

Impact of COVID-19's Economic Burden on Alcohol-Related Problems: An Indirect Effect of Depression, Stress, and Anxiety

The COVID-19 pandemic resulted in global monumental upheaval. Many people were displaced from their jobs and sources of income. COVID-19 was also linked to increased mental health difficulties and increased alcohol consumption and problems. The current study aims to identify the indirect effect of depression, stress, and anxiety on the relations between the economic burden of COVID-19 and alcohol problems. Participants (N = 344) were recruited via Amazon's Mechanical Turk (MTurk). Participants completed a questionnaire about substance use, mood, and the economic burden of COVID-19. Eligible participants were 18 years or older, consumed alcohol or cannabis within the past week, and verified through Amazon. Results indicated significant indirect effects of depression, stress, and anxiety on the association between the economic burden of COVID-19 and alcohol problems regardless of use. Findings revealed large effect sizes, suggesting that mental health symptomatology may have a large impact on the association between COVID-19's economic burden and alcohol-related problems. Findings suggest mental health difficulties indirectly effect the association between COVID-19's economic burden and alcohol-related problems. Intervention efforts targeting mental health may be beneficial in reducing alcohol problems among individuals experiencing distress due to large-scale public health impact, such as the COVID-19 pandemic.

A spatiotemporal analysis of the social determinants of health for COVID-19

This research aims to uncover how the association between social determinants of health and COVID-19 cases and fatality rate have changed across time and space. To begin to understand these associations and show the benefits of analysing temporal and spatial variations in COVID-19, we utilized Geographically Weighted Regression (GWR). The results emphasize the advantages for using GWR in data with a spatial component, while showing the changing spatiotemporal magnitude of association between a given social determinant and cases or fatalities. While previous research has demonstrated the merits of GWR for spatial epidemiology, our study fills a gap in the literature, by examining a suite of variables across time to reveal how the pandemic unfolded across the US at a county-level spatial scale. The results speak to the importance of understanding the local effects that a social determinant may have on populations at the county level. From a public health perspective, these results can be used for an understanding of the disproportionate disease burden felt by different populations, while upholding and building upon trends observed in epidemiological literature.

Obesity as an independent risk factor for COVID-19 severity and mortality

BACKGROUND

Since December 2019, the world has struggled with the COVID-19 pandemic. Even after the introduction of various vaccines, this disease still takes a considerable toll. In order to improve the optimal allocation of resources and communication of prognosis, healthcare providers and patients need an accurate understanding of factors (such as obesity) that are associated with a higher risk of adverse outcomes from the COVID-19 infection.

OBJECTIVES

To evaluate obesity as an independent prognostic factor for COVID-19 severity and mortality among adult patients in whom infection with the COVID-19 virus is confirmed.

SEARCH METHODS

MEDLINE, Embase, two COVID-19 reference collections, and four Chinese biomedical databases were searched up to April 2021.

SELECTION CRITERIA

We included case-control, case-series, prospective and retrospective cohort studies, and secondary analyses of randomised controlled trials if they evaluated associations between obesity and COVID-19 adverse outcomes including mortality, mechanical ventilation, intensive care unit (ICU) admission, hospitalisation, severe COVID, and COVID pneumonia. Given our interest in ascertaining the independent association between obesity and these outcomes, we selected studies that adjusted for at least one factor other than obesity. Studies were evaluated for inclusion by two independent reviewers working in duplicate.  DATA COLLECTION AND ANALYSIS: Using standardised data extraction forms, we extracted relevant information from the included studies. When appropriate, we pooled the estimates of association across studies with the use of random-effects meta-analyses. The Quality in Prognostic Studies (QUIPS) tool provided the platform for assessing the risk of bias across each included study. In our main comparison, we conducted meta-analyses for each obesity class separately. We also meta-analysed unclassified obesity and obesity as a continuous variable (5 kg/m2 increase in BMI (body mass index)). We used the GRADE framework to rate our certainty in the importance of the association observed between obesity and each outcome. As obesity is closely associated with other comorbidities, we decided to prespecify the minimum adjustment set of variables including age, sex, diabetes, hypertension, and cardiovascular disease for subgroup analysis.  MAIN RESULTS: We identified 171 studies, 149 of which were included in meta-analyses.  As compared to 'normal' BMI (18.5 to 24.9 kg/m2) or patients without obesity, those with obesity classes I (BMI 30 to 35 kg/m2), and II (BMI 35 to 40 kg/m2) were not at increased odds for mortality (Class I: odds ratio [OR] 1.04, 95% confidence interval [CI] 0.94 to 1.16, high certainty (15 studies, 335,209 participants); Class II: OR 1.16, 95% CI 0.99 to 1.36, high certainty (11 studies, 317,925 participants)). However, those with class III obesity (BMI 40 kg/m2 and above) may be at increased odds for mortality (Class III: OR 1.67, 95% CI 1.39 to 2.00, low certainty, (19 studies, 354,967 participants)) compared to normal BMI or patients without obesity. For mechanical ventilation, we observed increasing odds with higher classes of obesity in comparison to normal BMI or patients without obesity (class I: OR 1.38, 95% CI 1.20 to 1.59, 10 studies, 187,895 participants, moderate certainty; class II: OR 1.67, 95% CI 1.42 to 1.96, 6 studies, 171,149 participants, high certainty; class III: OR 2.17, 95% CI 1.59 to 2.97, 12 studies, 174,520 participants, high certainty). However, we did not observe a dose-response relationship across increasing obesity classifications for ICU admission and hospitalisation.

AUTHORS' CONCLUSIONS

Our findings suggest that obesity is an important independent prognostic factor in the setting of COVID-19. Consideration of obesity may inform the optimal management and allocation of limited resources in the care of COVID-19 patients.

