Social determinants of mortality from COVID-19: A simulation study using NHANES

Loneliness and Crowded Living Predicted Poor Health in a Sample of Cancer Patients During COVID-19 Pandemic

We investigated the influence of social determinants of health (SDOH), healthcare services, and health behaviors on mental and physical health outcomes of cancer patients between the first winter and the following post-vaccine summer of the COVID-19 pandemic. A three-wave online survey of individuals diagnosed with incident cancer between January 2019 and January 2020 was conducted between November of 2020 and August of 2021 in northeast Ohio. Descriptive analysis and mixed-effect regression analyses were performed. A total of 322 newly diagnosed cancer patients, with 40 African Americans and 282 Whites (215 from metropolitan areas and 67 nonmetropolitan) responded to the survey questions. In Wave 3 ending in August 2021, the survey respondents reported significantly reduced depression (p = .019) on the Hamilton Depression Rating Scale and improved global health (p = .036) on PROMIS. With age, comorbidity, and other demographic and medical variables controlled in the analyses, the feeling of loneliness (p < .001) and crowded living space (p = .001, p = .015) were the two most prominent factors associated with depression, irritability, and poor global health at baseline, with the lowest p values and persistent effect. Self-efficacy of taking preventive measures was associated with reduced depression (p = .001) and improved global health (p = .029). Increasing access to medicine (p < .01) and satisfaction with telehealth appointments (p < .01) were significantly associated with better global health and reduced irritability. Respondents who had private health insurance reported better health than those that had Medicare coverage only (p < .05). This longitudinal, observational study demonstrated the impact of SDOH on health outcomes of cancer patients. Substandard living conditions resulting in loneliness and crowdedness, quality of medical care (e.g., quality telehealth and access to medicine), and personal behaviors (e.g., self-efficacy) were significantly associated with health outcomes in newly diagnosed cancer patients during the pandemic and should be given adequate consideration for the purpose of improving clinical care.

Is there a relationship between internet access and COVID-19 mortality? Evidence from Nigeria based on a spatial analysis

With over 6.5 million deaths due to COVID-19, it has become an issue of global health concern. Early findings have identified several social determinants of deaths from COVID-19. However, very few studies have been done on the relationship between internet access and COVID-19 mortality in the context of developing countries. Using geospatial methods, this study examines the relationship between internet access and COVID-19 mortality disparity in Nigeria. In contrast to the widely reported relationship in the literature that internet access lowers the risk of COVID-19 mortality, the current study finds that geographical locations with the highest internet access are the hotspots of COVID-19 mortality in Nigeria, especially some parts of southwest Nigeria. In addition, findings show that population density and unemployment are risk factors of COVID-19 mortality. The study recommends educating the population on the use of online health information and the need to adhere strictly to non-pharmaceutical and vaccination interventions to reduce the number of deaths caused by the virus.

Sociodemographic, clinical and laboratory characteristics and risk factors for mortality of hospitalized COVID-19 patients at alternate care site: a Latin American experience

BACKGROUND

The establishment of Alternate Care Sites (ACS) helped the most severely impacted countries expand their response capability. The aim of this study was to evaluate the clinical characteristics and risk factors associated with the mortality of hospitalized COVID-19 patients at Alternate Care Site in Mexico City.

PATIENTS AND METHODS

A monocentric cohort study was conducted at Mexico City's Temporary Unit COVID-19 (UTC-19). Sociodemographic, clinical, laboratory and treatment variables were included in the analysis.

RESULTS

A total of 4865 patients were included, with a mean age of 49.33 years ± SD 15.28 years (IQR 38 to 60 years); 50.53% were women. 63.53% of the patients presented at least one comorbidity, the most frequent being: obesity (39.94%), systemic arterial hypertension (25.14%), and diabetes mellitus (21.52%). A total of 4549 patients (93.50%) were discharged due to improvement, 64 patients (1.31%) requested voluntary discharge, 39 patients (0.80%) were referred to another unit, and 213 patients (4.37%) died. Factors that were independently and significantly associated with death included male gender (odds ratio [OR], 1.60), age ≥ 50 years (OR 14.75), null or low schooling (OR 3.47), have at least one comorbidity (OR 3.26), atrial fibrillation (OR 22.14). In the multivariate analysis, the lymphopenia ≤ 1 × 103/μL (OR 1.91), and having required steroid treatment (OR 2.85), supplemental oxygen with high-flow nasal cannula (OR 3.12) or invasive mechanical ventilation (OR 42.52), was significantly associated with an increased risk of death.

CONCLUSIONS

This study identified the clinical characteristics and risk factors for mortality of hospitalized COVID-19 patients at ACS in Mexico City.KEY MESSAGESAn Alternate Care Site (ACS) is any building or structure that is temporarily converted or constructed for healthcare use during a public health emergency.Factors associated with death included male gender, age over 50 years, and lower educational attainment (elementary school or less).The findings corroborate the utility of the CALL score as a predictor of mortality; lymphopenia ≤1 × 103/μL was the most relevant biomarker.

Socioeconomic conditions and children's mental health and quality of life during the COVID-19 pandemic: An intersectional analysis

BACKGROUND

Children and adolescents are highly vulnerable to the impact of sustained stressors during developmentally sensitive times. We investigated how demographic characteristics intersect with socioeconomic dimensions to shape the social patterning of quality of life and mental health in children and adolescents, two years into the COVID-19 pandemic.

METHODS

We used data from the prospective SEROCoV-KIDS cohort study of children and adolescents living in Geneva (Switzerland, 2022). We conducted an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy by nesting participants within 48 social strata defined by intersecting sex, age, immigrant background, parental education and financial hardship in Bayesian multilevel logistic models for poor health-related quality of life (HRQoL, measured with PedsQL) and mental health difficulties (measured with the Strengths and Difficulties Questionnaire).

RESULTS

Among participants aged 2-17 years, 240/2096 (11.5%, 95%CI 10.1-12.9) had poor HRQoL and 105/2135 (4.9%, 95%CI 4.0-5.9) had mental health difficulties. The predicted proportion of poor HRQoL ranged from 3.4% for 6-11 years old Swiss girls with highly educated parents and no financial hardship to 34.6% for 12-17 years old non-Swiss girls with highly educated parents and financial hardship. Intersectional strata involving adolescents and financial hardship showed substantially worse HRQoL than their counterparts. Between-stratum variations in the predicted frequency of mental health difficulties were limited (range 4.4%-6.5%).

CONCLUSIONS

We found considerable differences in adverse outcomes across social strata. Our results suggest that, post-pandemic, interventions to address social inequities in HRQoL should focus on specific intersectional strata involving adolescents and families experiencing financial hardship, while those aiming to improve mental health should target all children and adolescents.

An Analysis of COVID-19 Mortality in Chhattisgarh: A Two-Year Study on Demographics, Trends, and Impacts

Background The COVID-19 pandemic, caused by the novel coronavirus, has had a profound impact on global health, significantly affecting demographics worldwide. As India's twelfth most affected state, Chhattisgarh has experienced substantial COVID-19-related fatalities. This study aims to analyze the temporal, geographical, and demographic distribution and trends in COVID-19 mortality reported by the Department of Health and Family Welfare, Chhattisgarh, spanning from the onset of the pandemic until March 2022 (two years). Methods Data about all COVID-19 deaths recorded between March 2020 and March 2022 were collected from the State Surveillance Unit, Department of Health and Family Welfare, Chhattisgarh, and subsequently compiled in a Microsoft Excel sheet (Microsoft, Redmond, Washinton) for analysis. Results A comprehensive dataset of 14,038 deaths was examined during the study period. Of these, 24.5% (3446), 72.2% (10141), and 3.3% (451) occurred in 2020, 2021, and 2022, respectively. The top five districts in Chhattisgarh with the highest COVID-19 mortality rates were identified as follows: 1) Raipur (23.5%), 2) Durg (13.4%), 3) Bilaspur (8.9%), 4) Raigarh (7.05%), and 5) Janjgir Champa (6.25%). The mean age of the deceased individuals was determined to be 55.44 years, with a standard deviation of 15.14 years. Furthermore, the impact of the pandemic was found to affect males compared to females in Chhattisgarh disproportionately. Conclusion Over the two-year study period, three distinct waves of COVID-19 were observed, with the second wave being the most devastating, particularly for the elderly population. Understanding the demographic characteristics and trends in COVID-19 mortality is crucial for implementing targeted public health measures and interventions to mitigate the impact of future infectious disease outbreaks.

