Socio-economic status and COVID-19-related cases and fatalities

Association of socioeconomic indicators with COVID-19 mortality in Brazil: a population-based ecological study

The article presents an analysis of the spatial distribution of mortality from COVID-19 and its association with socioeconomic indicators in the north-eastern region of Brazil - an area particularly vulnerable with regard to these indicators. This populationbased ecology study was carried out at the municipal level in the years 2020 and 2021, with analyses performed by spatial autocorrelation, multiple linear regression and spatial autoregressive models. The results showed that mortality from COVID-19 in this part of Brazil was higher in the most populous cities with better socioeconomic indicators. Factors such as the onset of the COVID-19 pandemic in large cities, the agglomerations existing within them, the pressure to maintain economic activities and mistakes in the management of the pandemic by the Brazilian federal Government were part of the complex scenario related to the spread of COVID-19 in the country and this study was undertaken in an attempt to understand this situation. Analysing the different scenarios is essential to face the challenges posed by the pandemic to the world's health systems.

Perceptions of the impact of COVID-19 in Tennessee, USA: a retrospective study

Background

Despite high incidence and mortality risks associated with COVID-19 during the pandemic, stay-at-home orders and vaccination recommendations were met with varying levels of acceptance in Tennessee. Understanding perceptions of individuals regarding the health and economic impacts of COVID-19 is necessary to address public concerns while ensuring appropriate public health response. Therefore, the objectives of this study were to (a) investigate differences in opinions among residents of Tennessee regarding the impacts of COVID-19; and (b) identify socioeconomic and demographic predictors/determinants of these opinions.

Methods

This retrospective cross-sectional study was conducted using survey data collected in nine waves during 2020. Distributions of survey-weighted sociodemographic characteristics and respondent perceptions of the impact of COVID-19 were computed. Weighted logistic models were used to investigate predictors of a number of perceptions: whether the health or economic impact was greater, concern for respondent's health, concern for family's health, and willingness to accept COVID-19 vaccine.

Results

The study included a total of 9,754 survey respondents. Approximately equal percentages considered COVID-19 to have a greater economic (48.4%) versus health impact (51.6%). Just 40.1% of the respondents reported that they would definitely accept a COVID-19 vaccine. Age group, race, educational attainment, and household composition were significant (p < 0.05) predictors of all investigated perceptions regarding COVID-19. Lack of prior infection was the strongest predictor of the perception of COVID-19 having a greater impact on health (OR = 2.40, p < 0.001), concern for respondent's health (OR = 1.86, p = 0.002), and concern for family members' health (OR = 1.90, p = 0.001). Compared to males, females had higher odds of identifying the health impact of COVID-19 as greater (OR = 1.09, p = 0.041) and reporting concern for family health (OR = 1.14, p = 0.003). However, they had lower odds (OR = 0.63, p < 0.001) of willingness to accept vaccine than males.

Conclusion

These findings improve our understanding of the drivers of health behaviors, including vaccine hesitancy, and are useful for guiding public health outreach/education programs.

Racial and Regional Disparities Surrounding In-Hospital Mortality among Patients with 2019 Novel Coronavirus Disease (COVID-19): Evidence from NIS Sample in 2020

OBJECTIVE

This study explores differences in COVID-19 in-hospital mortality rates by patient and geographic factors to identify at-risk populations and analyze how strained health disparities were exacerbated during the pandemic.

METHODS

The latest 2020 United States National Inpatient Sample (NIS) data was used to obtain a population-based estimate for patients with COVID-19. We conducted a cross-sectional retrospective data analysis, and sampling weights were used for all statistical analyses to represent nationwide in-hospital mortality of patients with COVID-19. We used multivariate logistic regression models to identify predictors for how patients with COVID-19 are associated with in-hospital death.

RESULTS

Of 200,531 patients, 88.9% did not have an in-hospital death (n=178,369), and 11.1% had in-hospital death (n=22,162). Patients older than 70 were 10 times more likely to have an in-hospital death than patients younger than 40 (p<0.001). Male patients were 37% more likely to have an in-hospital death than female patients (p<0.001). Hispanic patients were 25% more likely to have in-hospital deaths than White patients (p<0.001). In the sub-analysis, Hispanic patients in the 50-60, 60-70, and 70 age groups were 32%, 34%, and 24%, respectively, more likely to have in-hospital death than White patients (p<0.001). Patients with hypertension and diabetes were 69% and 29%, respectively, more likely to have in-hospital death than patients without hypertension and diabetes.

CONCLUSION

Health disparities in the COVID-19 pandemic occurred across races and regions and must be addressed to prevent future deaths. Age and comorbidities like diabetes have a well-established link to increased disease severity, and we have linked both to higher mortality risk. Low-income patients had a significantly increased risk of in-hospital death starting at over 40 years old.

Ecosystem degradation and the spread of Covid-19

The linkages between the emergence of zoonotic diseases and ecosystem degradation have been widely acknowledged by the scientific community and policy makers. In this paper we investigate the relationship between human overexploitation of natural resources, represented by the Human Appropriation of Net Primary Production Index (HANPP) and the spread of Covid-19 cases during the first pandemic wave in 730 regions of 63 countries worldwide. Using a Bayesian estimation technique, we highlight the significant role of HANPP as a driver of Covid-19 diffusion, besides confirming the well-known impact of population size and the effects of other socio-economic variables. We believe that these findings could be relevant for policy makers in their effort towards a more sustainable intensive agriculture and responsible urbanisation.

Relationships between the COVID-19 lockdown, socioeconomic factors and acute coronary syndrome hospitalisations in France

INTRODUCTION

Worldwide, the COVID-19 pandemic has been associated with an overall drop in acute coronary syndrome (ACS) hospitalizations. Additionally, there is a well-known association between ACS and socioeconomic status. This study aims to assess the COVID-19 effect on ACS admissions in France during the first national lockdown and investigate the factors associated with its spatial heterogeneity.

MATERIALS AND METHODS

In this retrospective study, we used the French hospital discharge database (PMSI) to estimate ACS admission rates in all public and private hospitals in 2019 and 2020. A negative binomial regression explored the nationwide change in ACS admissions during lockdown compared with 2019. A multivariate analysis explored the factors associated with the ACS admission incidence rate ratio (IRR, 2020 incidence rate/2019 incidence rate) variation at the county level.

RESULTS

We found a significant but geographically heterogeneous nationwide reduction in ACS admissions during lockdown (IRR 0·70 [0·64-0·76]). After adjustment for cumulative COVID-19 admissions and the ageing index, a higher share of people on short-term working arrangements during lockdown at the county level was associated with a lower IRR, while a higher share of individuals with a high school degree and a higher density of acute care beds were associated with a higher ratio.

CONCLUSIONS

During the first national lockdown, there was an overall decrease in ACS admissions. Local provision of inpatient care and socioeconomic determinants linked to occupation were independently associated with the variation in hospitalizations.

Face mask is an efficient tool to fight the Covid-19 pandemic and some factors increase the probability of its adoption

This study examines the dynamic impact of face mask use on both infected cases and fatalities at a global scale by using a rich set of panel data econometrics. An increase of 100% of the proportion of people declaring wearing a mask (multiply by two) over the studied period lead to a reduction of around 12 and 13.5% of the number of Covid-19 infected cases (per capita) after 7 and 14 days respectively. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. Our results hold when using the rigorous controlling approach. We also document the increasing adoption of mask use over time and the drivers of mask adoption. In addition, population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. However, individualism index is negatively correlated with mask adoption. Finally, strict government policies against Covid-19 have a strong significant effect on mask use.

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

Background and Aims

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

Methods

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

Results

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

Conclusion

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

Financial adversity and subsequent health and wellbeing during the COVID-19 pandemic in the UK: A qualitative interview study

Aims

There are concerns that the economic impacts of the COVID-19 pandemic, including employment inactivity and job loss, will have consequences for the UK population's health and wellbeing. However, there is limited qualitative research into how financial adversity contributes to poor health outcomes in this context. This study aimed to explore forms of financial adversity experienced during the pandemic and their subsequent impacts for health and wellbeing.