Linking Sepsis with chronic arterial hypertension, diabetes mellitus, and socioeconomic factors in the United States: A scoping review

RATIONALE

Sepsis is a syndrome of life-threatening organ dysfunction caused by a dysregulated host immune response to infection. Social risk factors including location and poverty are associated with sepsis-related disparities. Understanding the social and biological phenotypes linked with the incidence of sepsis is warranted to identify the most at-risk populations. We aim to examine how factors in disadvantage influence health disparities related to sepsis.

METHODS

A scoping review was performed for English-language articles published in the United States from 1990 to 2022 on PubMed, Web of Science, and Scopus. Of the 2064 articles found, 139 met eligibility criteria and were included for review.

RESULTS

There is consistency across the literature of disproportionately higher rates of sepsis incidence, mortality, readmissions, and associated complications, in neighborhoods with socioeconomic disadvantage and significant poverty. Chronic arterial hypertension and diabetes mellitus also occur more frequently in the same geographic distribution as sepsis, suggesting a potential shared pathophysiology.

CONCLUSIONS

The distribution of chronic arterial hypertension, diabetes mellitus, social risk factors associated with socioeconomic disadvantage, and sepsis incidence, are clustered in specific geographical areas and linked by endothelial dysfunction. Such population factors can be utilized to create equitable interventions aimed at mitigating sepsis incidence and sepsis-related disparities.

The severity of COVID-19 across the spectrum of HIV

PURPOSE OF REVIEW

We review the intersection between the HIV and COVID-19 pandemics, particularly the impact of HIV infection on the development of severe COVID-19.

RECENT FINDINGS

Studies early in the COVID-19 pandemic did not find a clear link between HIV infection and increased COVID-19 severity or mortality. People with HIV (PWH) were more likely to have severe COVID-19, but much of the risk for worse outcomes was related to high rates of comorbidities and social determinants of health. Although comorbidities and social determinants of health are certainly critically important reasons for severe COVID-19 among PWH, recent large studies have found HIV infection - particularly when the CD4 cell count is low or HIV RNA is not suppressed - is an independent risk factor for COVID-19 severity. The link between HIV and severe COVID-19 highlights the need to diagnose and treat HIV as well as the importance of COVID-19 vaccination and treatment among PWH.

SUMMARY

People with HIV have faced increased challenges during the COVID-19 pandemic because of high rates of comorbidities and social determinants of health as well as the impact of HIV on COVID-19 severity. Information on the intersection of the two pandemics has been crucial to improving care for people with HIV.

Fusion of imaging and non-imaging data for disease trajectory prediction for coronavirus disease 2019 patients

Purpose

Our study investigates whether graph-based fusion of imaging data with non-imaging electronic health records (EHR) data can improve the prediction of the disease trajectories for patients with coronavirus disease 2019 (COVID-19) beyond the prediction performance of only imaging or non-imaging EHR data.

Approach

We present a fusion framework for fine-grained clinical outcome prediction [discharge, intensive care unit (ICU) admission, or death] that fuses imaging and non-imaging information using a similarity-based graph structure. Node features are represented by image embedding, and edges are encoded with clinical or demographic similarity.

Results

Experiments on data collected from the Emory Healthcare Network indicate that our fusion modeling scheme performs consistently better than predictive models developed using only imaging or non-imaging features, with area under the receiver operating characteristics curve of 0.76, 0.90, and 0.75 for discharge from hospital, mortality, and ICU admission, respectively. External validation was performed on data collected from the Mayo Clinic. Our scheme highlights known biases in the model prediction, such as bias against patients with alcohol abuse history and bias based on insurance status.

Conclusions

Our study signifies the importance of the fusion of multiple data modalities for the accurate prediction of clinical trajectories. The proposed graph structure can model relationships between patients based on non-imaging EHR data, and graph convolutional networks can fuse this relationship information with imaging data to effectively predict future disease trajectory more effectively than models employing only imaging or non-imaging data. Our graph-based fusion modeling frameworks can be easily extended to other prediction tasks to efficiently combine imaging data with non-imaging clinical data.

Long-Term Effects of SARS-CoV-2 in the Brain: Clinical Consequences and Molecular Mechanisms

Numerous investigations have demonstrated significant and long-lasting neurological manifestations of COVID-19. It has been suggested that as many as four out of five patients who sustained COVID-19 will show one or several neurological symptoms that can last months after the infection has run its course. Neurological symptoms are most common in people who are less than 60 years of age, while encephalopathy is more common in those over 60. Biological mechanisms for these neurological symptoms need to be investigated and may include both direct and indirect effects of the virus on the brain and spinal cord. Individuals with Alzheimer's disease (AD) and related dementia, as well as persons with Down syndrome (DS), are especially vulnerable to COVID-19, but the biological reasons for this are not clear. Investigating the neurological consequences of COVID-19 is an urgent emerging medical need, since close to 700 million people worldwide have now had COVID-19 at least once. It is likely that there will be a new burden on healthcare and the economy dealing with the long-term neurological consequences of severe SARS-CoV-2 infections and long COVID, even in younger generations. Interestingly, neurological symptoms after an acute infection are strikingly similar to the symptoms observed after a mild traumatic brain injury (mTBI) or concussion, including dizziness, balance issues, anosmia, and headaches. The possible convergence of biological pathways involved in both will be discussed. The current review is focused on the most commonly described neurological symptoms, as well as the possible molecular mechanisms involved.

Variations in COVID-19 Hospital Mortality by Patient Race/Ethnicity and Hospital Type in Illinois

BACKGROUND AND OBJECTIVES

It is controversial whether hospital care mitigated or exacerbated population level racial and ethnic disparities in COVID-19 mortality. To begin answering that question, this study analyzed variations in COVID-19 hospital mortality in Illinois by patient race and ethnicity and by hospital characteristics, while providing an estimate of hospital-level variation in COVID-19 mortality.