Psychosis and substance abuse increase the COVID-19 mortality risk

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has been a global challenge. High mortality rates have been reported in some risk groups, including patients with pre-existing mental disorders.

METHODS

We used electronic health records to retrospectively identify people infected due to COVID-19 (between March 2020 and March 2021) in the three territories of the Basque Country. COVID-19 cases were defined as individuals who had tested positive on a reverse transcription-polymerase chain reaction (PCR) test. Univariate and multivariate logistic regression models and multilevel analyses with generalized estimated equations were used to determine factors associated with COVID-19-related mortality and hospital admission.

RESULTS

The COVID-19 mortality rate was increased for patients with psychotic disorders [odds ratio (OR) adjusted: 1.45, 95% confidence interval (CI) (1.09-1.94), p = 0.0114] and patients with substance abuse [OR adjusted: 1.88, 95% CI (1.13-3.14, p < 0.0152)]. The mortality rate was lower for patients with affective disorders [OR adjusted: 0.80, 95% CI (0.61-0.99), p = 0.0407]. Hospital admission rates due to COVID-19 were higher in psychosis [OR adjusted: 2.90, 95% CI (2.36-3.56), p < 0.0001] and anxiety disorder groups [OR adjusted: 1.54, 95% CI (1.37-1.72), p < 0.0001]. Among admitted patients, COVID-19 mortality rate was decreased for those with affective disorders rate [OR adjusted: 0.72, 95% CI (0.55-0.95), p = 0.0194].

CONCLUSIONS

COVID-19-related mortality and hospitalizations rates were higher for patients with a pre-existing psychotic disorder.

Associations Between Insurance, Race and Ethnicity, and COVID-19 Hospitalization, Beyond Underlying Health Conditions: A Retrospective Cohort Study

Introduction

: People of lower socioeconomic position (SEP) and people of color (POC) experience higher risks of severe COVID-19, but understanding of these associations beyond the effect of underlying health conditions (UHCs) is limited. Moreover, few studies have focused on young adults, who have had the highest incidence of COVID-19 during much of the pandemic.

Methods

: We conducted a retrospective cohort study using electronic health record data from the University of Washington Medicine healthcare system. Our study population included individuals aged 18-39 years who tested positive for SARS-CoV-2 from February 2020 to March 2021. Using regression modeling, we estimated adjusted risk ratios (aRRs) and differences (aRDs) of COVID-19 hospitalization by SEP (using health insurance as a proxy) and race and ethnicity. We adjusted for any UHC to examine these associations beyond the effect of UHCs. Results: Among 3,101 individuals, the uninsured/publicly insured had a 1.9-fold higher risk of hospitalization (aRR [95% CI]=1.9 [1.0, 3.6]) and 9 additional hospitalizations per 1,000 SARS-CoV-2 positive persons (aRD [95% CI]=9 [-1, 20]) compared to the privately insured. Hispanic or Latine, non-Hispanic (NH) Asian, NH Black, and NH Native Hawaiian or Pacific Islander patients had a 1.5-, 2.7-, 1.4-, and 2.1-fold-higher risk of hospitalization (aRR [95% CI]=1.5 [0.7, 3.1]; 2.7 [1.1, 6.5]; 1.4 [0.6, 3.3]; 2.1 [0.5, 9.1]), respectively, compared to NH White patients. Conclusions: Though they should be interpreted with caution given low precision, our findings suggest the increased risk of COVID-19 hospitalization among young adults of lower SEP and young adults of color may be driven by forces other than UHCs, including social determinants of health.

Academic Health Centers and the Quintuple Aim of Health Care

The Quintuple Aim of health care adds health equity to the existing Quadruple Aim of improving the individual experience of care for patients, improving the health of populations, reducing the per capita cost of care, and improving the experience of health care professionals. Health equity has previously been subsumed within the other 4 aims. Elevating health equity to the status of a distinct aim is necessary to address persistent health inequities that disproportionately affect underrepresented and minoritized groups. Academic health centers (AHCs) bear a unique responsibility to advance health equity due to the societal importance of their 4 missions: patient care, education, research, and community collaboration. Interprofessional education and practice provide natural connection points that enable AHCs to prepare both health professions students and practicing health care professionals to address all 5 aims. AHCs are well positioned to assess health outcomes related to health equity, develop a health care workforce that is representative of their communities, develop innovative research questions regarding health equity, and engage and invest in the communities they serve.

Interactive impacts of walkability, social vulnerability, & travel behavior on COVID-19 mortality: A hierarchical Bayesian spatial random parameter approach

While existing research highlights the built and social environment impacts on COVID-19 mortality, no empirical evidence exists on how the built and social environments may interact to influence COVID-19 mortality. This study presents a rigorous empirical assessment of the interactive impacts of social vulnerability and walkability on neighborhood-level COVID-19 mortality rates. Based in King County, WA, a unique data infrastructure is created by spatially integrating diverse census tract-level data on COVID-19 mortalities, walkability characteristics, social vulnerability, and travel behavior measures. Advanced Markov Chain Monte Carlo (MCMC) based Full Bayes hierarchical spatial random parameter models are developed to simultaneously capture spatial and unobserved random heterogeneity. Around 46% of the neighborhoods had opposite levels of walkability and social vulnerability. Compared to low walkability and high social vulnerability, neighborhoods with high walkability and low social vulnerability (i.e., best case scenario) had on average 20.2% (95% Bayesian CI: -37.2% to -3.3%) lower COVID-19 mortality rates. Analysis of the interactive impacts when only one of the social and built environment metrics was in a healthful direction revealed significant offsetting effects - suggesting that the underlying structural social vulnerability issues faced by our communities should be addressed first for the infectious disease-related health impacts of walkable urban design to be observed. Concerning travel behavior, the findings indicate that COVID-19 mortality rates may be reduced by discouraging auto use and encouraging active transportation. The study methodologically contributes by simultaneously capturing spatial and unobserved heterogeneity in a holistic Full Bayesian framework.

The illusion of personal health decisions for infectious disease management: disease spread in social contact networks

Close contacts between individuals provide opportunities for the transmission of diseases, including COVID-19. While individuals take part in many different types of interactions, including those with classmates, co-workers and household members, it is the conglomeration of all of these interactions that produces the complex social contact network interconnecting individuals across the population. Thus, while an individual might decide their own risk tolerance in response to a threat of infection, the consequences of such decisions are rarely so confined, propagating far beyond any one person. We assess the effect of different population-level risk-tolerance regimes, population structure in the form of age and household-size distributions, and different interaction types on epidemic spread in plausible human contact networks to gain insight into how contact network structure affects pathogen spread through a population. In particular, we find that behavioural changes by vulnerable individuals in isolation are insufficient to reduce those individuals' infection risk and that population structure can have varied and counteracting effects on epidemic outcomes. The relative impact of each interaction type was contingent on assumptions underlying contact network construction, stressing the importance of empirical validation. Taken together, these results promote a nuanced understanding of disease spread on contact networks, with implications for public health strategies.

The COVID-19 pandemic's impact on all-cause mortality disparities in Medicare: By race, income, chronic health, mental/behavioral health, disability

BACKGROUND

The Medicare-enrolled population is heterogeneous across race, ethnicity, age, dual eligibility, and a breadth of chronic health, mental and behavioral health, and disability-related conditions, which may be differentially impacted by the COVID-19 pandemic.

OBJECTIVE

To quantify changes in all-cause mortality prior-to and in the first year of the COVID-19 pandemic across Medicare's different sociodemographic and health-condition subpopulations.

METHODS

This observational, population-based study used stratified bivariate regression to investigate Medicare fee-for-service subpopulation differences in pre-pandemic (i.e., 2019 versus 2016) and pandemic-related (2020 versus 2019) changes in all-cause mortality.

RESULTS

All-cause mortality in the combined Medicare-Advantage (i.e., managed care) and fee-for-service beneficiary population improved by a relative 1% in the ten years that preceded the COVID-19 pandemic, but then escalated by a relative 15.9% in 2020, the pandemic's first year. However, a closer look at Medicare's fee-for-service subpopulations reveals critical differences. All-cause mortality had actually been worsening prior to the pandemic among most psychiatric and disability-related condition groups, all race and ethnicity groups except White Non-Hispanic, and Medicare-Medicaid dual-eligible (i.e., low-income) beneficiaries. Many of these groups then experienced all-cause mortality spikes in 2020 that were over twice that of the overall Medicare fee-for-service population. Of all 61 chronic health conditions studied, beneficiaries with schizophrenia were the most adversely affected, with all-cause mortality increasing 38.4% between 2019 and 2020.