Methods

Qualitative semi-structured interviews with 20 people who experienced a form of financial adversity during the pandemic and six service providers employed in social welfare support services. Data were analysed using reflexive thematic analysis.

Results

Two main sources of financial adversity were identified: reductions in household incomes and increased living costs which engendered emotional and physical burdens. Coping strategies included increased financial borrowing, support from informal and formal networks and cutting back on energy use, food and non-essential items.

Conclusion

Our study highlighted exposure to multiple financial adversities because of the pandemic and how these experiences led to poor mental and physical health. The findings underline the importance of measures attending to the immediate needs of individuals, including accessible, co-located financial and psychological services, as well as broader measures that seek to reduce social and economic inequalities.

Cardiac Surgery Outcomes During the COVID-19 Pandemic Worsened Across All Socioeconomic Statuses

BACKGROUND

Increasing socioeconomic distress has been associated with worse cardiac surgery outcomes. The extent to which the pandemic affected cardiac surgical access and outcomes remains unknown. We sought to examine the relationship between the COVID-19 pandemic and outcomes after cardiac surgery by socioeconomic status.

METHODS

All patients undergoing a Society of Thoracic Surgeons (STS) index operation in a regional collaborative, the Virginia Cardiac Services Quality Initiative (2011-2022), were analyzed. Patients were stratified by timing of surgery before vs during the COVID-19 pandemic (March 13, 2020). Hierarchic logistic regression assessed the relationship between the pandemic and operative mortality, major morbidity, and cost, adjusting for the Distressed Communities Index (DCI), STS predicted risk of mortality, intraoperative characteristics, and hospital random effect.

RESULTS

A total of 37,769 patients across 17 centers were included. Of these, 7269 patients (19.7%) underwent surgery during the pandemic. On average, patients during the pandemic were less socioeconomically distressed (DCI 37.4 vs DCI 41.9; P < .001) and had a lower STS predicted risk of mortality (2.16% vs 2.53%, P < .001). After risk adjustment, the pandemic was significantly associated with increased mortality (odds ratio 1.398; 95% CI, 1.179-1.657; P < .001), cost (+$4823, P < .001), and STS failure to rescue (odds ratio 1.37; 95% CI, 1.10-1.70; P = .005). The negative impact of the pandemic on mortality and cost was similar regardless of DCI.

CONCLUSIONS

Across all socioeconomic statuses, the pandemic is associated with higher cost and greater risk-adjusted mortality, perhaps related to a resource-constrained health care system. More patients during the pandemic were from less distressed communities, raising concern for access to care in distressed communities.

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.

Retrospective Analysis of Equity-Based Optimization for COVID-19 Vaccine Allocation

Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counter-factual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American Indian or Alaska Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

Neighborhood Socioeconomic Characteristics Associated with the COVID-19 Incidence in Elementary School Children: An Ecological Study in Osaka City, Japan

We aimed to determine whether neighborhood socioeconomic characteristics are associated with the coronavirus disease 2019 (COVID-19) incidence in elementary school children and, if so, the associated characteristics. We obtained data on the number of infected children from 282 public elementary schools and the socioeconomic characteristics of each school district in Osaka City, Japan. We examined associations between these variables through negative binomial regression analyses. The proportion of employment in the wholesale and retail trade industry and the college graduation rate were significantly positively and negatively associated, respectively, with the total number of COVID-19-infected children. It was discovered that percentages of employment in the accommodation and food service industries in Wave 2, wholesale and retail trade industries after Wave 3, and healthcare and social assistance industries in Wave 5 were significantly positively associated with the number of infected children; likewise, the college graduation rate in Wave 5 was significantly negatively associated with the number of infected children. Our findings provide insight into the relevant and important areas of focus for public health policymakers and practitioners to ensure reduced disparities in COVID-19 infection rates.

The mediating effect of health literacy on COVID-19 vaccine confidence among a diverse sample of urban adults in Boston and Chicago

BACKGROUND

A high rate of COVID-19 vaccination is critical to reduce morbidity and mortality related to infection and to control the COVID-19 pandemic. Understanding the factors that influence vaccine confidence can inform policies and programs aimed at vaccine promotion. We examined the impact of health literacy on COVID-19 vaccine confidence among a diverse sample of adults living in two major metropolitan areas.

METHODS

Questionnaire data from adults participating in an observational study conducted in Boston and Chicago from September 2018 through March 2021 were examined using path analyses to determine whether health literacy mediates the relationship between demographic variables and vaccine confidence, as measured by an adapted Vaccine Confidence Index (aVCI).

RESULTS

Participants (N = 273) were on average 49 years old, 63 % female, 4 % non-Hispanic Asian, 25 % Hispanic, 30 % non-Hispanic white, and 40 % non-Hispanic Black. Using non-Hispanic white and other race as the reference category, Black race and Hispanic ethnicity were associated with lower aVCI (-0.76, 95 % CI -1.00 to -0.50; -0.52, 95 % CI -0.80 to -0.27, total effects from a model excluding other covariates). Lower education was also associated with lower aVCI (using college or more as the reference, -0.73 for 12th grade or less, 95 % CI -0.93 to -0.47; -0.73 for some college/associate's/technical degree, 95 % CI -1.05 to -0.39). Health literacy partially mediated these effects for Black and Hispanic participants and those with lower education (indirect effects -0.19 and -0.19 for Black race and Hispanic ethnicity; 0.27 for 12th grade or less; -0.15 for some college/associate's/technical degree).

CONCLUSIONS

Lower levels of education, Black race, and Hispanic ethnicity were associated with lower scores on health literacy, which in turn were associated with lower vaccine confidence. Our findings suggest that efforts to improve health literacy may improve vaccine confidence, which in turn may improve vaccination rates and vaccine equity.

CLINICAL TRIALS NUMBER

NCT03584490.

Understanding Australian Government Risk Communication Early in the COVID-19 Pandemic: Sociodemographics, Risk Attitudes and Media Consumption

Effective risk communication is essential for government and health authorities to effectively manage public health during the Coronavirus disease (COVID-19) pandemic. Understanding the factors that influence people's perceptions of crisis-related risk messages is critical to identify gaps and inequalities in population risk communication. Using a longitudinal survey of a representative adult sample, we examined risk communication about COVID-19 during April-June 2020 in Australia across sociodemographic groups especially the at-risk groups, accounting for and exploring the effects of risk attitudes and media engagement. Our findings showed that individuals who were younger, more left-wing, more risk-tolerant, and had a current or a history of mental disorders perceived risk communication of the Australian Government to be lower quality. On the other hand, greater consumption of information from televisions was found to be associated with more positive attitudes toward government risk communication. Our results also revealed the importance of effective and high-quality risk communication in gaining the public endorsement of various public health directions. We discuss the implications of results in terms of the development of effective public communications that lead to health-protective behaviors and effectively scaffold public understanding of risk.

Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality

The COVID-19 pandemic has unprecedentedly shaken the public health system worldwide. It has been one of the greatest humanitarian crises faced by all countries, regardless of their economic prosperity. However, some countries have been able to minimize the deaths caused by the coronavirus even in the face of a large number of cases, while others have failed to control the death rate even in a comparatively small number of cases. This study explores possible causes of this disparity using cross-sectional data from 126 countries associated with demography, governance, income level, the extent of ICT maturity and the geographical divide. The results of this study suggest that while government effectiveness is negatively associated with the COVID-19 death rate, the logistics performance of governments is positively linked to the COVID-19 mortality rate. The ICT maturity proxied through online service delivery did not confirm its association with the COVID-19 mortality rate. This study informs that poverty and the location of countries do not necessarily influence COVID-19 deaths. Hence, it behoves governments to focus on improving government effectiveness and putting in place more effective and efficient mobility systems, healthcare supply chains and digital administration to address the global health crisis posed by the COVID-19 pandemic and mitigate its harsh effects, including mortality.

Excess mortality from COVID 19 in Costa Rica: a registry based study using Poisson regression

Background

Official death toll related to COVID-19 has been considerably underestimated in reports from some Latin American countries. This study aimed to analyze the mortality associated with the COVID-19 pandemic in Costa Rica between March 2020 and December 2021.