METHOD

This is a retrospective cohort study based on hospital administrative data for adult patients with COVID-19 discharged from acute care, non-federal Illinois hospitals from April 1, 2020 through June 30, 2021. The association of patient and hospital characteristics with the likelihood of death was analyzed using multilevel logistic regression.

RESULTS

There were 158,569 COVID-19-coded admissions to 181 general hospitals in Illinois; 14.5% resulted in death or discharge to hospice. Hospital deaths accounted for nearly 90% of all COVID-19-associated deaths over 15 months in Illinois. After adjusting for patient- and hospital-level characteristics, Hispanic patients had higher mortality risk (aOR 1.26, 95% CI: 1.20-1.33) as compared with non-Hispanic White patients, while non-Hispanic Black patients had lower mortality risk (aOR 0.75, 95% CI: 0.71-0.79). Safety net hospitals receiving disproportionate share hospital (DSH) funds had higher mortality risk (aOR 1.81, 95% CI: 1.43-2.30) compared with other hospitals.

CONCLUSION

Risk-adjusted COVID-19 hospital mortality was highest among patients of Hispanic ethnicity, while non-Hispanic Black patients had lower risk than non-Hispanic White patients. There was significant variation in hospital mortality rates, with particularly high safety net hospital mortality.

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis

BACKGROUND

The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes.

METHODS

Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05.

FINDINGS

Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures.

INTERPRETATION

COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises.

FUNDING

Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Perceptions of the SARS-CoV2 pandemic: a small comparative survey analysis between language preference populations in a United States community health center

In 2019, a new variant of coronavirus, SARS-CoV-2 (COVID-19) created a global pandemic that has highlighted and exacerbated health disparities. Educating the general public about COVID-19 is one of the primary mitigation strategies amongst health professionals. English is not the preferred language for an estimated 22% of the United States population making effective mass communication efforts difficult to achieve. This study seeks to understand and compare several topics surrounding COVID-19 health communication and healthcare disparities between individuals with English language preference (ELP) and non-English language preference (NELP) within the United States. A survey available in seven languages asking about knowledge and opinions on COVID-19, vaccines, preferred sources of health information, and other questions, was administered February-April 2021 to patients at an urban federally qualified health center that also serves global refugees and immigrants. Descriptive statistics and comparative analysis were performed to identify differences between ELP and NELP individuals. Analysis of 144 surveys, 33 of which were NELP, showed 90.97% of all patients agreed that COVID-19 was a serious disease and 66.67% would receive the COVID-19 vaccine. There were numerous differences between ELP and NELP individuals, including trust in government, symptom identification, preferred source of health information, and feelings that cultural needs had been met. This study has identified several significant differences in patient perceptions relating to the COVID-19 pandemic when comparing NELP to ELP and highlighted areas where improvement can occur. Applying this information, easily utilized targeted resources can be created to quickly intervene and address health disparities among patients seeking care at an urban community health center.

Socioeconomic inequality in hospital case fatality rate and care among children and adolescents hospitalized for COVID-19 in Brazil

OBJECTIVE

To analyze the association of hospital case fatality rate and care received by children and adolescents hospitalized for COVID-19 with the gross domestic product (GDP) per capita of Brazilian municipalities and regions of residence.

METHODS

Data were collected from the Influenza Epidemiological Surveillance Information System and the Brazilian Institute of Geography and Statistics. The dichotomous outcomes analyzed were hospital case fatality rate of COVID-19, biological samples collected for COVID-19 diagnosis, X-rays, computed tomography (CT) scans, use of ventilatory support, and intensive care unit hospitalization. The covariates were municipal GDP per capita and the Brazilian region of residence. Poisson regression was used for the outcomes recorded in 2020 and 2021 in Brazil, covering the two COVID-19 waves in the country, adjusted for age and gender.

RESULTS

The hospital case fatality rate was 7.6%. In municipalities with lower GDP per capita deciles, the case fatality rate was almost four times higher among children and twice as high in adolescents compared to cities with higher deciles. Additionally, residents of municipalities with lower GDP per capita had fewer biological samples collected for diagnosis, X-ray examinations, and CT scans. We found regional disparities associated with case fatality rate, with worse indicators in the North and Northeast regions. The findings remained consistent over the two COVID-19 waves.

CONCLUSION

Municipalities with lower GDP per capita, as well as the North and Northeast regions, had worse indicators of hospital case fatality rate and care.

Inpatient outcomes comparing White and Black patients with obesity hospitalized for COVID-19 infection

OBJECTIVE

Comparisons between Black and White patients with obesity hospitalized with COVID-19 have not been fully studied. We sought to determine outcomes differences between these two groups.

METHODS

National Inpatient Sample database year 2020 was studied using multivariable regression to compare Black and White patients with obesity and COVID-19 infection. Outcomes were in-hospital mortality, length of stay, and hospital charges.

RESULTS

205,365 Black and White patients with obesity were hospitalized for COVID-19. 141,010 (68.6%) were White and 64,355 (31.3%) were Black. Black patients were younger (mean age [± standard error] 55.5 ± 0.14 vs. 62.1± 0.11; p < 0.01), more likely female (63.2% vs 50.9%; p < 0.01), and had lower mean comorbidity (Elixhauser score means [± standard error] 4.4 ± 0.02 vs. 4.6 ± 0.01; p < 0.01) than White patients. Black patients had lower odds of in-hospital mortality (adjusted Odds Ratio {aOR}=0.86 CI [0.77-0.97]; p = 0.01), longer hospital stays (adjusted Mean Difference {aMD}=0.32 days CI [0.14-0.51]; p < 0.01) and incurred higher, though non-significant hospital charges (aMD = $2,144 CI [-2270-+6560]; p = 0.34) than White patients.

CONCLUSION

During the first year of the pandemic, Black patients with obesity and COVID-19 were less likely to die during the incident hospitalization but used greater hospital resources compared to White patients.