CONCLUSION

This analysis reveals subpopulation differences in all-cause mortality trends, both prior to and in year-one of the COVID-19 pandemic, indicating that the events of 2020 exacerbated preexisting health-related inequities.

Parental and Other Caregiver Loss Due to COVID-19 in the United States: Prevalence by Race, State, Relationship, and Child Age

The more than one million COVID-19 deaths in the United States include parents, grandparents, and other caregivers for children. These losses can disrupt the social, emotional, and economic well-being of children, their families, and their communities, and understanding the number and characteristics of affected children is a critical step in responding. We estimate the number of children who lost a parent or other co-residing caregiver to COVID-19 in the U.S. and identify racial, ethnic, and geographic disparities by aligning COVID-19 death counts through mid-May 2022 with household information from a representative sample of individuals. We estimate that 216,617 children lost a co-residing caregiver to COVID-19; 77,283 lost a parent and more than 17,000 children lost the only caregiver with whom they lived. Non-White children were more than twice as likely as White children to experience caregiver loss, and children under 14 years old experienced 70% of caregiver loss. These losses are a salient threat to the functioning of families and the communities in which COVID-19 deaths are concentrated, compounding additional challenges to physical and mental health and economic stability disproportionately imposed by the pandemic on historically disadvantaged populations. Policymakers and systems should take steps to ensure access to appropriate supports.

Intersecting epidemics: the impact of coronavirus disease 2019 on the HIV prevention and care continua in the United States

OBJECTIVE

To summarize the broad impact of the coronavirus disease 2019 (COVID-19) pandemic on HIV prevention and care in the United States with a focus on the status-neutral HIV care continuum.

DESIGN

We conducted an editorial review of peer-reviewed literature on the topics of HIV-risk behaviors, sexually transmitted illness (STI) and HIV prevalence, HIV prevention and treatment trends, and evolving practices during the COVID-19 pandemic.

METHODS

For relevant literature, we reviewed, summarized, and categorized into themes that span the HIV prevention and care continua, including sexual risk behaviors, mental health, and substance use.

RESULTS

We identified important changes within each component of the HIV care continuum across the United States during the COVID-19 pandemic. Shifts in prevention practices, engagement with care, care provision, medication adherence, testing, and prevalence rates were observed during the pandemic.

CONCLUSION

Although heightened disparities for people at risk for, and living with, HIV were seen during the COVID-19 pandemic, many health systems and clinics have achieved and maintained engagement in HIV prevention and care. This review highlights barriers and innovative solutions that can support durable and accessible health systems through future public health crises.

COVID-19 Vaccination is not a Sufficient Public Policy to face Crisis Management of next Pandemic Threats

This study reveals that a vast vaccination campaign is a necessary but not sufficient public policy to reduce the negative impact of Coronavirus Disease 2019 (COVID-19) pandemic crisis because manifold factors guide the spread of this new infectious disease and related mortality in society. Statistical evidence here, based on a worldwide sample of countries, shows a positive correlation between people fully vaccinated and COVID-19 mortality (r = + 0.65, p-value < 0.01). Multivariate regression, controlling income per capita, confirms this finding. Results suggest that the increasing share of people vaccinated against COVID-19 seems to be a necessary but not sufficient health policy to reduce mortality of COVID-19. The findings here can be explained with the role of Peltzman effect, new variants, environmental and socioeconomic factors that affect the diffusion and negative impact of COVID-19 pandemic in society. This study extends the knowledge in this research field to design effective public policies of crisis management for facing next pandemic threats.

Access, socioeconomic environment, and death from COVID-19 in Nebraska

Our study assesses whether factors related to healthcare access in the first year of the pandemic affect mortality and length of stay (LOS). Our cohort study examined hospitalized patients at Nebraska Medicine between April and October 2020 who were tested for SARS-CoV-2 and had a charted sepsis related diagnostic code. Multivariate logistic was used to analyze the odds of mortality and linear regression was used to calculate the parameter estimates of LOS associated with COVID-19 status, age, gender, race/ethnicity, median household income, admission month, and residential distance from definitive care. Among 475 admissions, the odds of mortality is greater among those with older age (OR: 1.04, 95% CI: 1.02-1.07) and residence in an area with low median household income (OR: 2.11, 95% CI: 0.52-8.57), however, the relationship between mortality and wealth was not statistically significant. Those with non-COVID-19 sepsis had longer LOS (Parameter Estimate: -5.11, adjusted 95% CI: -7.92 to -2.30). Distance from definitive care had trends toward worse outcomes (Parameter Estimate: 0.164, adjusted 95% CI: -1.39 to 1.97). Physical and social aspects of access to care are linked to poorer COVID-19 outcomes. Non-COVID-19 healthcare outcomes may be negatively impacted in the pandemic. Strategies to advance patient-centered outcomes in vulnerable populations should account for varied aspects (socioeconomic, residential setting, rural populations, racial, and ethnic factors). Indirect impacts of the pandemic on non-COVID-19 health outcomes require further study.

[Social determinants associated with self-reporting of symptoms and access to COVID-19 testing and diagnosis in the Plurinational State of BoliviaDeterminantes sociais associados ao autorrelato de sintomas, acesso a testagem e diagnóstico de COVID-19 no Estado Plurinacional da Bolívia]

Objective

To identify the prevalence of self-reporting of symptoms and access to testing and diagnosis of coronavirus-19 disease (COVID-19), as well as its association with social determinants of health (SDH).

Methods

Cross-sectional study with a sample of 11 728 men and 12 612 women over the age of 17, based on the National Household Survey 2020. The dependent variables were the self-reporting of symptoms, access to testing, and a positive COVID-19 test. The independent variables were age, educational level, area of residence and geographic area, ethnicity, type of household, income per capita, occupation, and health insurance. Prevalences, bivariate associations, and binomial logistical regression models (odds ratio (OR), and 95% confidence interval (CI95%) were calculated.

Results

Of the total individuals included, 16% reported symptoms, 10% a test, and 4.2% a positive COVID-19 test. Inequalities were observed in the reporting of COVID-19 symptoms, with a higher probability in women whose income had fallen (OR: 1.7; CI95%: 1.2-2.4) and unemployed persons (OR: 1.2; CI95%: 1.1-1.4 for men and OR: 1.3; CI95%: 1.5-1.5 for women). In contrast, with respect to access to diagnostic tests, the highest probability was observed in people with higher education (OR: 2.4; CI95%: 1.9-2.9 for men and OR: 2.7; CI95%: 2.2-3.4 for women), whose income was maintained (OR: 1.5; CI95%: 1.3-1.9 for men and OR: 1.7; CI95%: 1.4-2.0 for women) and those in the highest quartile of per capita household income (OR: 2.0; CI95%: 1.6-2.5 for men and OR: 1.6; CI95%: 1.3-2.0 for women). The probability of reporting symptoms and getting tested, and being diagnosed with COVID-19 increased with age for people with health insurance and those living in the llanos region; however, it decreased for residents of rural areas.

Conclusions

There are inequalities in access to testing and the reporting of COVID-19 symptoms.

A machine learning algorithm to analyse the effects of vaccination on COVID-19 mortality

The coronavirus disease 2019 (COVID-19), with new variants, continues to be a constant pandemic threat that is generating socio-economic and health issues in manifold countries. The principal goal of this study is to develop a machine learning experiment to assess the effects of vaccination on the fatality rate of the COVID-19 pandemic. Data from 192 countries are analysed to explain the phenomena under study. This new algorithm selected two targets: the number of deaths and the fatality rate. Results suggest that, based on the respective vaccination plan, the turnout in the participation in the vaccination campaign, and the doses administered, countries under study suddenly have a reduction in the fatality rate of COVID-19 precisely at the point where the cut effect is generated in the neural network. This result is significant for the international scientific community. It would demonstrate the effective impact of the vaccination campaign on the fatality rate of COVID-19, whatever the country considered. In fact, once the vaccination has started (for vaccines that require a booster, we refer to at least the first dose), the antibody response of people seems to prevent the probability of death related to COVID-19. In short, at a certain point, the fatality rate collapses with increasing doses administered. All these results here can help decisions of policymakers to prepare optimal strategies, based on effective vaccination plans, to lessen the negative effects of the COVID-19 pandemic crisis in socioeconomic and health systems.