Methods

A registry based study based on 2017-2021 data from the National Institute of Statistics and Census was designed (N = 128,106). Excess deaths were defined by the WHO as "the difference in the total number of deaths in a crisis compared to those expected under normal conditions"; and were estimated using a Poisson regression, and mortality and years of potential life lost (YPLL) rates were calculated.

Findings

The COVID-19 pandemic represented 15% of the deaths in Costa Rica between March 2020 and December 2021. The mortality rate related to COVID-19 was 83 per 100,000 person-years. Between March and July 2020 (low-incidence period), observed number of deaths was 9%-lower than expected, whereas it was 15% and 24% higher than expected between July 2020 and March 2021 (high incidence period - no vaccination), and between March 2021 and December 2021 (high incidence period - progressive vaccination) respectively. Between July 2020 and December 2021, excess deaths observed and COVID-19 deaths reported were comparable (7461 and 7620 respectively). Nevertheless, there were more deaths than expected for conditions that predispose to COVID-19 deaths. YPLL and mortality rates increased with age, but significant excess deaths were observed in all age-groups older than 30-39 years. No large differences were noted by districts' socioeconomic characteristics although excess death rate was lower in rural compared to urban areas.

Interpretation

Reporting of deaths was only slightly underestimated. In the pre-vaccination period, mortality rate and YPLL rates increased with age, being highest in people aged 60 years or older and justifying the decision to initially prioritize vaccination of older individuals.

Funding

The study was supported by the University of Costa Rica and the Agencia Costarricense de Investigaciones Biomédicas - Fundación Inciensa.

Long COVID in the context of social determinants of health

The COVID-19 pandemic has been a challenge for the public health system and has highlighted health disparities. COVID-19 vaccines have effectively protected against infection and severe disease, but some patients continue to suffer from symptoms after their condition is resolved. These post-acute sequelae, or long COVID, continues to disproportionately affect some patients based on their social determinants of health (SDOH). This paper uses the World Health Organization's (WHO) SDOH conceptual framework to explore how SDOH influences long COVID outcomes.

A study of disparities in access to genetic care pre- and post-pandemic

We aimed to explore the delivery of pediatric genetic care before and during the COVID-19 pandemic and assess if disparities in care existed or emerged. We retrospectively reviewed the electronic medical record for patients 18 years old or younger seen in the Division of Pediatric Genetics between September 2019-March 2020 and April-October 2020. Outcomes included time between referral and new visit, recommendation and completion of genetic testing and/or follow-up visit within 6 months, and telemedicine versus in-person format. Outcomes were compared pre- and post-COVID-19 emergence across ethnicity, race, age, health insurance, socioeconomic status (SES), and use of medical interpretation services. Three hundred thirteen total records were reviewed with comparable demographics between cohorts. Cohort 2 had shorter times between referral and new visit, greater telemedicine utilization, and a greater proportion of testing completed. Younger patients tended to have shorter times between referral and initial visit. In Cohort 1, those with Medicaid insurance or no coverage had longer referral-initial visit times. In Cohort 2, there were differences in testing recommendation based on age. For all outcomes, no disparities were observed across ethnicity, race, SES, or use of medical interpretation services. This study characterizes the impact of the pandemic on pediatric genetics care delivery at our center and may have wider implications.

The links between COVID-19 vaccine acceptance and non-pharmaceutical interventions

The information set from which individuals make their decision on vaccination includes signals from trusted agents, such as governments, community leaders and the media. By implementing restrictions, or by relaxing them, governments can provide a signal about the underlying risk of the pandemic and indirectly affect vaccination take-up. Rather than focusing on measures specifically designed to increase vaccine acceptance, this paper studies how governments' non-pharmaceutical policy responses to the pandemic can modify the degree of preventive health behavior, including vaccination. To do so, we use repeated waves of a global survey on COVID-19 Beliefs, Behaviors and Norms covering 18 countries from October 2020 to March 2021. Controlling for the usual determinants, we explore how individuals' willingness to get vaccinated is affected by changes in government restriction measures (as measured by the Oxford Stringency Index). This relationship is mediated by individual characteristics, social norms (social pressure to conform with what most people do), and trust in government institutions. Our results point to a complex picture as the implementation of restrictions is associated with increased acceptance in some contexts and decreased acceptance in others. The stringency of government restrictions has significant positive correlations with vaccine acceptance in contexts of weak social norms of vaccine acceptance and lower trust in government. In countries or communities with tighter social norms and high trust in health authorities, vaccine acceptance is high but less sensitive to changes in policies. These results suggest that the effect of government policy stringency is stronger among individuals who report lower trust and weaker social norms of vaccine acceptance.

National Documentation and Coding Practices of Noncompliance: The Importance of Social Determinants of Health and the Stigma of African-American Bias

Patient records serve many purposes, one of which includes monitoring the quality of care provided that they can be analyzed through coding and documentation. Z-codes can provide additional information beyond a specific clinical disorder that may still warrant treatment. Social Determinants of Health have specific Z-codes that may help clinicians address social factors that may contribute to patients' health care outcomes. However, there are Z-codes that specify patient noncompliance which has a pejorative connotation that may stigmatize patients and prevent clinicians from examining nonadherence from a social determinant of health perspective. A retrospective cross-sectional study was performed to examine the associations of patient and encounter characteristics with the coding of patient noncompliance. Included in the study were all patients >18 years of age who were admitted to hospitals participating in the Vizient Clinical Data Base (CDB) between January 1, 2019 and December 31, 2019. Almost 9 million US inpatients were included in the study. Of those, 6.3% had a noncompliance Z-code. Use of noncompliance Z-codes was associated with the following odds estimate ratio in decreasing order: the presence of a social determinant of health (odds ratio [OR], 4.817), African American race (OR, 2.010), Medicaid insurance (OR, 1.707), >3 chronic medical conditions (OR, 1.546), living in an economically distressed community (OR, 1.320), male gender (OR, 1.313), nonelective admission status (OR, 1.245), age <65 years (OR, 1.234). More than 1 in 15 patient hospitalizations had a noncompliance code. Factors associated with these codes are difficult, if not impossible, for patients to modify. Disproportionate representation of Africa-Americans among hospitalizations with noncompliance coding is concerning and urgently deserves further exploration to determine the degree to which it may be a product of clinician bias, especially if the term noncompliance prevents health care providers from looking into socioeconomic factors that may contribute to patient nonadherence.

Evaluating the association between in-person work and the risk of SARS-CoV-2 infection through June 2021

OBJECTIVES

Recent studies have evaluated COVID-19 outbreaks and excess mortality by occupation sectors. Studies on SARS-CoV-2 infection across occupation and occupation-related factors remain lacking. In this study, we estimate the effect of in-person work on SARS-CoV-2 infection risk and describe SARS-CoV-2 seroprevalence among working adults.

METHODS

We used Wave 1 data (May to June 2021) from CalScope, a population-based seroprevalence study in California. Occupation data were coded using the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System. Dried blood spot specimens were tested for antibodies to establish evidence of prior infection. We estimated the causal effect of in-person work on SARS-CoV-2 infection risk using the g-formula and describe SARS-CoV-2 seroprevalence across occupation-related factors.

RESULTS

Among 4335 working adults, 53% worked in person. In-person work was associated with increased risk of prior SARS-CoV-2 infection (risk difference: 0.03; [95% CI: 0.02-0.04]) compared with working remotely. Workers that reported job loss or who were without medical insurance had higher evidence of prior infection. Amongst in-person workers, evidence of prior infection was highest within farming, fishing, and forestry (55%; [95% CI: 26%-81%]); installation, maintenance, and repair (23%; [12%-39%]); building and grounds cleaning and maintenance (23%; [13%-36%]); food preparation and serving related (22% [13%-35%]); and healthcare support (22%; [13%-34%]) occupations. Workers who identified as Latino, reported a household income of <$25K, or who were without a bachelor's degree also had higher evidence of prior infection.

CONCLUSIONS

SARS-CoV-2 infection risk varies by occupation. Future vaccination strategies may consider prioritizing in-person workers.

Assessment of a COVID-19 vaccination protocol for unhoused patients in the emergency department

BACKGROUND

We aimed to evaluate the feasibility of implementing an emergency department (ED)-based Coronavirus Disease of 2019 (COVID-19) vaccination protocol in a population of unhoused patients.