Impact of Hospital Safety-Net Burden on Outcomes of In-Hospital Cardiac Arrest in the United States

High safety-net burden hospitals (HBHs) treating large numbers of uninsured or Medicaid-insured patients have generally been linked to worse clinical outcomes. However, limited data exist on the impact of the hospitals' safety-net burden on in-hospital cardiac arrest (IHCA) outcomes in the United States.

OBJECTIVES

To compare the differences in survival to discharge, routine discharge home, and healthcare resource utilization between patients at HBH with those treated at low safety-net burden hospital (LBH).

DESIGN SETTING AND PARTICIPANTS

Retrospective cohort study across hospitals in the United States: Hospitalized patients greater than or equal to 18 years that underwent cardiopulmonary resuscitation (CPR) between 2008 and 2018 identified from the Nationwide Inpatient Database. Data analysis was conducted in January 2022.

EXPOSURE

IHCA.

MAIN OUTCOMES AND MEASURES

The primary outcome is survival to hospital discharge. Other outcomes are routine discharge home among survivors, length of hospital stay, and total hospitalization cost.

RESULTS

From 2008 to 2018, an estimated 555,016 patients were hospitalized with IHCA, of which 19.2% occurred at LBH and 55.2% at HBH. Compared with LBH, patients at HBH were younger (62 ± 20 yr vs 67 ± 17 yr) and predominantly in the lowest median household income (< 25th percentile). In multivariate analysis, HBH was associated with lower chances of survival to hospital discharge (adjusted odds ratio [aOR], 0.88; 95% CI, 0.85-0.96) and lower odds of routine discharge (aOR, 0.6; 95% CI, 0.47-0.75), compared with LBH. In addition, IHCA patients at publicly owned hospitals and those with medium and large hospital bed size were less likely to survive to hospital discharge, while patients with median household income greater than 25th percentile had better odds of hospital survival.

CONCLUSIONS AND RELEVANCE

Our study suggests that patients who experience IHCA at HBH may have lower rates and odds of in-hospital survival and are less likely to be routinely discharged home after CPR. Median household income and hospital-level characteristics appear to contribute to survival.

Desigualdade socioeconômica na letalidade e no cuidado hospitalar de crianças e adolescentes internados por COVID-19 no Brasil

RESUMO Objetivo: Analisar a associação entre a letalidade e o cuidado hospitalar recebido por crianças e adolescentes internados por COVID-19 e o produto interno bruto (PIB) per capita dos municípios brasileiros e a região de residência. Métodos: Os dados foram extraídos do Sistema de Informação de Vigilância Epidemiológica da Gripe e do Instituto Brasileiro de Geografia e Estatística. Analisaram-se como desfechos dicotômicos a letalidade hospitalar por COVID-19, a coleta de amostra biológica para diagnóstico de COVID-19, a realização de exames raio X e tomografia, o uso de suporte ventilatório e a internação em unidade de terapia intensiva. As covariáveis foram o PIB municipal per capita e a região brasileira de residência. Foi realizada regressão de Poisson para os desfechos registrados em 2020 e 2021 no Brasil e segundo o período compreendido em duas ondas de COVID-19 no país, ajustando-a por idade e sexo. Resultados: A letalidade hospitalar foi de 7,6%. Nos municípios dos menores decis de PIB per capita a letalidade foi quase quatro vezes maior entre crianças e duas vezes mais elevada entre adolescentes quando comparada àquela dos maiores decis. Adicionalmente, os residentes de municípios com menor PIB per capita realizaram menos coleta de amostra biológica para diagnóstico, exames de raio X e tomografias. Foram encontradas disparidades regionais associadas à letalidade, com piores indicadores nas regiões Norte e Nordeste. Os achados mantiveram-se consistentes durante as duas ondas de COVID-19. Conclusão: Em municípios com menor PIB per capita e das regiões Norte e Nordeste houve piores indicadores de letalidade e cuidado hospitalar.

Comorbidities, sociodemographic factors, and determinants of health on COVID-19 fatalities in the United States

Previous studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities. This cross-sectional study used county-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by the COVID-19 Community Vulnerability Index (CCVI). Effect estimates of COVID-19 fatality rates for risk factors such as comorbidities, sociodemographic factors and determinant of health. Factors associated with reducing COVID-19 fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influenced case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and chronic obstructive pulmonary disease (COPD) diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of chronic kidney disease (CKD) within counties were often the strongest predictor of increased case-fatality rates for several regions. Our findings highlight the importance of considering the full context when evaluating contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

COVID-19 Incidence and Death Rates in the Southern Region of the United States: A Racial and Ethnic Association

The SARS-CoV-2 virus responsible for the COVID-19 pandemic continues to spread worldwide, with over half a billion cases linked to over 6 million deaths globally. COVID-19 has impacted populations unequally based on income, age, race, sex, and geographical location. This study aimed to characterize COVID-19 incidence and death rate trends in six states of the southern region of the USA and to understand the demographic and racial differences in its incidence and death rates. Data for the study were collected from the COVID-19 Data tracker of the Centers for Disease Control and Prevention for the following southern states: Alabama (AL), Florida (FL), Georgia (GA), Louisiana (LA), Mississippi (MS), and Tennessee (TN). The results showed a significant geographical variation in the COVID-19 cases and related deaths. Significant variations in COVID-19 cases and death rates were observed among different races and ethnic groups. The highest number of COVID-19 cases were observed among the Hispanic and Black populations, and the highest death rates were found among non-Hispanic Blacks and Whites. The southern states included in this paper showed a high number of COVID-19 cases and high death rates during the study period. These increased rates may result from the low socioeconomic status and large minority populations.

Race-related differences in the economic, healthcare-access, and psychological impact of COVID-19: personal resources associated with resilience

Background

The impact of the coronavirus disease 2019 (COVID) is worse among those with fewer financial resources, in jobs not amenable to remote work, and in denser living conditions. People of color are more likely to be among these vulnerable groups. Although race itself is a social construction and not based on underlying genetic/biological differences, this study investigated race/ethnicity differences in the negative repercussions of COVID and in the benefits of psychological and social resources.