Opioid Use Disorder and COVID-19: Treatment and Recovery Factors among Vulnerable Populations at the Intersection of Two U.S. Epidemics

Social inequities made some sociodemographic groups - including those of older age, minoritized race/ethnicity, and low socioeconomic status - disproportionately vulnerable to morbidity and mortality associated with the opioid epidemic and COVID-19 pandemic. Given shared vulnerability to these public health crises, it is critical to understand how COVID-19 impacts substance use disorder (SUD) treatment and recovery among people with these characteristics. The current study examined COVID-19's perceived impact on treatment factors and psychosocial outcomes by sociodemographic vulnerability. Patients receiving SUD treatment with a history of opioid misuse were recruited. Participants completed self-report questionnaires regarding the impact of COVID-19 on treatment indicators and mood and substance use symptoms. Most participants reported that COVID-19 decreased their treatment access and quality. There were no sociodemographic differences in treatment factors. Those with high sociodemographic vulnerability reported greater pandemic-related increases in depression and demonstrated greater mood symptoms. Post-hoc analyses demonstrated that unmet basic needs were significantly associated with lower treatment access and quality, greater mood symptoms, and higher substance use. Findings suggest pandemic-related stressors and barriers affected those across the sociodemographic spectrum. Treatment systems must address socioeconomic barriers to care exacerbated by the pandemic and bolster integrated treatment options for opioid use and mood disorders.

Disparities in COVID-19 Mortality Rates: Implications for Rural Health Policy and Preparedness

CONTEXT

It is well established that rural communities face geographic and socioeconomic challenges linked to higher rates of health disparities across the United States, though the coronavirus disease 2019 (COVID-19) impact on rural communities is less certain.

OBJECTIVE

To understand the COVID-19 pandemic's impact on rural communities in Tennessee, investigate differences in rural-urban mortality rates after controlling for confounding variables, and inform state pandemic response policy.

DESIGN

A cross-sectional analysis of cumulative COVID-19 morality rates.

SETTING/PARTICIPANTS

Tennessee county-level COVID-19 mortality data from March 1, 2020, to January 31, 2021, were matched with county-level sociodemographic and health data from public datasets: Agency for Healthcare Research and Quality Social Determinants of Health, PLACES: Local Data for Better Health County Data, and the US Census Bureau. County status was defined using the 2013 National Center for Health Statistics Urban-Rural Classification.

MAIN OUTCOME MEASURES

A negative binomial regression model estimated adjusted incidence rate ratio and 95% confidence intervals (CI) for rural compared with urban mortality. Unadjusted rate ratios and rate differences for COVID-19 mortality in rural versus urban counties were compared with those for influenza and pneumonia and all-cause mortality over the past 5 years.

RESULTS

During the study period, 9650 COVID-19 deaths occurred across 42 urban and 53 rural counties. Controlling for county-level sociodemographic characteristics, health care access, and comorbidities, incidence rate ratio was 1.13 (95% CI, 1.00-1.28, P < .05) for rural as compared with urban deaths. Unadjusted COVID-19 mortality risk difference between rural and urban counties was greater (61.85, 95% CI, 54.31-69.31) than 5-year influenza and pneumonia rural-urban risk difference (12.57, 95% CI, 11.16-13.00) during 2015-2019.

CONCLUSIONS

COVID-19 mortality rates were greater for populations living in Tennessee's rural as compared with urban counties during the study period. This differential impact must be considered in public health decision making to mitigate COVID-19.

COVID-19 trends, public restrictions policies and vaccination status by economic ranking of countries: a longitudinal study from 110 countries

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has transitioned to a third phase and many variants have been originated. There has been millions of lives loss as well as billions in economic loss. The morbidity and mortality for COVID-19 varies by country. There were different preventive approaches and public restrictions policies have been applied to control the COVID-19 impacts and usually measured by Stringency Index. This study aimed to explore the COVID-19 trend, public restriction policies and vaccination status with economic ranking of countries.

METHODS

We received open access data from Our World in Data. Data from 210 countries were available. Countries (n = 110) data related to testing, which is a key variable in the present study, were included for the analysis and remaining 100 countries were excluded due to incomplete data. The analysis period was set between January 22, 2020 (when COVID-19 was first officially reported) and December 28, 2021. All analyses were stratified by year and the World Bank income group. To analyze the associations among the major variables, we used a longitudinal fixed-effects model.

RESULTS

Out of the 110 countries included in our analysis, there were 9 (8.18%), 25 (22.72%), 31 (28.18%), and 45 (40.90%) countries from low income countries (LIC), low and middle income countries (LMIC), upper middle income countries (UMIC) and high income countries (HIC) respectively. New case per million was similar in LMIC, UMIC and HIC but lower in LIC. The number of new COVID-19 test were reduced in HIC and LMIC but similar in UMIC and LIC. Stringency Index was negligible in LIC and similar in LMIC, UMIC and HIC. New positivity rate increased in LMIC and UMIC. The daily incidence rate was positively correlated with the daily mortality rate in both 2020 and 2021. In 2020, Stringency Index was positive in LIC and HIC but a negative association in LMIC and in 2021 there was a positive association between UMIC and HIC. Vaccination coverage did not appear to change with mortality in 2021.

CONCLUSION

New COVID-19 cases, tests, vaccinations, positivity rates, and Stringency indices were low in LIC and highest in UMIC. Our findings suggest that the available resources of COVID-19 pandemic would be allocated by need of countries; LIC and UMIC.

Acceptance Rates of COVID-19 Vaccine Highlight the Need for Targeted Public Health Interventions

We aimed to examine rates of COVID-19 vaccination to elucidate the need for targeted public health interventions. We retrospectively reviewed the electronic medical files of all adults registered in a central district in Israel from 1 January 2021 to 31 March 2022. The population was characterized by vaccination status against COVID-19 and the number of doses received. Univariate and multivariable analyses were used to identify predictors of low vaccination rates that required targeted interventions. Of the 246,543 subjects included in the study, 207,911 (84.3%) were vaccinated. The minority groups of ultra-Orthodox Jews and Arabs had lower vaccination rates than the non-ultra-Orthodox Jews (68.7%, 80.5% and 87.7%, respectively, p < 0.001). Adults of low socioeconomic status (SES) had lower vaccination rates compared to those of high SES (74.4% vs. 90.8%, p < 0.001). Adults aged 20−59 years had a lower vaccination rate than those ≥60 years (80.0% vs. 92.1%, p < 0.0001). Multivariate analysis identified five independent variables that were significantly (p < 0.001) associated with low vaccination rates: minority groups of the ultra-Orthodox sector and Arab population, and underlying conditions of asthma, smoking and diabetes mellitus (odds ratios: 0.484, 0.453, 0.843, 0.901 and 0.929, respectively). Specific targeted public health interventions towards these subpopulations with significantly lower rates of vaccination are suggested.

Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia

INTRODUCTION

Worldwide, the 33 recognised megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021.

METHODS

This retrospective cohort included residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data and disease prevalence from Jakarta Health Office surveillance records, and collected subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality.

RESULTS

Of 705 503 cases with a definitive outcome by 31 August 2021, 694 706 (98.5%) recovered and 10 797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93 459) were <18 years and 51.6% were female. The subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95% CI 1.17 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest).

CONCLUSION

In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.

Investigation of Statistical Machine Learning Models for COVID-19 Epidemic Process Simulation: Random Forest, K-Nearest Neighbors, Gradient Boosting

COVID-19 has become the largest pandemic in recent history to sweep the world. This study is devoted to developing and investigating three models of the COVID-19 epidemic process based on statistical machine learning and the evaluation of the results of their forecasting. The models developed are based on Random Forest, K-Nearest Neighbors, and Gradient Boosting methods. The models were studied for the adequacy and accuracy of predictive incidence for 3, 7, 10, 14, 21, and 30 days. The study used data on new cases of COVID-19 in Germany, Japan, South Korea, and Ukraine. These countries are selected because they have different dynamics of the COVID-19 epidemic process, and their governments have applied various control measures to contain the pandemic. The simulation results showed sufficient accuracy for practical use in the K-Nearest Neighbors and Gradient Boosting models. Public health agencies can use the models and their predictions to address various pandemic containment challenges. Such challenges are investigated depending on the duration of the constructed forecast.