METHODS

On June 10, 2021, a best practice alert (BPA) was implemented that fired when an ED provider opened the charts of unhoused patients and prompted the provider to order COVID-19 vaccination for eligible patients. We downloaded electronic medical record data of patients who received a COVID-19 vaccine in the ED between June 10, 2021 and August 26, 2021. The outcomes of interest were the number of unhoused, and the total number of patients vaccinated for COVID-19 during the study period. Data were described with simple descriptive statistics.

RESULTS

There were 25,871 patient encounters in 19,992 unique patients (mean 1.3 visits/patient) in the emergency department during the study period. There were 1,474 (6% of total ED population) visits in 1,085 unique patients who were unhoused (mean 1.4 visits/patient). The BPA fired in 1,046 unhoused patient encounters (71% of PEH encounters) and was accepted in 79 (8%). Forty-three unhoused patients were vaccinated as a result of the BPA (4% of BPA fires) and 18 unhoused patients were vaccinated without BPA prompting. An additional 76 domiciled patients were vaccinated in the ED.

CONCLUSIONS

Implementing an ED-based COVID-19 vaccination program is feasible, however, only a small number of patients underwent COVID-19 vaccination. Further studies are needed to explore the utility of using the ED as a setting for COVID-19 vaccination.

Along party Lines: Examining the gubernatorial party difference in COVID-19 mortality rates in U.S. Counties

Drawing upon the literatures on risk factors for COVID-19 and the roles of political party and political partisanship in COVID-19 policies and outcomes, this study quantifies the extent to which differences in Republican- and Democrat-governed counties' observable characteristics explain the Republican - Democrat gap in COVID-19 mortality rate in the United States. We analyze the county COVID-19 mortality rate between February 1 and December 31, 2020 and employ the Blinder-Oaxaca decomposition method. We estimate the extent to which differences in county characteristics - demographic, socioeconomic, employment, health status, healthcare access, area geography, and Republican vote share, explain the difference in COVID-19 mortality rates in counties governed by Republican vs Democrat governors. Among 3,114 counties, Republican-governed counties had significantly higher COVID-19 mortality than did Democrat-governed counties (127 ± 86 vs 97 ± 80 per 100,000 population, p < 0.001). Results are sensitive to which weights are used: of the total gap of 30.3 deaths per 100,000 population, 12.8 to 20.5 deaths, or 42.2-67.7 %, are explained by differences in observable characteristics of Republican- and Democratic-governed counties. Difference in support for President Trump between Republican- and Democrat-governed counties explains 25 % of the additional deaths in Republican counties. Policies aimed at improving population health and lowering racial disparity in COVID-19 outcomes may also be correlated with reducing the partisan gap in COVID-19 mortality.

Geography, rurality, and community distress: deaths due to suicide, alcohol-use, and drug-use among Colorado Veterans

BACKGROUND

In the USA, deaths due to suicide, alcohol, or drug-related causes (e.g., alcohol-related liver disease, overdose) have doubled since 2002. Veterans appear disproportionately impacted by growing trends. Limited research has been conducted regarding the relationship between community-level factors (e.g., rurality, community distress resulting from economic conditions) and the presence of spatial clustering of suicide, alcohol-related, or drug-related deaths. We explored community-level relationships in Colorado Veterans and compared suicide, alcohol-, and drug-related death rates between the Colorado adult population and Veterans.

METHODS

2009-2020 suicide, alcohol-related, and/or drug-related deaths were identified using qualifying multiple cause-of-death International Classification of Disease (ICD)-10 codes in CDC WONDER for the general adult population and Colorado death data for Veteran populations. Age and race adjusted rates were calculated to compare risk overall and by mortality type (i.e., suicide, alcohol-related, drug-related). In Veteran decedents, age-adjusted rates were stratified by rurality and community distress, measured by the Distressed Communities Index. Standardized mortality ratios were calculated to measure spatial autocorrelation and identify clusters using global and local Moran's I, respectively.

RESULTS

6.4% of Colorado Veteran deaths (n = 6948) were identified as being related to suicide, alcohol, or drugs. Compared to rates in the general population of Colorado adults, Veterans had 1.8 times higher rates of such deaths overall (2.1 times higher for suicide, 1.8 times higher for alcohol-related, 1.3 times higher for drug-related). Among Veterans, community distress was associated with an increased risk of alcohol-related [age-adjusted rate per 100,000 (95% CI) = 129.6 (89.9-193.1)] and drug-related deaths [95.0 (48.6-172.0)]. This same significant association was not identified among those that died by suicide. Rurality was not associated with risk for any of the deaths of interest. There was significant spatial clustering for alcohol-related deaths in southeast Colorado.

CONCLUSIONS

Colorado Veterans have higher rates of deaths due to suicide, alcohol-related, and drug-related causes compared to members of the general adult population. Upstream prevention efforts, such as community-based interventions targeting alcohol-use and community economic distress, are warranted. More research is also needed to understand how community distress and other social determinants of health impact the community burden of suicide, alcohol-related, and drug-related mortality.

Understanding Drivers of Vaccine Hesitancy During the COVID-19 Pandemic Among Older Adults in Jiangsu Province, China: Cross-sectional Survey

BACKGROUND

Older adults are particularly at risk from infectious diseases, including serve complications, hospitalization, and death.

OBJECTIVE

This study aimed to explore the drivers of vaccine hesitancy among older adults based on the "3Cs" (confidence, complacency, and convenience) framework, where socioeconomic status and vaccination history played the role of moderators.

METHODS

A cross-sectional questionnaire survey was conducted in Jiangsu Province, China, between June 1 and July 20, 2021. Older adults (aged ≥60 years) were recruited using a stratified sampling method. Vaccine hesitancy was influenced by the 3Cs in the model. Socioeconomic status and vaccination history processed through the item parceling method were used to moderate associations between the 3Cs and hesitancy. Hierarchical regression analyses and structural equation modeling were used to test the validity of the new framework. We performed 5000 trials of bootstrapping to calculate the 95% CI of the pathway's coefficients.

RESULTS

A total of 1341 older adults participated. The mean age was 71.3 (SD 5.4) years, and 44.7% (599/1341) of participants were men. Confidence (b=0.967; 95% CI 0.759-1.201; P=.002), convenience (b=0.458; 95% CI 0.333-0.590; P=.002), and less complacency (b=0.301; 95% CI 0.187-0.408; P=.002) were positively associated with less vaccine hesitancy. Socioeconomic status weakened the positive effect of low complacency (b=-0.065; P=.03) on low vaccine hesitancy. COVID-19 vaccination history negatively moderated the positive association between confidence (b=-0.071; P=.02) and lower vaccine hesitancy.

CONCLUSIONS

Our study identified that confidence was the more influential dimension in reducing vaccine hesitancy among older adults. COVID-19 vaccination history, as well as confidence, had a positive association with less vaccine hesitancy and could weaken the role of confidence in vaccine hesitancy. Socioeconomic status had a substitution relationship with less complacency, which suggested a competitive positive association between them on less vaccine hesitancy.

Political Economy of the COVID-19 Pandemic: How State Policies Shape County-Level Disparities in COVID-19 Deaths

The authors examine how two state-level coronavirus disease 2019 (COVID-19) policy indices (one capturing economic support and one capturing stringency measures such as stay-at-home orders) were associated with county-level COVID-19 mortality from April through December 2020 and whether the policies were more beneficial for certain counties. Using multilevel negative binominal regression models, the authors found that high scores on both policy indices were associated with lower county-level COVID-19 mortality. However, the policies appeared to be most beneficial for counties with fewer physicians and larger shares of older adults, low-educated residents, and Trump voters. They appeared to be less effective in counties with larger shares of non-Hispanic Black and Hispanic residents. These findings underscore the importance of examining how state and local factors jointly shape COVID-19 mortality and indicate that the unequal benefits of pandemic policies may have contributed to county-level disparities in COVID-19 mortality.