Methods

This cross-sectional, web-based study (n = 4817) was administered to a heterogeneous United States sample in Spring/Summer 2020. Information was gathered on the following COVID-specific variables: Infection Status, Coping with Lockdown, Social Support, Post-traumatic Growth, Interpersonal Conflict, Worry about Self, Financial Impact on Family, Lack of Money, Inadequate Access to Healthcare, and Housing Instability. Resilience was operationalized as the ability to maintain a sense of wellness in the face of the pandemic, using the DeltaQuest Wellness measure. Multivariate linear regression (adjusting for demographics) and propensity-matched cohort analysis (matched on demographics) evaluated the impact of COVID-specific variables on Wellness in separate models for Whites and Non-Whites.

Findings

Both sets of models retained the same COVID-specific variables and explained about half of the variance in wellness. Coping with Lockdown, Social Support, and Post-traumatic Growth were associated with higher levels of Wellness in both Whites and Non-Whites, while Interpersonal Conflict and Worry about Self were associated with lower levels of Wellness. While these associations are similar, Non-Whites reported worse levels of some positive resources (e.g., social support) and more challenging levels of negative stressors (e.g., interpersonal, worry, financial). Non-Whites also reported much higher levels of post-traumatic growth.

Conclusion

COVID was a source of worry and even conflict, but also unlocked people’s resources in use of health-enhancing behavioral strategies, social support, and renewed gratitude for sources of personal meaning and value. The similar relationships between Whites and Non-Whites on wellness and COVID-specific stressors across racial groups underscore that race is a social construction, not a biological fact. Focusing on a renewed appreciation for sources of personal meaning, and particularly faith, seemed to buffer much of the COVID-related stress for Non-Whites.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41687-022-00514-2.

Forgone Health Care for Non-COVID-19-Related Needs Among Medicare Beneficiaries During the COVID-19 Pandemic, Summer 2020-Winter 2021

INTRODUCTION

Forgone health care, defined as not using health care despite perceiving a need for it, is associated with poor health outcomes, especially among people with chronic conditions. The objective of our study was to examine how the pandemic affected forgone health care during 3 stages of the pandemic.

METHODS

We used the Medicare Current Beneficiary Survey COVID-19 Rapid Response Questionnaire administered in summer 2020, fall 2020, and winter 2021 to examine sociodemographic characteristics, chronic diseases, COVID-19 vaccination status, and telehealth availability in relation to beneficiary reports of forgone health care.

RESULTS

Of the 3 periods studied, the overall rate of forgone health care was highest in summer 2020 (20.8%), followed by fall 2020 (7.8%) and winter 2021 (6.5%). COVID-19 vaccination status, age, sex, race and ethnicity, US region, availability of primary care telehealth appointments, and chronic conditions (heart disease, arthritis, depression, osteoporosis or a broken hip, and diabetes or high blood glucose) were significantly related to forgone care.

CONCLUSION

High rates of forgone care among Medicare participants varied over time and were significantly related to beneficiary characteristics. Our findings highlight the need for health care reform and changes in policy to address the issue of access to care for people with chronic conditions during a pandemic or other public health emergency.

Prevalence of surgery cancelation and challenges in restarting elective surgery in the pandemic: A cross-sectional study

Objectives

The COVID-19 pandemic caused primary disruption of health services, especially to elective surgery. As the pandemic goes in waves of high and low infection rates in a country, restarting elective surgery must be dynamic while balancing patients’ needs, staff safety and the hospital capacity. We aim to report the prevalence of elective surgery and minimally invasive procedures cancelation due to positive Covid-19 screening and describe steps in restarting elective cases after the third wave of Covid-19 infection.

Methods

This study was a descriptive cross-sectional study in Indonesia's tertiary referral and teaching hospital from January to September 2021. Subjects were patients scheduled for elective surgery or minimally invasive procedures from our outpatient clinic. Subjects were screened for SARS-CoV-2 using real-time polymerase chain reaction (rRT-PCR) 24-48 hours before scheduled surgery or intervention. Data was taken from the hospital information system and the central operating theatre online surgical list. Statistical analysis is presented in percentage.

Results

There were 5286 subjects identified for the study, and 3088 were included with an available PCR result from the outpatient department. The average elective cancelation rate was 7.4%, and the highest cancelation was on August 2021, with 14.7%. All subjects with positive results were asymptomatic, with more than 90% cycle time rRT-PCR above 30.

Conclusion

Elective surgery cancelation can reflect a trend in community infection, and monitoring its values is crucial for saving elective surgery plans during a pandemic.

Vulnerable populations during COVID-19 response: Health-related quality of life among Chinese population and its influence due to socio-demographic factors and loneliness

Background

Infection control policy affected people's wellbeing during the COVID-19 pandemic, especially those vulnerable populations. This study aimed to compare the health-related quality of life (HRQoL) of the Hong Kong (HK) Chinese population under the pandemic with the normative profiles and explore its influencing factors, including socio-demographic characteristics, loneliness, and the interaction between them.

Methods

A cross-sectional questionnaire survey (301 online and 202 in-person) was conducted between June and December 2020 among the adult Chinese population during the 2nd wave of COVID-19 in HK. HRQoL was measured by a Hong Kong validated EQ-5D-5L instrument (EQ-5D-5L HK). Loneliness was measured by a single-item question regarding the frequency of the participants reporting feeling lonely and their subjective social status was measured by the MacArthur Scale of Subjective Social Status. A series of Tobit regressions was conducted. The interaction terms between socio-demographics and loneliness were also examined to decide their association with HRQoL.

Results

A total of 503 responses were collected. The level of HRQoL of the respondents was significantly lower than the referred norms profile among the local general population. The findings identified that younger age, single, a higher subjective social status, and a lower level of loneliness were significantly associated with better HRQoL. Moreover, age and marital status were significant moderators in the relationship between loneliness and HRQoL.