A compelling demonstration of why traditional statistical regression models cannot be used to identify risk factors from case data on infectious diseases: a simulation study

BACKGROUND

Regression models are often used to explain the relative risk of infectious diseases among groups. For example, overrepresentation of immigrants among COVID-19 cases has been found in multiple countries. Several studies apply regression models to investigate whether different risk factors can explain this overrepresentation among immigrants without considering dependence between the cases.

METHODS

We study the appropriateness of traditional statistical regression methods for identifying risk factors for infectious diseases, by a simulation study. We model infectious disease spread by a simple, population-structured version of an SIR (susceptible-infected-recovered)-model, which is one of the most famous and well-established models for infectious disease spread. The population is thus divided into different sub-groups. We vary the contact structure between the sub-groups of the population. We analyse the relation between individual-level risk of infection and group-level relative risk. We analyse whether Poisson regression estimators can capture the true, underlying parameters of transmission. We assess both the quantitative and qualitative accuracy of the estimated regression coefficients.

RESULTS

We illustrate that there is no clear relationship between differences in individual characteristics and group-level overrepresentation -small differences on the individual level can result in arbitrarily high overrepresentation. We demonstrate that individual risk of infection cannot be properly defined without simultaneous specification of the infection level of the population. We argue that the estimated regression coefficients are not interpretable and show that it is not possible to adjust for other variables by standard regression methods. Finally, we illustrate that regression models can result in the significance of variables unrelated to infection risk in the constructed simulation example (e.g. ethnicity), particularly when a large proportion of contacts is within the same group.

CONCLUSIONS

Traditional regression models which are valid for modelling risk between groups for non-communicable diseases are not valid for infectious diseases. By applying such methods to identify risk factors of infectious diseases, one risks ending up with wrong conclusions. Output from such analyses should therefore be treated with great caution.

Assessing the Influence of Food Insecurity and Retail Environments as a Proxy for Structural Racism on the COVID-19 Pandemic in an Urban Setting

A collaborative partnership launched the Great Grocer Project (GGP) in March 2021 in Detroit, Michigan where health inequities, including deaths due to COVID-19, have historically been politically determined and informed by socially entrenched norms. Institutional and structural racism has contributed to a lack of diversity in store ownership among Detroit grocers and limited access to high-quality, affordable healthy foods as well as disparate food insecurity among Detroit residents. The GGP seeks to promote Detroit's healthy grocers to improve community health and economic vitality through research, programs, and policies that have the potential to advance health equity. A cross-sectional design was used to explore relationships between scores from the Nutrition Environment Measures Surveys-Stores (NEMS-S) in 62 stores and city-level data of COVID-19 cases and deaths as well as calls to 211 for food assistance. Regression and predictive analyses were conducted at the ZIP code level throughout the city to determine a relationship between the community food environment and food insecurity on COVID-19 cases and deaths. COVID-19 cases and deaths contributed to greater food insecurity. The use of ZIP code data and the small sample size were limitations within this study. Causation could not be determined in this study; therefore, further analyses should explore the potential effects of individual grocery stores on COVID-related outcomes since a cluster of high-scoring NEMS-S stores and calls to 211 for food security resources inferred a potential protective factor. Poor nutrition has been shown to be associated with increased hospitalizations and deaths due to COVID-19. It is important to understand if a limited food environment can also have a negative effect on COVID-19 rates and deaths. Lessons learned from Detroit could have implications for other communities in using food environment improvements to prevent an uptick in food insecurity and deaths due to COVID-19 and other coronaviruses.

COVID-19 pandemic over 2020 (withlockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors

How is the dynamics of Coronavirus Disease 2019 (COVID-19) in 2020 with an health policy of full lockdowns and in 2021 with a vast campaign of vaccinations? The present study confronts this question here by developing a comparative analysis of the effects of COVID-19 pandemic between April-September 2020 (based upon strong control measures) and April-September 2021 (focused on health policy of vaccinations) in Italy, which was one of the first European countries to experience in 2020 high numbers of COVID-19 related infected individuals and deaths and in 2021 Italy has a high share of people fully vaccinated against COVID-19 (>89% of population aged over 12 years in January 2022). Results suggest that over the period under study, the arithmetic mean of confirmed cases, hospitalizations of people and admissions to Intensive Care Units (ICUs) in 2020 and 2021 is significantly equal (p-value<0.01), except fatality rate. Results suggest in December 2021 lower hospitalizations, admissions to ICUs, and fatality rate of COVID-19 than December 2020, though confirmed cases and mortality rates are in 2021 higher than 2020, and likely converging trends in the first quarter of 2022. These findings reveal that COVID-19 pandemic is driven by seasonality and environmental factors that reduce the negative effects in summer period, regardless control measures and/or vaccination campaigns. These findings here can be of benefit to design health policy responses of crisis management considering the growth of COVID-19 pandemic in winter months having reduced temperatures and low solar radiations ( COVID-19 has a behaviour of influenza-like illness). Hence, findings here suggest that strategies of prevention and control of infectious diseases similar to COVID-19 should be set up in summer months and fully implemented during low-solar-irradiation periods (autumn and winter period).

COVID-19 vaccination readiness among multiple racial and ethnic groups in the San Francisco Bay Area: A qualitative analysis

BACKGROUND

COVID-19 vaccination rates are lower among historically marginalized populations, including Black/African American and Latinx populations, threatening to contribute to already high COVID-19 morbidity and mortality disparities for these groups. We conducted a community-based participatory research study using qualitative methods to explore knowledge and beliefs about COVID-19 vaccination among Black/African American, Latinx, and Chinese American residents of the San Francisco Bay Area and assess their views on vaccination outreach and delivery strategies.

METHODS AND FINDINGS

Data were collected from January 14, 2021, to February 24, 2021, with adult residents (N = 109 [Female: N = 76; 70%]) in San Francisco. Focus groups (N = 10) and in-depth interviews (N = 25) were conducted among Black/African Americans (N = 35), Latinx (N = 40), and Chinese Americans (n = 34) in English, Spanish, Cantonese, or Mandarin. Themes were identified using grounded field theory, and included misinformation, mistrust of government and health institutions, and linguistic and other barriers to vaccine access. All three racial/ethnic groups had experiences with vaccine misinformation and information overload. Many African American and Latinx participants cited structural and interpersonal racism, and anti-immigrant discrimination, as factors reducing their trust in government and public health disseminated information and their willingness to be vaccinated. Participants expressed trust in community-based organizations, including faith-based organizations and community-run clinics. Participants often experienced barriers to vaccine access, such as transportation to drive-in sites, with Latinx and Chinese American groups also frequently citing language barriers.

CONCLUSIONS

Vaccine outreach strategies must acknowledge how longstanding systemic, institutional, and structural racism contributes to mistrust in government and health institutions and engage with and support trusted messengers from the community to eliminate cultural, linguistic, and other barriers to vaccine access.

Impact of environmental and individual factors on COVID-19 mortality in children and adolescents in Mexico: An observational study

Background

During the Covid-19 pandemic, children and adolescents faced poverty, potentially dying from preventable causes, or missing out essential vaccines. The aim of this study was to assess potential environmental and individual factors associated to COVID-19 mortality in children and adolescents in Mexico.

Methods

This cross-sectional study analysed the official data of 131,001 children under 10 years of age and adolescents between 10 and 19 years of age with COVID-19 disease, in Mexico. Participants were diagnosticated between March 2020 and June 13, 2021. The environmental variables such as malnutrition, vaccination coverage and social lag index were evaluated at the state level. Multilevel models were fitted to evaluate the association between environmental and individual factors and COVID-19 mortality.