The long-term dynamic relationship between communicable disease spread, economic prosperity, greenhouse gas emissions, and government health expenditures: preparing for COVID-19-like pandemics

The spread of communicable diseases, such as COVID-19, has a detrimental effect on our socio-economic structure. In a dynamic log-run world, socio-economic and environmental factors interact to spread communicable diseases. We investigated the long-term interdependence of communicable disease spread, economic prosperity, greenhouse gas emissions, and government health expenditures in India's densely populated economy using a variance error correction (VEC) approach. The VEC model was validated using stationarity, cointegration, autocorrelation, heteroscedasticity, and normality tests. Our impulse response and variance decomposition analyses revealed that economic prosperity (GNI) significantly impacts the spread of communicable diseases, greenhouse gas emissions, government health expenditures, and GNI. Current health expenditures can reduce the need for future increases, and the spread of communicable diseases is detrimental to economic growth. Developing economies should prioritize economic growth and health spending to combat pandemics. Simultaneously, the adverse effects of economic prosperity on environmental degradation should be mitigated through policy incentives.

The Influence of the COVID-19 Pandemic on Social Anxiety: A Systematic Review

The COVID-19 pandemic has resulted in negative mental health outcomes throughout the world, and its impact on social interactions and relationships is likely to be evident in problematic social anxiety. This systematic review qualitatively synthesized data from studies that have reported on the effects of the pandemic on social anxiety. A systematic search of Web of Science Core Collection, Embase, PsychINFO, Scopus, EBSCOhost, Cochrane Central Register of Controlled Trials, and Proquest Central-Dissertations and Theses was conducted, with thirty-three studies meeting the inclusion criteria. The results suggest that social anxiety has been heightened in the general population due to the pandemic, with women and low-income earners being especially vulnerable. Other contributing factors include impaired coping strategies, lower socio-emotional well-being, limited support networks, and contraction of the SARS-CoV-2 virus. Individuals with a Social Anxiety Disorder diagnosis may be at risk of a deterioration of mental health in general. Limitations of the literature reviewed include the predominance of cross-sectional study designs, which limit causal inferences are limited. Additionally, associations may be inflated as many studies have not accounted for mediating variables. Taken together, the research suggests that social anxiety, either pre-pandemic or arising due to the pandemic environment, has contributed to a variety of negative mental health outcomes related to social anxiety.

SARS-CoV-2 epidemiology, antibody dynamics, and neutralisation capacity in Irish healthcare workers in the era of booster COVID-19 vaccinations

Background

The PRECISE Study, a multi-phase cross-sectional seroprevalence study of anti-SARS-CoV-2 antibodies in Irish healthcare workers (HCW) investigated: (1) risk factors for SARS-CoV-2 seropositivity, (2) the durability of antibody responses in a highly vaccinated HCW cohort, and (3) the neutralisation capacity of detected antibodies, prior to booster COVID-19 vaccination.

Materials and methods

Serology samples were collected across two hospital sites in November 2021 and analysed using the Roche Elecsys Anti-SARS-CoV-2/Elecsys-S Anti-SARS-CoV-2 assays to detect anti-nucleocapsid (N) and anti-spike (S) antibodies respectively. Paired serology results from prior study phases were used to analyse changes in individual HCW serostatus over time. Risk-factors for SARS-CoV-2 infection were assessed for demographic and work-related factors. Antibody neutralisation capacity was assessed in a subset of samples via an in vitro ACE2 binding enzyme-linked immunosorbent assay.

Results

2,344 HCW samples were analysed. Median age was 43 years (IQR 33-50) with 80.5% (n = 1,886) female participants. Irish (78.9%, n = 1,850) and Asian (12.3%, n = 288) were the most commonly reported ethnicities. Nursing/midwifery (39.3%, n = 922) was the most common job role. 97.7% of participants were fully vaccinated, with Pfizer (81.1%, n = 1,902) and AstraZeneca (16.1%, n = 377) the most common vaccines received. Seroprevalence for anti-SARS-CoV-2 antibodies indicating prior infection was 23.4%, of these 33.6% represented previously undiagnosed infections. All vaccinated participants demonstrated positive anti-S antibodies and in those with paired serology, no individual demonstrated loss of previously positive anti-S status below assay threshold for positivity. Interval loss of anti-N antibody positivity was demonstrated in 8.8% of previously positive participants with paired results. Risk factors for SARS-CoV-2 seropositivity suggestive of previous infection included age 18-29 years (aRR 1.50, 95% CI 1.19-1.90, p < 0.001), India as country of birth (aRR 1.35, 95% CI 1.01-1.73, p = 0.036), lower education level (aRR 1.35, 95% CI 1.11-1.66, p = 0.004) and HCA job role (aRR 2.12, 95% CI 1.51-2.95, p < 0.001). Antibody neutralisation varied significantly by anti-SARS-CoV-2 antibody status, with highest levels noted in those anti-N positive, in particular those with vaccination plus previous SARS-CoV-2 infection.

Conclusion

All vaccinated HCWs maintained anti-S positivity prior to COVID-19 booster vaccination, however anti-N positivity was more dynamic over time. Antibody neutralisation capacity was highest in participants with COVID-19 vaccination plus prior SARS-CoV-2 infection.

Geographical variations and district-level factors associated with COVID-19 mortality in Indonesia: a nationwide ecological study

BACKGROUND

Ensuring health equity, especially for vulnerable populations in less developed settings with poor health system is essential for the current and future global health threats. This study examined geographical variations of COVID-19 mortality and its association with population health characteristics, health care capacity in responding pandemic, and socio-economic characteristics across 514 districts in Indonesia.

METHODS

This nationwide ecological study included aggregated data of COVID-19 cases and deaths from all 514 districts in Indonesia, recorded in the National COVID-19 Task Force database, during the first two years of the epidemic, from 1 March 2020 to 27 February 2022. The dependent variable was district-level COVID-19 mortality rate per 100,000 populations. The independent variables include district-level COVID-19 incidence rate, population health, health care capacity, and socio-demographics data from government official sources. We used multivariable ordinal logistic regression to examine factors associated with higher mortality rate.

RESULTS

Of total 5,539,333 reported COVID-19 cases, 148,034 (2.7%) died, and 5,391,299 (97.4%) were recovered. The district-level mortality rate ranged from 0 to 284 deaths per 100,000 populations. The top five districts with the highest mortality rate were Balikpapan (284 deaths per 100,000 populations), Semarang (263), Madiun (254), Magelang (250), and Yogyakarta (247). A higher COVID-19 incidence (coefficient 1.64, 95% CI 1.22 to 1.75), a higher proportion of ≥ 60 years old population (coefficient 0.26, 95% CI 0.06 to 0.46), a higher prevalence of diabetes mellitus (coefficient 0.60, 95% CI 0.37 to 0.84), a lower prevalence of obesity (coefficient -0.32, 95% CI -0.56 to -0.08), a lower number of nurses per population (coefficient -0.27, 95% CI -0.50 to -0.04), a higher number of midwives per population (coefficient 0.32, 95% CI 0.13 to 0.50), and a higher expenditure (coefficient 0.34, 95% CI 0.10 to 0.57) was associated with a higher COVID-19 mortality rate.

CONCLUSION

COVID-19 mortality rate in Indonesia was highly heterogeneous and associated with higher COVID-19 incidence, different prevalence of pre-existing comorbidity, healthcare capacity in responding the pandemic, and socio-economic characteristics. This study revealed the need of controlling both COVID-19 and those known comorbidities, health capacity strengthening, and better resource allocation to ensure optimal health outcomes for vulnerable population.

Resilience level and its association with maladaptive coping behaviours in the COVID-19 pandemic: a global survey of the general populations

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has induced a significant global concern on mental health. However few studies have measured the ability of individuals to "withstand setbacks, adapt positively, and bounce back from adversity" on a global scale. We aimed to examine the level of resilience, its determinants, and its association with maladaptive coping behaviours during the pandemic.

METHODS

The Association of Pacific Rim Universities (APRU) conducted a global survey involving 26 countries by online, self-administered questionnaire (October 2020-December 2021). It was piloted-tested and validated by an expert panel of epidemiologists and primary care professionals. We collected data on socio-demographics, socioeconomic status, clinical information, lifestyle habits, and resilience levels measured by the Brief Resilience Scale (BRS) among adults aged ≥ 18 years. We examined factors associated with low resilience level, and evaluated whether low resilience was correlated with engagement of maladaptive coping behaviours.