Conclusion

The present study found that some population groups face additional vulnerabilities during the pandemic in terms of declined HRQoL. In addition, reducing loneliness can protect the HRQoL during the pandemic, especially among older people. This article provides useful information for policy-makers to design and promote effective services or provide education to improve the connection of people and recover from the global pandemic.

Income differences in COVID-19 incidence and severity in Finland among people with foreign and native background: A population-based cohort study of individuals nested within households

BACKGROUND

Although intrahousehold transmission is a key source of Coronavirus Disease 2019 (COVID-19) infections, studies to date have not analysed socioeconomic risk factors on the household level or household clustering of severe COVID-19. We quantify household income differences and household clustering of COVID-19 incidence and severity.

METHODS AND FINDINGS

We used register-based cohort data with individual-level linkage across various administrative registers for the total Finnish population living in working-age private households (N = 4,315,342). Incident COVID-19 cases (N = 38,467) were identified from the National Infectious Diseases Register from 1 July 2020 to 22 February 2021. Severe cases (N = 625) were defined as having at least 3 consecutive days of inpatient care with a COVID-19 diagnosis and identified from the Care Register for Health Care between 1 July 2020 and 31 December 2020. We used 2-level logistic regression with individuals nested within households to estimate COVID-19 incidence and case severity among those infected. Adjusted for age, sex, and regional characteristics, the incidence of COVID-19 was higher (odds ratio [OR] 1.67, 95% CI 1.58 to 1.77, p < 0.001, 28.4% of infections) among individuals in the lowest household income quintile than among those in the highest quintile (18.9%). The difference attenuated (OR 1.23, 1.16 to 1.30, p < 0.001) when controlling for foreign background but not when controlling for other household-level risk factors. In fact, we found a clear income gradient in incidence only among people with foreign background but none among those with native background. The odds of severe illness among those infected were also higher in the lowest income quintile (OR 1.97, 1.52 to 2.56, p < 0.001, 28.0% versus 21.6% in the highest quintile), but this difference was fully attenuated (OR 1.08, 0.77 to 1.52, p = 0.64) when controlling for other individual-level risk factors-comorbidities, occupational status, and foreign background. Both incidence and severity were strongly clustered within households: Around 77% of the variation in incidence and 20% in severity were attributable to differences between households. The main limitation of our study was that the test uptake for COVID-19 may have differed between population subgroups.

CONCLUSIONS

Low household income appears to be a strong risk factor for both COVID-19 incidence and case severity, but the income differences are largely driven by having foreign background. The strong household clustering of incidence and severity highlights the importance of household context in the prevention and mitigation of COVID-19 outcomes.

Impact of social determinants of health on colorectal cancer screening and surveillance in the COVID reopening phase

BACKGROUND/AIMS

Procedural delays due to the coronavirus disease 2019 (COVID-19) pandemic may exacerbate disparities in colorectal cancer (CRC) preventive care. We aimed to measure racial and socioeconomic disparities in the prioritization of CRC screening or adenoma surveillance during the COVID reopening period.

METHODS

We identified CRC screening or surveillance colonoscopies performed during two time periods: (1) 9 June 2019-30 September 2019 (pre-COVID) and (2) 9 June 2020-30 September 2020 (COVID reopening). We recorded the procedure indication, patient age, sex, race/ethnicity, primary language, insurance status and zip code. Multivariable logistic regression was used to determine factors independently associated with undergoing colonoscopy in the COVID reopening era.

RESULTS

We identified 1473 colonoscopies for CRC screening or adenoma surveillance; 890 occurred in the pre-COVID period and 583 occurred in the COVID reopening period. In total 342 (38.4%) pre-COVID patients underwent adenoma surveillance and 548 (61.6%) underwent CRC screening; in the COVID reopening cohort, 257 (44.1%) underwent adenoma surveillance and 326 (55.9%) underwent CRC screening (P = 0.031). This increased proportion of surveillance procedures in the reopening cohort was statistically significant on multivariable analysis [odds ratio (OR), 1.26; 95% confidence interval (CI), 1.001-1.58]. Black patients comprised 17.4% of the pre-COVID cohort, which declined to 15.3% (P = 0.613). There was a trend toward an inverse association between reopening phase colonoscopy and Medicaid insurance compared with commercial insurance (OR, 0.71; 95% CI, 0.49-1.04). No significant associations were found between reopening phase colonoscopy and the remaining variables.

CONCLUSIONS

During the COVID reopening period, colonoscopies for CRC fell by over one-third with significantly more surveillance than screening procedures. Nonwhite patients and non-English speakers comprised a shrinking proportion in the COVID reopening period.

Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction

INTRODUCTION

Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization.

METHODS

Electronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance.

RESULTS

A total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821.

CONCLUSIONS

Cardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race.

Influence of SARS-CoV-2 on airway mucus production: A review and proposed model

Coronavirus disease 2019 (COVID-19) is a worldwide pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has affected millions of lives. Individuals who survive severe COVID-19 can experience sustained respiratory symptoms that persist for months after initial infection. In other airway diseases, abnormal airway mucus contributes to sustained airway symptoms. However, the impact of SARS-CoV-2 on airway mucus has received limited attention. In the current review, we assess literature describing the impact of SARS-CoV-2 on airway pathophysiology with specific emphasis on mucus production. Accumulating evidence suggests that the 2 major secreted airway mucin glycoproteins, MUC5AC and MUC5B, are abnormal in some patients with COVID-19. Aberrations in MUC5AC or MUC5B in response to SARS-CoV-2 infection are likely due to inflammation, though the responsible mechanisms have yet to be determined. Thus, we also provide a proposed model highlighting mechanisms that can contribute to acute and sustained mucus abnormalities in SARS-CoV-2, with an emphasis on inflammatory cells and mediators, including mast cells and histamine. Last, we bring to light the challenges of studying abnormal mucus production in SARS-CoV-2 infections and discuss the strengths and limitations of model systems commonly used to study COVID-19. The evidence to date suggests that ferrets, nonhuman primates, and cats may have advantages over other models to investigate mucus in COVID-19.