Findings

A total of 773 (0.6%) children and adolescents died due to COVID-19. Younger age (OR = 0.878, 95%CI: 0.869-0.888), diabetes (OR = 3.898, 95%CI: 2.596-5.851), immunosuppression (OR = 5.410, 95%CI: 4.088-7.158), obesity (OR = 1.876, 95%CI: 1.397-2.521), hypertension (OR = 1.906, 95%CI: 1.239-2.932), cardiovascular disease (OR = 2.288, 95%CI: 1.482-3.531), and chronic kidney disease (OR = 13.250, 95%CI: 9.066-19.350) were associated with mortality. COVID-19 mortality was directly associated with social lag index and malnutrition (OR_{very high} = 2.939, 95%CI: 1.111-7.775, and OR = 1.390, 95%CI: 1.073-1.802, respectively), and inversely associated with population density (OR = 0.374, 95%CI: 0.204-0.688). Finally, children and adolescents living in areas with a higher percentage of people with incomplete education (OR = 1.045, 95%CI: 1.011-1.081), of children of school age of 6–14 years who do not attend school (OR = 1.266, 95%CI: 1.032-1.554), and of illiterate population aged 15 and over (OR = 1.086, 95%CI: 0.999-1.179) were associated with a higher risk of COVID-19 mortality.

Interpretation

Malnutrition, social lag index and population density are key factors to understand COVID-19 mortality in children and adolescents. Also, age and pre-existing comorbidities were also associated with worse COVID-19 prognosis.

Funding

No funding was secured for this study.

Modeling Years of Life Lost Due to COVID-19, Socioeconomic Status, and Nonpharmaceutical Interventions: Development of a Prediction Model

Background

Research in the COVID-19 pandemic focused on the health burden, thereby largely neglecting the potential harm to life from welfare losses.

Objective

This paper develops a model that compares the years of life lost (YLL) due to COVID-19 and the potential YLL due to the socioeconomic consequences of its containment.

Methods

It improves on existing estimates by conceptually disentangling YLL due to COVID-19 and socioeconomic status. By reconciling the normative life table approach with socioeconomic differences in life expectancy, it accounts for the fact that people with low socioeconomic status are hit particularly hard by the pandemic. The model also draws on estimates of socioeconomic differences in life expectancy to ascertain potential YLL due to income loss, school closures, and extreme poverty.

Results

Tentative results suggest that if only one-tenth of the current socioeconomic damage becomes permanent in the future, it may carry a higher YLL burden than COVID-19 in the more likely pandemic scenarios. The model further suggests that the socioeconomic harm outweighs the disease burden due to COVID-19 more quickly in poorer and more unequal societies. Most urgently, the substantial increase in extreme poverty needs immediate attention. Avoiding a relatively minor number of 4 million unemployed, 1 million extremely poor, and 2 million students with a higher learning loss may save a similar amount of life years as saving 1 million people from dying from COVID-19.

Conclusions

Primarily, the results illustrate the urgent need for redistributive policy interventions and global solidarity. In addition, the potentially high YLL burden from income and learning losses raises the burden of proof for the efficacy and necessity of school and business closures in the containment of the pandemic, especially where social safety nets are underdeveloped.

Effects of non-pharmaceutical interventions on social distancing during the COVID-19 pandemic: Evidence from the 27 Brazilian states

Background

Despite substantial evidence on the effectiveness of non-pharmaceutical interventions (NPIs), there is still limited evidence on the individual effects of different types of NPIs on social distancing, especially in low- and middle-income countries.

Methods

We used panel data analysis to evaluate the effects of mandatory social distancing rules on social distancing. We obtained data on six different categories of mandatory restrictions implemented in Brazil, by date and state, from state government gazettes (diários oficiais). We then defined a social distancing rules index (SDI) to measure the strictness of social distancing rules, assigning each a value of 2, 1, or 0 depending on whether restrictions were full, partial, or very limited/non-existent at every given time. A separate variable was defined for masking mandates. We tested whether the following variables were associated to social distancing: SDI, masking mandates, COVID-19 incidence, population socioeconomic status, and political orientation. Data is for each day between March 11th and November 10th, 2020 in the 27 Brazilian states (N = 6615).

Findings

Social distancing increased when social distancing rules were stricter, and decreased when the use of face masks became mandatory. The effects of different types of restrictions varied: suspending in-person classes and gatherings, religious/sport/cultural activities had a greater effect than other types of restrictions. Also, the effect of social distancing rules on people’s behaviour decreased over time, especially when rules were stricter.

Interpretation

Mandatory social distancing rules must be adopted to increase social distancing. Stricter rules have a higher impact, but result in decreased compliance over time. Policymakers should prioritize more targeted policies.

Optimal levels of vaccination to reduce COVID-19 infected individuals and deaths: A global analysis

Coronavirus disease 2019 (COVID-19) continues to be a pandemic threat that is generating a constant state of alert in manifold countries. One of the strategies of defense against infectious diseases (e.g., COVID-19) is the vaccinations that decrease the numbers of infected individuals and deaths. In this context, the optimal level of vaccination for COVID-19 is a basic point to control this pandemic crisis in society. The study here,-using data of doses of vaccines administered per 100 inhabitants, confirmed cases and case fatality ratio of COVID-19 between countries (N=192) from March to May 2021,- clarifies the optimal levels of vaccination for reducing the number of infected individuals and, consequently, the numbers of deaths at global level. Findings reveal that the average level of administering about 80 doses of vaccines per 100 inhabitants between countries can sustain a reduction of confirmed cases and number of deaths. In addition, results suggest that an intensive vaccination campaign in the initial phase of pandemic wave leads to a lower optimal level of doses administered per 100 inhabitants (roughly 47 doses of vaccines administered) for reducing infected individuals; however, the growth of pandemic wave (in May, 2021) moves up the optimal level of vaccines to about 90 doses for reducing the numbers of COVID-19 related infected individuals. All these results here could aid policymakers to prepare optimal strategies directed to a rapid COVID-19 vaccination rollout, before the takeoff of pandemic wave, to lessen negative effects of pandemic crisis on environment and socioeconomic systems.

COVID-19 vaccination coverage in deprived populations living in segregated colonies: A nationwide cross-sectional study in Hungary

The segregated colonies (SCs) in Hungary are populated mainly but not exclusively by Roma. Their health care use is restricted in many respects. It has not been studied yet, whether fair COVID-19 vaccination coverage achieved in Hungary is accompanied with fair effectiveness in SCs. Using census data, the vaccination coverage in SCs and the complementary areas (CAs) in the same settlements of the country was determined. To describe the settlement level differences, the vaccination coverage (until June 30, 2021) in SCs were compared to those in CAs by age, sex, and eligibility for exemption certificate standardized measures. Aggregating settlement level data, the level of geographic discrimination in Hungary was also determined. According to nationwide aggregates, crude vaccination coverage was significantly lower in SCs (40.05%, 95% CI 39.87%-40.23%) than in CAs (65.42%, 95% CI 65.37%-65.46%). The relative standardized vaccination coverage was 0.643 (95% CI 0.639-0.647) in SCs. A total of 437 of the 938 investigated settlements showed significant local vaccination disparities. Hungarian citizens living in SCs, mainly of Roma ethnicity, are a distinct high-risk group. Special intervention adapted to SCs is needed to mitigate inequality in vaccination coverage and further consequences of the pandemic.

Is Mandatory Vaccination in Population over 60 Adequate to Control the COVID-19 Pandemic in E.U.?

Vaccine hesitancy, which potentially leads to the refusal or delayed acceptance of COVID-19 vaccines, is considered a key driver of the increasing death toll from the pandemic in the EU. The European Commission and several member states’ governments are either planning or have already directly or indirectly announced mandatory vaccination for individuals aged over 60, the group which has repeatedly proved to be the most vulnerable. In this paper, an assessment of this strategy’s benefits is attempted by deriving a metric for the potential gains of vaccination mandates that can be used to compare EU member states. This is completed by examining the reduction in Standard Expected Years of Life Lost (SEYLL) per person for the EU population over 60 as a function of the member states’ vaccination percentage in these ages. The publicly available data and results of the second iteration of the SHARE COVID-19 survey on the acceptance of COVID-19 vaccines, conducted during the summer of 2021, are used as inputs.

Social Determinants of Disease: HIV and COVID-19 Experiences

PURPOSE OF REVIEW

The differential impact of the COVID-19 and HIV pandemics on marginalized communities has renewed calls for more robust and deeper investigation into structural and social causes of health inequities contributing to these infections, including underlying factors related to systematic racism. Using the Social Determinants of Health (SDOH) framework, we analyzed parallel and divergent factors associated with COVID-19 and HIV/AIDS and the prevalence of disparate disease in diverse communities. We utilized PRISMA guidelines to identify relevant literature (N = 210 articles) that resulted in a review of 125 articles included in our synthesis.