RESULTS

From 1,762 surveys, the prevalence of low resilience level (BRS score 1.00-2.99) was 36.4% (America/Europe) and 24.1% (Asia Pacific). Young age (18-29 years; adjusted odds ratio [aOR] = 0.31-0.58 in older age groups), female gender (aOR = 1.72, 95% C.I. = 1.34-2.20), poorer financial situation in the past 6 months (aOR = 2.32, 95% C.I. = 1.62-3.34), the presence of one (aOR = 1.56, 95% C.I. = 1.19-2.04) and more than two (aOR = 2.32, 95% C.I. = 1.59-3.39) medical conditions were associated with low resilience level. Individuals with low resilience were significantly more likely to consume substantially more alcohol than usual (aOR = 3.84, 95% C.I. = 1.62-9.08), take considerably more drugs (aOR = 12.1, 95% C.I. = 2.72-54.3), buy supplements believed to be good for treating COVID-19 (aOR = 3.34, 95% C.I. = 1.56-7.16), exercise less than before the pandemic (aOR = 1.76, 95% C.I. = 1.09-2.85), consume more unhealthy food than before the pandemic (aOR = 2.84, 95% C.I. = 1.72-4.67), self-isolate to stay away from others to avoid infection (aOR = 1.83, 95% C.I. = 1.09-3.08), have an excessive urge to disinfect hands for avoidance of disease (aOR = 3.08, 95% C.I. = 1.90-4.99) and transmission (aOR = 2.54, 95% C.I. = 1.57-4.10).

CONCLUSIONS

We found an association between low resilience and maladaptive coping behaviours in the COVID-19 pandemic. The risk factors identified for low resilience in this study were also conditions known to be related to globalization-related economic and social inequalities. Our findings could inform design of population-based, resilience-enhancing intervention programmes.

Self-Isolation and Testing Behaviour During the COVID-19 Pandemic: An Agent-Based Model

Since the beginning of the COVID-19 pandemic, various models of virus spread have been proposed. While most of these models focused on the replication of the interaction processes through which the virus is passed on from infected agents to susceptible ones, less effort has been devoted to the process through which agents modify their behaviour as they adapt to the risks posed by the pandemic. Understanding the way agents respond to COVID-19 spread is important, as this behavioural response affects the dynamics of virus spread by modifying interaction patterns. In this article, we present an agent-based model that includes a behavioural module determining agent testing and isolation propensity in order to understand the role of various behavioural parameters in the spread of COVID-19.

The effect of the COVID-19 pandemic on infant development and maternal mental health in the first 2 years of life

We investigated how exogenous variation in exposure to the COVID-19 pandemic during the first year of life is related to infant development, maternal mental health, and perceived stress. Ninety-three socioeconomically diverse pregnant women were recruited before the pandemic to participate in a longitudinal study. Infants ranged in age at the beginning of lockdown (0-9.5 months old), thus experiencing different durations of pandemic exposure across the first year of life. The duration of pandemic exposure was not associated with family demographic characteristics, suggesting it captured exogenous variability. We tested associations between this exogenous variation in pandemic exposure and child and family outcomes. We also examined whether mother-reported disruptive life events were correlated with child and family outcomes. We found no association between duration of pandemic exposure in the first year of life and infant socioemotional problems, infant language development, or maternal mental health and perceived stress symptoms, at 12 or 24 months. However, we found that self-reported exposure to pandemic-related disruptive life events predicted greater maternal depression, anxiety, and perceived stress at 12 months, and greater depression and anxiety at 24 months. Socioeconomic status did not moderate these associations. These findings suggest cautious optimism for infants raised during this period.

Educational inequalities in self-rated health and emotional exhaustion among workers during the COVID-19 pandemic: a longitudinal study

OBJECTIVE

This study aimed to investigate trends in educational inequalities in poor health and emotional exhaustion during the pandemic among workers, and differences in trends between men and women.

METHODS

Five waves (2019-2021) from the longitudinal study 'the Netherlands Working Conditions Survey COVID-19 study' were used (response rates: 32-38%). Generalized logistic mixed models were used to estimate the changes in absolute and relative educational inequalities in poor health and emotional exhaustion for all workers (n = 12,479) and for men and women, separately.

RESULTS

Low and intermediate educated workers reported more often poor health (OR 2.54; 95% CI 1.71-3.77 and OR 2.09; 95% CI 1.68-2.61, respectively) than high educated workers. Intermediate educated women (OR 0.49; 95% CI 0.37-0.64) reported less emotional exhaustion than high educated women, but no differences were observed among men. The prevalence of poor health first decreased across all educational levels until March 2021, and bounced back in November 2021. A similar pattern was found for emotional exhaustion, but for low and intermediate educated workers only. Relative educational inequalities in poor health reduced among men during the pandemic, and absolute differences decreased among men and women by 2.4-2.6%. Relative educational inequalities in emotional exhaustion widened among men only. Absolute differences in emotional exhaustion first increased among both men and women, but narrowed between the last two waves.

DISCUSSION

Socioeconomic inequalities for poor self-rated health remained but narrowed in relative and absolute terms during the pandemic. With regard to emotional exhaustion, socioeconomic inequalities returned to pre-COVID-19 levels at the end of 2021.

COVID-19 Risk Perception and Prevention Practices among High- and Low-Density Populations in Bangladesh: A Mixed-Methods Study

We aimed to explore coronavirus disease 2019 (COVID-19) risk perception and prevention practices among people living in high- and low-population density areas in Dhaka, Bangladesh. A total of 623 patients with confirmed COVID-19 agreed to participate in the survey. Additionally, we purposively selected 14 participants from diverse economic and occupational groups and conducted qualitative interviews for them accordingly. Approximately 70% of the respondents had low socioeconomic status. Among the 623 respondents, 146 were from low-density areas, and 477 were from high-density areas. The findings showed that study participants perceived COVID-19 as a punishment from the Almighty, especially for non-Muslims, and were not concerned about its severity. They also believed that coronavirus would not survive in hot temperatures or negatively impact Bangladeshis. This study revealed that people were reluctant to undergo COVID-19 testing. Family members hid if anyone tested positive for COVID-19 or did not adhere to institutional isolation. The findings showed that participants were not concerned about COVID-19 and believed that coronavirus would not have a devastating impact on Bangladeshis; thus, they were reluctant to follow prevention measures and undergo testing. Tailored interventions for specific targeted groups would be relevant in mitigating the prevailing misconceptions.

Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020-2022

BACKGROUND

It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death.

METHODS

We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated.

RESULTS

The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients < 70 years old. With the Omicron variant, the CFR among the 80s and older in Tokyo and Osaka was 3.2% (95% CI 3.0 to 3.5) and 2.9% (95% CI 2.7 to 3.1), respectively.

CONCLUSION

We found that without substantial control, the CFR can increase when a surge in cases occurs with an identifiable elevation in risk-especially among older people. Because active treatment options including admission to ICU cannot be offered to the elderly with an overwhelmed medical service, the CFR value can potentially double compared with that in other areas of health care under less pressure.

Using the social vulnerability index to assess COVID-19 vaccine uptake in Louisiana

Using data from the Louisiana Department of Public Health, we explored the spatial relationships between the Social Vulnerability Index (SVI) and COVID-19-related vaccination and mortality rates. Publicly available COVID-19 vaccination and mortality data accrued from December 2020 to October 2021 was downloaded from the Louisiana Department of Health website and merged with the SVI data; geospatial analysis was then performed to identify the spatial association between the SVI and vaccine uptake and mortality rate. Bivariate Moran's I analysis revealed significant clustering of high SVI ranking with low COVID-19 vaccination rates (1.00, p < 0.001) and high smoothed mortality rates (0.61, p < 0.001). Regression revealed that for each 10% increase in SVI ranking, COVID-19 vaccination rates decreased by 3.02-fold (95% CI = 3.73-2.30), and mortality rates increased by a factor of 1.19 (95% CI = 0.99-1.43). SVI values are spatially linked and significantly associated with Louisiana's COVID-19-related vaccination and mortality rates. We also found that vaccination uptake was higher in whites than in blacks. These findings can help identify regions with low vaccination rates and high mortality, enabling the necessary steps to increase vaccination rates in disadvantaged neighborhoods.