Association of COVID-19 Case-Fatality Rate With State Health Disparity in the United States

Background

The disproportionate burden of COVID-19 pandemic has become a major concern in the United States (US), but the association between COVID-19 case-fatality rate (CFR) and factors influencing health outcomes at a state level has not been evaluated.

Methods

We calculated COVID-19 CFR for three different waves using COVID Data Tracker from the Centers for Disease Control and Prevention. America's Health Rankings assesses the factors that influence health outcomes to determine state's health rankings. The association between COVID-19 CFR and state health disparities was analyzed by linear regression.

Results

States with better rankings of Physical Environment were associated with lower CFR for the 1st wave (β = 0.06%, R2 = 0.170, P = 0.003). There was a paradoxical association between the 2nd wave CFR and Clinical Care (β = -0.04%, R2 = 0.112, P = 0.017) and Overall health rankings (β = -0.03%, R2 = 0.096, P = 0.029). For the 3rd wave, states with better rankings of Overall health factors (β = 0.01%, R2 = 0.179, P = 0.002), Social & Economic Factors (β = 0.01%, R2 = 0.176, P = 0.002), Behaviors (β = 0.01%, R2 = 0.204, P < 0.001), and Health Outcomes (β = 0.01%, R2 = 0.163, P = 0.004) were associated with lower CFR. COVID-19 vaccination coverage was also associated with state health rankings (at least one dose: β = -0.13%, R2 = 0.305, P < 0.001; fully vaccinated: β = -0.06%, R2 = 0.120, P = 0.014).

Conclusions

These findings suggested targeted public health interventions and mitigation strategies addressing health disparities are essential to improve inequitable outcomes of COVID-19 in the US.

Advanced age, comorbidity and the risk of mortality in COVID-19 infection

Background

Objective

Methods

Results

Conclusions

Breast cancer diagnosis and treatment during the COVID-19 pandemic in a nationwide, insured population

Purpose

The early months of the COVID-19 pandemic led to reduced cancer screenings and delayed cancer surgeries. We used insurance claims data to understand how breast cancer incidence and treatment after diagnosis changed nationwide over the course of the pandemic.

Methods

Using the Optum Research Database from January 2017 to March 2021, including approximately 19 million US adults with commercial health insurance, we identified new breast cancer diagnoses and first treatment after diagnosis. We compared breast cancer incidence and proportion of newly diagnosed patients receiving pre-operative systemic therapy pre-COVID, in the first 2 months of the COVID pandemic and in the later part of the COVID pandemic.

Results

Average monthly breast cancer incidence was 19.3 (95% CI 19.1–19.5) cases per 100,000 women and men pre-COVID, 11.6 (95% CI 10.8–12.4) per 100,000 in April–May 2020, and 19.7 (95% CI 19.3–20.1) per 100,000 in June 2020–February 2021. Use of pre-operative systemic therapy was 12.0% (11.7–12.4) pre-COVID, 37.7% (34.9–40.7) for patients diagnosed March–April 2020, and 14.8% (14.0–15.7) for patients diagnosed May 2020–January 2021. The changes in breast cancer incidence across the pandemic did not vary by demographic factors. Use of pre-operative systemic therapy across the pandemic varied by geographic region, but not by area socioeconomic deprivation or race/ethnicity.

Conclusion

In this US-insured population, the dramatic changes in breast cancer incidence and the use of pre-operative systemic therapy experienced in the first 2 months of the pandemic did not persist, although a modest change in the initial management of breast cancer continued.

Citizenship and Social Responsibility in Surgery: A Review

Importance

Social determinants of health have been shown to be key drivers of disparities in access to surgical care and surgical outcomes. Though the concept of social responsibility has received growing attention in the medical field, little has been published contextualizing social responsibility in surgery. In this narrative review, we define social responsibility as it relates to surgery, explore the duty of surgeons to society, and provide examples of social factors associated with adverse surgical outcomes and how they can be mitigated.

Observations

The concept of social responsibility in surgery has deep roots in medical codes of ethics and evolved alongside changing views on human rights and the role of social factors in disease. The ethical duty of surgeons to society is based on the ethical principles of benevolence and justice and is grounded within the framework of the social contract. Surgeons have a responsibility to understand how factors such as patient demographics, the social environment, clinician awareness, and the health care system are associated with inequitable patient outcomes. Through education, we can empower surgeons to advocate for their patients, address the causes and consequences of surgical disparities, and incorporate social responsibility into their daily practice.

Conclusions and Relevance

One of the greatest challenges in the field of surgery is ensuring that surgical care is provided in an equitable and sustainable way. Surgeons have a duty to understand the factors that lead to health care disparities and use their knowledge, skills, and privileged position to address these issues at the individual and societal level.

The association between area deprivation and COVID-19 incidence: a municipality-level spatio-temporal study in Belgium, 2020–2021

Background

In Belgium, current research on socio-economic inequalities in the coronavirus disease 2019 (COVID-19) crisis has mainly focused on excess mortality and data from the first epidemiological wave. The current study adds onto this by examining the association between COVID-19 incidence and area deprivation during the first five wave and interwave periods, thus adding a temporal gradient to the analyses.

Methods

We use all confirmed COVID-19 cases between March 2020 and June 2021 in Belgium, aggregated at the municipality-level. These data were collected by the national laboratory-based COVID-19 surveillance system. A level of area deprivation was assigned to each Belgian municipality using data of three socio-economic variables: the share of unemployed persons in the active population, the share of households without a car and the share of low-educated persons. The spatio-temporal association between COVID-19 incidence and area deprivation was assessed by performing multivariate negative-binomial regression analyses and computing population attributable fractions.