RECENT FINDINGS

With racial health inequities as a core contributor to disease vulnerability, we also identified other factors such as economic stability, social and community support, the neighborhood and built environment, healthcare access and quality, and education access and quality as important socioecological considerations toward achieving health equity. Our review identifies structural and systematic factors that drive HIV and COVID-19 transmission. Our review highlights the importance of not solely focusing on biomedical interventions as solutions to ending HIV and COVID-19, but rather call for building a more just public health and social service safety net that meets the needs of people at the intersection of multiple vulnerabilities.

A Prospective, Longitudinal Evaluation of SARS-CoV-2 COVID-19 Exposure, Use of Protective Equipment and Social Distancing in a Group of Community Physicians

Introduction: Healthcare workers experience a significant risk of exposure to and infection from SARS-CoV-2, COVID-19. Nonetheless, little research has focused on physicians’ use of personal protective equipment (PPE), their concerns about becoming infected and their social distancing maneuvers. Methods: All staff physicians at Advocate Lutheran General Hospital were invited to participate. Their COVID-19 IgG antibody level was measured and an online questionnaire was completed. The questionnaire assessed the risk of COVID-19 exposure, PPE usage, concern for contracting COVID-19, the performance of high-risk procedures, work in high-risk settings, and social distancing practices. Testing was performed in September (T0), and December 2020 (T1) at the height of the global pandemic. Results: A total of 481 (26.7%) of 1800 AGLH physicians were enrolled at T0 and 458 (95% of the original group) at T1. A total of 21 (4.3%) and 39 (8.5%) participants had antibodies at T0 and T1. A total of 63 (13.8%) worked in high-risk settings and 111 (24.2%) performed high-risk procedures. Participants working in high-risk settings had increased exposure to COVID-19 infected patients (OR = 4.464 (CI = 2.522–8.459, p < 0.001). Participants were highly adherent to the use of PPE and social distancing practices including mask-wearing in public (86%, 82.1%), avoiding crowds (85.1%, 85.6%), six feet distancing (83.8%, 83.4%), and avoiding public transportation (78%, 83.8%). A total of 251 (55.4%) participants expressed moderate to extreme concern about becoming infected with COVID-19. Conclusions and Relevance: Among a group of community physicians, consistent PPE use and social distancing practices were common. These practices were associated with a low level of initial acquisition of COVID-19 infections and a relatively low longitudinal risk of infection.

Disparities in Excess Mortality Between Indigenous and Non-Indigenous Brazilians in 2020: Measuring the Effects of the COVID-19 Pandemic

This study aimed to estimate the number of excess deaths among Indigenous Peoples associated with the COVID-19 pandemic in 2020 and to assess the disparities in excess mortality between Indigenous and non-Indigenous Brazilians. A time series analysis of weekly mortality data including all deaths from January 2015 to December 2020 was conducted. The number of expected deaths for 2020 was estimated using an over-dispersed Poisson model that accounts for demographic changes, temporal trends, and seasonal effects in mortality. Weekly excess deaths were calculated as the difference between the number of observed deaths and the expected deaths. Regional differences in Indigenous mortality were investigated. A significant increase in Indigenous mortality was observed from April 1 to December 31, 2020. An estimated 1149 (95% CI 1018-1281) excess deaths was found among Indigenous Brazilians in 2020, representing a 34.8% increase from the expected deaths for this population. The overall increase in non-Indigenous mortality was 18.1%. The Indigenous population living in the Brazilian Amazon area was the earliest-affected Indigenous group, with one of the highest proportional increases in mortality. Disparities in excess mortality revealed a disproportionate burden of COVID-19 among Indigenous Brazilians compared to their non-Indigenous counterparts. Findings highlight the importance of implementing an effective emergency plan that addresses the increased vulnerability of Indigenous Peoples to COVID-19.

County-level socio-economic disparities in COVID-19 mortality in the USA

Background

Preliminary studies have suggested a link between socio-economic characteristics and COVID-19 mortality. Such studies have been carried out on particular geographies within the USA or selective data that do not represent the complete experience for 2020.

Methods

We estimated COVID-19 mortality rates, number of years of life lost to SARS-CoV-2 and reduction in life expectancy during each of the three pandemic waves in 2020 for 3144 US counties grouped into five socio-economic status categories, using daily death data from the Johns Hopkins University of Medicine and weekly mortality age structure from the Centers for Disease Control.

Results

During March–May 2020, COVID-19 mortality was highest in the most socio-economically advantaged quintile of counties and lowest in the two most-disadvantaged quintiles. The pattern reversed during June–August and widened by September–December, such that COVID-19 mortality rates were 2.58 times higher in the bottom than in the top quintile of counties. Differences in the number of years of life lost followed a similar pattern, ultimately resulting in 1.002 (1.000, 1.004) million years in the middle quintile to 1.381 (1.378, 1.384) million years of life lost in the first (most-disadvantaged) quintile during the whole year.

Conclusions

Diverging trajectories of COVID-19 mortality among the poor and affluent counties indicated a progressively higher rate of loss of life among socio-economically disadvantaged communities. Accounting for socio-economic disparities when allocating resources to control the spread of the infection and to reinforce local public health infrastructure would reduce inequities in the mortality burden of the disease.

Do Old Age and Comorbidity via Non-Communicable Diseases Matter for COVID-19 Mortality? A Path Analysis

This paper used Our World data for coronavirus disease-2019 (COVID-19) death count, test data, stringency, and transmission count and prepared a path model for COVID-19 deaths. We augmented the model with age structure-related variables and comorbidity via non-communicable diseases for 117 countries of the world for September 23, 2021, on a cross-section basis. A broad-based global quantitative study incorporating these two prominent channels with regional variation was unavailable in the existing literature. Old age and comorbidity were identified as two prime determinants of COVID-19 mortality. The path model showed that after controlling for these factors, one SD increase in the proportion of persons above 65, above 70, or of median age raised COVID-19 mortality by more than 0.12 SDs for 117 countries. The regional intensity of death is alarmingly high in South America, Europe, and North America compared with Oceania. After controlling for regions, the figure was raised to 0.213, which was even higher. For old age, the incremental coefficient was the highest for South America (0.564), and Europe (0.314), which were substantially higher than in Oceania. The comorbidity channel via non-communicable diseases illustrated that one SD increase in non-communicable disease intensity increased COVID-19 mortality by 0.132 for the whole sample. The regional figure for the non-communicable disease was 0.594 for South America and 0.358 for Europe compared with the benchmark region Oceania. The results were statistically significant at a 10% level of significance or above. This suggested that we should prioritize vaccinations for the elderly and people with comorbidity via non-communicable diseases like heart disease, cancer, chronic respiratory disease, and diabetes. Further attention should be given to South America and Europe, which are the worst affected regions of the world.

Impact and variability of social determinants of health on the transmission and outcomes of COVID-19 across the world: a systematic review protocol

INTRODUCTION

The COVID-19 pandemic has exacerbated health inequalities across the globe, disproportionately affecting those with poor social determinants of health (SDOHs). It is imperative to understand how SDOH influences the transmission and outcomes (positive case, hospitalisation and mortality) of COVID-19. This systematic review will investigate the impact of a wide range of SDOHs across the globe on the transmission and outcomes of COVID-19.

METHODS AND ANALYSIS

This review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. We will search three electronic bibliographical databases (MEDLINE via PubMed, Embase and Scopus), as well as the WHO COVID-19 Global Research on Coronavirus Disease database. We will consider observational studies that report statistical relationships between the SDOHs (as listed in PROGRESS-Plus and Healthy People 2020) and COVID-19 transmission and outcomes. There will be no limitation on the geographical location of publications. The quality of included observational studies will be assessed using a modified version of the Newcastle-Ottawa Scale. A narrative synthesis without meta-analysis reporting standards will be used to report the review findings.

ETHICS AND DISSEMINATION

This review will be based on published studies obtained from publicly available sources, and therefore, ethical approval is not required. We will publish the results of this review in a peer-reviewed journal, as well as present the study findings at a national conference.

PROSPERO REGISTRATION NUMBER

CRD42021228818.