COVID-19 and drivers of excess death rate in Peru: A longitudinal ecological study

Background

Peru has experienced unprecedented mortality and economic toll due to the COVID-19 (Coronavirus disease 2019) pandemic in 2020. We aimed to assess the association between socioeconomic factors and excess death rate, and to explore the relative contribution of these factors to the differences in excess death rate during January–December 2020.

Methods

Different national secondary data sources were used to describe excess death rates and different determinants, from distal to proximal. A confounding-adjusted multilevel mixed-effects linear regression was used to assess the association between these variables and excess death rates. Their relative contributions to the differences in excess death rate between the periods with the highest and lowest excess death rates were analyzed through regression-based Oaxaca-Blinder decomposition methods.

Findings

The excess death rate showed an increasing trend in all regions, with different slopes. The confounding-adjusted multilevel analysis showed that higher healthcare access was associated with lower excess death rates (difference (95%CI) -0.004 (-0.005, -0.002)), whereas COVID-19 incidence was associated with higher excess death rates (difference (95%CI) 0.052 (0.042, 0.063)). The decomposition analysis showed COVID-19 incidence (41.9%), per capita income (19.4%) and unemployment rate (14.6%) as the main risk factors, while the main protective factors included per capita health expenditure (44.7%), healthcare access (33.2%) and health insurance (12.1%).

Interpretation

Our study suggests that the excess death rate during the COVID-19 pandemic in Peru may have been influenced by other factors besides COVID-19 incidence, from distal to proximal drivers, including socioeconomic determinants, factors outside and within the health sector, and susceptibility factors. Further studies at individual level are needed to corroborate our findings.

The Unequal Impact of the COVID-19 Pandemic on Infant Health

The COVID-19 pandemic has taken a large toll on population health and well-being. We examine the consequences of prenatal exposure for infant health, through which the pandemic may have lasting intergenerational effects. We examine multiple pathways by which the pandemic shaped birth outcomes and socioeconomic disparities in these consequences. Analysis of more than 3.5 million birth records in California with universal information on COVID infection among persons giving birth at the time of delivery reveals deep inequalities in infection by education, race/ethnicity, and place-based socioeconomic disadvantage. COVID infection during pregnancy, in turn, predicts a large increase in the probability of preterm birth, by approximately one third. At the population level, a surprising reduction in preterm births during the first months of the pandemic was followed by an increase in preterm births during the surge in COVID infections in the winter of 2021. Whereas the early-pandemic reduction in preterm births benefited primarily highly educated mothers, the increase in preterm births during the winter infection surge was entirely concentrated among mothers with low levels of schooling. The COVID-19 pandemic is expected to exacerbate U.S. inequality in multiple ways. Our findings highlight a particularly enduring pathway: the long-term legacy of prenatal exposure to an unequal pandemic environment.

Association of Economic Well-Being With Comorbid Conditions in Patients Undergoing Carpal Tunnel Release

PURPOSE

Medical comorbidities have been associated with the development of carpal tunnel syndrome (CTS), severity at the time of presentation, and outcomes of carpal tunnel release (CTR). Socioeconomic factors have also been associated with worse function in patients with CTS at presentation and after surgery. However, the effects of economic well-being on the prevalence of medical comorbidities in patients with CTS have not been well-described. The objective of this study was to determine whether economic well-being is associated with medical comorbidities in a cohort of patients undergoing CTR.

METHODS

Patients (n = 1,297) who underwent CTR at a single tertiary care referral center over a 5-year period from July 2008 to June 2013 were retrospectively identified. The exclusion criteria were acute trauma or infection, revision surgery, incomplete medical records, and neoplasm excision. Additionally, patients were excluded if they lacked documented confirmatory or normal electrodiagnostic study findings prior to CTR. Finally, this study comprised a cohort of 892 patients with electrodiagnostic study-confirmed CTS who underwent CTR. The economic well-being of patients was assessed using the Distressed Communities Index. The comorbidities of diabetes mellitus, chronic kidney disease, hypertension, hypothyroidism, cervical radiculopathy, tobacco use, and body mass index were assessed. Bivariate comparisons were used to determine the associations between the tiers of economic well-being and comorbidities.

RESULTS

Lower economic well-being was associated with body mass index, diabetes mellitus, chronic kidney disease, and tobacco use in these patients. Although hypertension, hypothyroidism, and cervical radiculopathy were not associated with economic well-being, their comparisons were underpowered.

CONCLUSIONS

Patients experiencing economic distress have a higher comorbidity burden, and as such, may be at an increased risk of complications or poorer outcomes. The association between economic well-being and comorbidities in this population suggests the need for a multidisciplinary care model that addresses both compressive neuropathy and the associated economic factors.

TYPE OF STUDY/LEVEL OF EVIDENCE

Prognostic II.

Population flow based spatial-temporal eigenvector filtering modeling for exploring effects of health risk factors on COVID-19

The COVID-19 pandemic has had great impact on human health and social economy. Several studies examined spatial and temporal patterns of health risk factors associated with COVID-19, but population flow spillover effect has not been sufficiently considered. In this paper, a population flow-based spatial-temporal eigenvector filtering model (FLOW-ESTF) was developed to consider spatial-temporal patterns and population flow connectivity simultaneously. The proposed FLOW-ESTF method efficiently improved model prediction accuracy, which could help the government aware of the infection risk level and to make suitable control policies. The selected population flow spatial-temporal eigenvector contributed most to modeling and the visualization of corresponding eigenvector set helped to explore the underlying spatial-temporal patterns and pandemic transmission nodes. The model coefficients could reflect how health risk factors contribute the modeling of state-level COVID-19 weekly increased cases and how their influence changed through time, which could help people and government to better aware the potential health risks and to adjust control measures at different stage. The extracted population flow spatial-temporal eigenvector not only represents influence of population flow and its spillover effects but also represents some possible omitted health risk factors. This could provide an efficient path to solve the problem of spatial and temporal autocorrelation in COVID-19 modeling and an intuitive way to discover underlying spatial patterns, which will partially compensate for the problems of insufficient consideration of potential risk variables and missing data.

A joint Bayesian spatiotemporal risk prediction model of COVID-19 incidence, IC admission, and death with application to Sweden

The three closely related COVID-19 outcomes of incidence, intensive care (IC) admission and death, are commonly modelled separately leading to biased estimation of the parameters and relatively poor forecasts. This paper presents a joint spatiotemporal model of the three outcomes based on weekly data that is used for risk prediction and identification of hotspots. The paper applies a pure spatiotemporal model consisting of structured and unstructured spatial and temporal effects and their interaction capturing the effects of the unobserved covariates. The pure spatiotemporal model limits the data requirements to the three outcomes and the population at risk per spatiotemporal unit. The empirical study for the 21 Swedish regions for the period 1 January 2020-4 May 2021 confirms that the joint model predictions outperform the separate model predictions. The fifteen-week-ahead spatiotemporal forecasts (5 May-11 August 2021) show a significant decline in the relative risk of COVID-19 incidence, IC admission, death and number of hotspots.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00168-022-01191-1.

Delta and Omicron: protective measures and SARS-CoV-2 infections in day care centres in Germany in the 4th and 5th wave of the pandemic 2021/2022

Background

During the five waves of the SARS-CoV-2 pandemic so far, German early childhood education and care (ECEC) centres implemented various protective measures, such as wearing a face mask, fixed children-staff groups or regular ventilation. In addition, parents and ECEC staff were increasingly vaccinated throughout 2021. During the 4th wave, variant of concern (VOC) Delta-driven transmission indicators reached record values at the end of 2021. Those values were even exceeded in the 5th wave at the beginning of 2022 when Omicron dominated. We examine which factors facilitated or prevented infection with SARS-CoV-2 in ECEC centres, and if these differed between different phases within wave 4 (Delta) and 5 (Omicron).

Methods

Since August 2020, a weekly online survey among approximately 8000 ECEC managers has been conducted, monitoring both incident SARS-CoV-2 infections and protective measures taken. We included data from calendar week 26/2021 to 05/2022. We estimate the probability of any infections and the number of SARS-CoV-2 infections in children, parents and staff using random-effect-within-between (REWB) panel models for binomial and count data.