Results

A significant association between COVID-19 incidence and area deprivation was found over the entire study period, with the incidence in the most deprived areas predicted to be 24% higher than in the least deprived areas. This effect was dependent on the period during the COVID-19 crisis. The largest socio-economic inequalities in COVID-19 infections could be observed during wave 2 and wave 3, with a clear disadvantage for deprived areas.

Conclusion

Our results provide new insights into spatio-temporal patterns of socio-economic inequalities in COVID-19 incidence in Belgium. They reveal the existence of inequalities and a shift of these patterns over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00856-9.

Contribution of Individual- and Neighborhood-Level Social, Demographic, and Health Factors to COVID-19 Hospitalization Outcomes

BACKGROUND

Although disparities in COVID-19 outcomes have been observed, factors contributing to these differences are not well understood.

OBJECTIVE

To determine whether COVID-19 hospitalization outcomes are related to neighborhood-level social vulnerability, independent of patient-level clinical factors.

DESIGN

Pooled cross-sectional study of prospectively collected data.

SETTING

38 Michigan hospitals.

PATIENTS

Adults older than 18 years hospitalized for COVID-19 in a participating site between March and December 2020.

MEASUREMENTS

COVID-19 outcomes included acute organ dysfunction, organ failure, invasive mechanical ventilation, intensive care unit stay, death, and discharge disposition. Social vulnerability was measured by the social vulnerability index (SVI), a composite measure of social disadvantage.

RESULTS

Compared with patients in low-vulnerability ZIP codes, those living in high-vulnerability ZIP codes were more frequently treated in the intensive care unit (29.0% vs. 24.5%); more frequently received mechanical ventilation (19.3% vs. 14.2%); and experienced higher rates of organ dysfunction (51.9% vs. 48.6%), organ failure (54.7% vs. 51.6%), and in-hospital death (19.4% vs. 16.7%). In mixed-effects regression analyses accounting for age, sex, and comorbid conditions, an increase in a patient's neighborhood SVI by 0.25 (1 quartile) was associated with greater likelihood of mechanical ventilation (increase of 2.1 percentage points), acute organ dysfunction (increase of 2.8 percentage points), and acute organ failure (increase of 2.8 percentage points) but was not associated with intensive care unit stay, mortality, or discharge disposition.

LIMITATION

Observational data focused on hospitalizations in a single state.

CONCLUSION

Hospitalized patients with COVID-19 from socially vulnerable neighborhoods presented with greater illness severity and required more intensive treatment, but once hospitalized they did not experience differences in hospital mortality or discharge disposition. Policies that target socially vulnerable neighborhoods and access to COVID-19 care may help ameliorate health disparities.

PRIMARY FUNDING SOURCE

Blue Cross Blue Shield of Michigan (BCBSM) and Blue Care Network as part of the BCBSM Value Partnerships Program, the Michigan Public Health Institute, and the Michigan Department of Health & Human Services.

Therapist disclosure to combat COVID-19 vaccine hesitancy: a narrative review

With the onset of the COVID-19 pandemic in 2019–2020 and the rapid development of vaccines to prevent this disease came a rise in interest around vaccine hesitancy. Naturally, methods of combatting vaccine hesitancy and increasing vaccination rates are of paramount importance. One such method is building upon the trust and openness of one’s relationship with their healthcare provider. Specifically, this paper examines how psychotherapist self-disclosure could facilitate effective health behaviors in patients, focusing on vaccines. Traditionally, mental health therapists have been encouraged to avoid self-disclosure of personal information due to the possibility of unbalancing or damaging the therapeutic relationship. However, research from medicine and other disciplines suggests that personal recommendation, self-disclosure of vaccination status, and expert encouragement may be effective methods of addressing vaccine hesitancy. In addition, recommendations for therapists in discussing vaccination and in working with vaccine-hesitant patients are provided.

Age-specific rate of severe and critical SARS-CoV-2 infections estimated with multi-country seroprevalence studies

BACKGROUND

Knowing the age-specific rates at which individuals infected with SARS-CoV-2 develop severe and critical disease is essential for designing public policy, for infectious disease modeling, and for individual risk evaluation.

METHODS

In this study, we present the first estimates of these rates using multi-country serology studies, and public data on hospital admissions and mortality from early to mid-2020. We combine these under a Bayesian framework that accounts for the high heterogeneity between data sources and their respective uncertainties. We also validate our results using an indirect method based on infection fatality rates and hospital mortality data.

RESULTS

Our results show that the risk of severe and critical disease increases exponentially with age, but much less steeply than the risk of fatal illness. We also show that our results are consistent across several robustness checks.

CONCLUSION

A complete evaluation of the risks of SARS-CoV-2 for health must take non-fatal disease outcomes into account, particularly in young populations where they can be 2 orders of magnitude more frequent than deaths.

Age-specific rate of severe and critical SARS-CoV-2 infections estimated with multi-country seroprevalence studies

BACKGROUND

Knowing the age-specific rates at which individuals infected with SARS-CoV-2 develop severe and critical disease is essential for designing public policy, for infectious disease modeling, and for individual risk evaluation.

METHODS

In this study, we present the first estimates of these rates using multi-country serology studies, and public data on hospital admissions and mortality from early to mid-2020. We combine these under a Bayesian framework that accounts for the high heterogeneity between data sources and their respective uncertainties. We also validate our results using an indirect method based on infection fatality rates and hospital mortality data.

RESULTS

Our results show that the risk of severe and critical disease increases exponentially with age, but much less steeply than the risk of fatal illness. We also show that our results are consistent across several robustness checks.

CONCLUSION

A complete evaluation of the risks of SARS-CoV-2 for health must take non-fatal disease outcomes into account, particularly in young populations where they can be 2 orders of magnitude more frequent than deaths.