Pandemic Response Requires Research Samples: A U.S. Safety-Net Hospital's Experience and Call for National Action

Biorepositories provide a critical resource for gaining knowledge of emerging infectious diseases and offer a mechanism to rapidly respond to outbreaks; the emergence of the novel coronavirus, SARS-CoV-2, has proved their importance. During the COVID-19 pandemic, the absence of centralized, national biorepository efforts meant that the onus fell on individual institutions to establish sample repositories. As a safety-net hospital, Boston Medical Center (BMC) recognized the importance of creating a COVID-19 biorepository to both support critical science at BMC and ensure representation in research for its urban patient population, most of whom are from underserved communities. This article offers a realistic overview of the authors' experience in establishing this biorepository at the onset of the COVID-19 pandemic during the height of the first surge of cases in Boston, Massachusetts, with the hope that the challenges and solutions described are useful to other institutions. Going forward, funders, policymakers, and infectious disease and public health communities must support biorepository implementation as an essential element of future pandemic preparedness.

Correction: Social determinants of mortality from COVID-19: A simulation study using NHANES

[This corrects the article DOI: 10.1371/journal.pmed.1003490.].

COVID-19 Pandemic: Public Health Risk Assessment and Risk Mitigation Strategies

A newly emerged respiratory viral disease called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is also known as pandemic coronavirus disease (COVID-19). This pandemic has resulted an unprecedented global health crisis and devastating impact on several sectors of human lives and economies. Fortunately, the average case fatality ratio for SARS-CoV-2 is below 2%, much lower than that estimated for MERS (34%) and SARS (11%). However, COVID-19 has a much higher transmissibility rate, as evident from the constant increase in the count of infections worldwide. This article explores the reasons behind how COVID-19 was able to cause a global pandemic crisis. The current outbreak scenario and causes of rapid global spread are examined using recent developments in the literature, epidemiological features relevant to public health awareness, and critical perspective of risk assessment and mitigation strategies. Effective pandemic risk mitigation measures have been established and amended against COVID-19 diseases, but there is still much scope for upgrading execution and coordination among authorities in terms of organizational leadership's commitment and diverse range of safety measures, including administrative control measures, engineering control measures, and personal protective equipment (PPE). The significance of containment interventions against the COVID-19 pandemic is now well established; however, there is a need for its effective execution across the globe, and for the improvement of the performance of risk mitigation practices and suppression of future pandemic crises.

Socioeconomic gradient in COVID-19 vaccination: evidence from Israel

BACKGROUND

Low socioeconomic status (SES) groups have been disproportionately affected by the COVID-19 pandemic. We aimed to examine COVID-19 vaccination rate by neighborhood SES and ethnicity in Israel, a country which has achieved high vaccination rates.

METHODS

Data on vaccinations were obtained from the Israeli Ministry of Health's open COVID-19 database, for December 20, 2020 to August 31, 2021. Correlation between vaccination rate and neighborhood SES was analyzed. Difference in vaccination rate between the first and second vaccine dose was analyzed by neighborhood SES and ethnicity.

FINDINGS

A clear socioeconomic gradient was demonstrated, with higher vaccination rates in the higher SES categories (first dose: r = 0.66; second dose: r = 0.74; third dose: r = 0.92). Vaccination uptake was lower in the lower SES groups and in the Arab population, with the largest difference in uptake between Jewish and Arab localities for people younger than 60, and with the gap widening between first and third doses.

CONCLUSIONS

Low SES groups and the Arab ethnic minority demonstrated disparities in vaccine uptake, which were greater for the second and third, compared with the first vaccine dose. Strategies to address vaccination inequity will need to identify barriers, provide targeted information, and include trust-building in disadvantaged communities.

New insights into the burden of COVID-19 mortality for U.S. Hispanics and Blacks when examined by country/region of origin: An observational study

Background

Florida's diverse population composition includes persons from throughout Latin America and the Caribbean. This facilitated an insightful examination of disparities in 2020 Florida COVID-19 deaths not only among racial/ethnic populations in the aggregate (non-Hispanic White, non-Hispanic Black, Hispanic) but also at the level of country/region of origin.

Methods

Age-adjusted mortality rates (AAMRs) for 2020 Florida COVID-19 deaths were calculated by race, ethnicity, and country/region of origin along with mean age at death, mean number of comorbidities, and percentage of decedents who had not completed secondary education. Regression-derived mortality rate ratios (MRRs) compared death rates for each racial/ethnic/country-of-origin population to non-Hispanic whites.

Findings

The overall AAMR (per 100,000) for 18,342 Florida COVID-19 deaths in 2020 was 55.4, with a much lower AAMR for non-Hispanic Whites (39.3) than for Hispanics (86.8) or Blacks (107.6). Marked differences in AAMRs were observed for specific Black and Hispanic ethnic groups from varied countries/regions of origin. COVID-19 decedents from Mexico and Central America had the highest AAMRs (170.7 and 168.8 per 100,000, respectively), lowest age at death, lowest educational level, and fewest comorbidities. Mean comorbidities were highest for Blacks (all origins) and Cuban Hispanics.

Interpretation

Florida Blacks and Hispanics experienced disproportionately high COVID-19 mortality rates throughout 2020, with notable variability based on country/region of origin. Inequities were particularly pronounced for Hispanic populations from Mexico and Central America. To better understand these heterogeneous COVID-19 mortality trends, more nuanced racial/ethnic analyses and detailed data on social determinants of health are needed.

Funding

Supplemental funding was provided by the Sylvester Comprehensive Cancer Center at University of Miami Miller School of Medicine. Research reported in this publication was also supported by the National Cancer Institute of the National Institutes of Health under Award Number P30CA240139.

Attitudes and Intentions of US Veterans Regarding COVID-19 Vaccination

Importance

Compared with the general population, veterans are at high risk for COVID-19 and have a complex relationship with the government. This potentially affects their attitudes toward receiving COVID-19 vaccines.

Objective

To assess veterans' attitudes toward and intentions to receive COVID-19 vaccines.

Design, Setting, and Participants

This cross-sectional web-based survey study used data from the Department of Veterans Affairs (VA) Survey of Healthcare Experiences of Patients' Veterans Insight Panel, fielded between March 12 and 28, 2021. Of 3420 veterans who were sent a link to complete a 58-item web-based survey, 1178 veterans (34%) completed the survey. Data were analyzed from April 1 to August 25, 2021.

Exposures

Veterans eligible for COVID-19 vaccines.

Main Outcomes and Measures

The outcomes of interest were veterans' experiences with COVID-19, vaccination status and intention groups, reasons for receiving or not receiving a vaccine, self-reported health status, and trusted and preferred sources of information about COVID-19 vaccines. Reasons for not getting vaccinated were classified into categories of vaccine deliberation, dissent, distrust, indifference, skepticism, and policy and processes.

Results

Among 1178 respondents, 974 (83%) were men, 130 (11%) were women, and 141 (12%) were transgender or nonbinary; 58 respondents (5%) were Black, 54 veterans (5%) were Hispanic or Latino, and 987 veterans (84%) were non-Hispanic White. The mean (SD) age of respondents was 66.7 (10.1) years. A total of 817 respondents (71%) self-reported being vaccinated against COVID-19. Of 339 respondents (29%) who were not vaccinated, those unsure of getting vaccinated were more likely to report fair or poor overall health (32 respondents [43%]) and mental health (33 respondents [44%]) than other nonvaccinated groups (overall health: range, 20%-32%; mental health: range, 18%-40%). Top reasons for not being vaccinated were skepticism (120 respondents [36%] were concerned about side effects; 65 respondents [20%] preferred using few medications; 63 respondents [19%] preferred gaining natural immunity), deliberation (74 respondents [22%] preferred to wait because vaccine is new), and distrust (61 respondents [18%] did not trust the health care system). Among respondents who were vaccinated, preventing oneself from getting sick (462 respondents [57%]) and contributing to the end of the COVID-19 pandemic (453 respondents [56%]) were top reasons for getting vaccinated. All veterans reported the VA as 1 of their top trusted sources of information. The proportion of respondents trusting their VA health care practitioner as a source of vaccine information was higher among those unsure about vaccination compared with those who indicated they would definitely not or probably not get vaccinated (18 respondents [26%] vs 15 respondents [15%]). There were no significant associations between vaccine intention groups and age (χ24 = 5.90; P = .21) or gender (χ22 = 3.99; P = .14).

Conclusions and Relevance

These findings provide information needed to develop trusted messages used in conversations between VA health care practitioners and veterans addressing specific vaccine hesitancy reasons, as well as those in worse health. Conversations need to emphasize societal reasons for getting vaccinated and benefits to one's own health.