Results

While children, parents and staff of ECEC centres with a high proportion of children from families with low socioeconomic status (SES) have a higher risk of infections in the beginning of wave 4 (OR up to 1.99 [1.56; 2.56]), this effect diminishes for children and parents with rising incidences. Protective measures, such as wearing face masks, tend to have more extensive effects with rising incidences in wave 5 (IRR up to 0.87 [0.8; 0.93]). Further, the protective effect of vaccination against infection among staff is decreasing from wave 4 to wave 5 (OR 0.3 [0.16; 0.55] to OR 0.95, [0.84; 1.07, n.s.]). The degree of transmission from staff to child and from staff to parent is decreasing from wave 4 to wave 5, while transmission from child to staff seems to increase.

Conclusion

While Omicron seems to affect children and parents from ECEC centres with families with all SES levels more equally than Delta, the protective effect of vaccination against infection is decreasing and the effect of protective measures like face masks becomes increasingly important. In order to prevent massive closures of ECEC centres due to infection of staff, protective measures should be strictly adhered to, especially to protect staff in centres with a high proportion of children from families with low socioeconomic status.

Environmental health, COVID-19, and the syndemic: internal medicine facing the challenge

Internists are experts in complexity, and the COVID-19 pandemic is disclosing complex and unexpected interactions between communicable and non-communicable diseases, environmental factors, and socio-economic disparities. The medicine of complexity cannot be limited to facing comorbidities and to the clinical management of multifaceted diseases. Evidence indicates how climate change, pollution, demographic unbalance, and inequalities can affect the spreading and outcomes of COVID-19 in vulnerable communities. These elements cannot be neglected, and a wide view of public health aspects by a "one-health" approach is strongly and urgently recommended. According to World Health Organization, 35% of infectious diseases involving the lower respiratory tract depend on environmental factors, and infections from SARS-Cov-2 is not an exception. Furthermore, environmental pollution generates a large burden of non-communicable diseases and disabilities, increasing the individual vulnerability to COVID-19 and the chance for the resilience of large communities worldwide. In this field, the awareness of internists must increase, as privileged healthcare providers. They need to gain a comprehensive knowledge of elements characterizing COVID-19 as part of a syndemic. This is the case when pandemic events hit vulnerable populations suffering from the increasing burden of chronic diseases, disabilities, and social and economic inequalities. Mastering the interplay of such events requires a change in overall strategy, to adequately manage not only the SARS-CoV-2 infection but also the growing burden of non-communicable diseases by a "one health" approach. In this context, experts in internal medicine have the knowledge and skills to drive this change.

An experimental COVID-19 messaging study in a representative sample of the Scottish population: Increasing physical distancing intentions through self-efficacy

OBJECTIVES

Self-efficacy is important for adherence to transmission-reducing behaviours (e.g., physical distancing) as also shown in the CHARIS project. We aimed to show that a theory-based short message can increase physical distancing self-efficacy and intentions to keep physical distance.

DESIGN

Structured telephone surveys with a randomly selected nationally representative sample of adults in Scotland (N = 497).

METHODS

Participants were randomly assigned to one of two experimental conditions: message condition (short message to increase self-efficacy via vicarious experiences, verbal persuasion and emotional arousal) or control condition (no message). Followed by measures for self-efficacy and intention for physical distancing on 4-point scales. Adherence to physical distancing was assessed on a 5-point frequency scale (never - always).

RESULTS

Using mediation analyses with bootstrapping procedures, we first confirmed that self-efficacy was associated indirectly with adherence, via higher intentions in a partial mediation (unstandardized indirect effect .21, 95% CI .18-.25). The message increased self-efficacy; participants receiving the message reported higher self-efficacy (M = 4.23, SD = .80) compared to participants in the control condition (M = 4.08, SD = .77; standardized regression coefficient = .19, p < .05) and self-efficacy affected intention (.48, p < .001). There was a small significant indirect effect of the message on intention via self-efficacy (unstandardized indirect effect .07, CI .01-.14).

CONCLUSIONS

Increasing self-efficacy for physical distancing with a short message can successfully increase intention to physical distance via increased self-efficacy. As both self-efficacy and intentions are important predictors of adherence to transmission-reducing behaviours short messages have potential to limit the spread of COVID-19.

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.

How Cumulative Statistics Can Mislead: The Temporal Dynamism of Sex Disparities in COVID-19 Mortality in New York State

Overall, men have died from COVID-19 at slightly higher rates than women. But cumulative estimates of mortality by sex may be misleading. We analyze New York State COVID-19 mortality by sex between March 2020 and August 2021, demonstrating that 72.7% of the total difference in the number of COVID-19 deaths between women and men was accrued in the first seven weeks of the pandemic. Thus, while the initial surge in COVID-19 mortality was characterized by stark sex disparities, this article shows that disparities were greatly attenuated in subsequent phases of the pandemic. Investigating changes over time could help illuminate how contextual factors contributed to the development of apparent sex disparities in COVID-19 outcomes.

Revisiting the COVID-19 fatality rate and altitude association through a comprehensive analysis

The emergence of COVID-19 virus has led to a pandemic with staggering morbidity and mortality. There is evidence showing that pre-existing conditions and environmental factors are associated with worse COVID-19 outcomes. Among these conditions, altitude is of particular interest. Altitude has been shown to influence the morbidity and mortality of multiple chronic pathologies such as cardiovascular disease, chronic obstructive pulmonary disease and lung cancer. COVID-19 fatality rate has been associated with as altitude as well, but findings are disputed. Therefore, we revisit this assessment with a comprehensive analysis of the relationship between COVID-19 fatality rates and altitude for the Mountain region of the United States while considering the effect of additional comorbidities and sociodemographic factors. A Generalized Additive Model (GAM) approach using one year of county data adjusted by population density was performed to evaluate associations within states and for the whole region. Our analysis revealed a consistent effect where COVID-19 case-fatality rate is decreased with higher altitude, even when controlling for pre-existing conditions and certain demographic variables. In summary, the work presented provides evidence that suggests that the protective effects of high altitude are likely to be influenced by physiologic factors but demographic trends that are associated with life at high altitude must also be considered.

Compliance with COVID-19 preventive measures among chronic disease patients in Wolaita and Dawuro zones, Southern Ethiopia: A proportional odds model

Introduction

So far, shreds of evidence have shown that COVID-19 related hospitalization, serious outcomes, and mortality were high among individuals with chronic medical conditions. However, strict compliance with basic public health measures such as hand washing with soap, social distancing, and wearing masks has been recommended and proven effective in preventing transmission of the infection. Therefore, this study aimed to determine the level of compliance with COVID-19 preventive measures and identify its predictors among patients with common chronic diseases in public hospitals of Southern Ethiopia by applying the proportional odds model.

Methods

A facility-based cross-sectional study was employed in public hospitals of Southern Ethiopia between February and March 2021. Using a systematic random sampling technique, 419 patients with common chronic diseases were recruited. Data were collected using an Open Data Kit and then submitted to the online server. The proportional odds model was employed, and the level of significance was declared at a p-value of less than 0.05.

Results

This study revealed that 55.2% (95%CI: 50.4%-59.9%) of the study participants had low compliance levels with COVID-19 preventive measures. The final proportional odds model identified that perceived susceptibility (AOR: 0.91, 95%CI: 0.84, 0.97), cues to action (AOR: 0.89, 95%CI: 0.85, 0.94), having access to drinking water piped into the dwelling (AOR: 0.52, 95%CI: 0.32, 0.84), having no access to any internet (AOR: 0.62, 95%CI: 0.42, 0.92), having no functional refrigerator (AOR: 2.17, 95%CI: 1.26, 3.74), and having poor knowledge (AOR: 1.42, 95%CI: 1.02, 1.98) were the independent predictors of low compliance level with COVID-19 preventive measures.

Conclusion

In the study area, more than half of the participants had low compliance levels with COVID-19 preventive measures. Thus, the identified factors should be considered when designing, planning, and implementing new interventional strategies, so as to improve the participants’ compliance level.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.