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

First wave of COVID-19 in Venezuela: Epidemiological, clinical, and paraclinical characteristics of first cases

The coronavirus disease 2019 (COVID-19) pandemic has particularly affected countries with weakened health services in Latin America, where proper patient management could be a critical step to address the epidemic. In this study, we aimed to characterize and identify which epidemiological, clinical, and paraclinical risk factors defined COVID-19 infection from the first confirmed cases through the first epidemic wave in Venezuela. A retrospective analysis of consecutive suspected cases of COVID-19 admitted to a sentinel hospital was carried out, including 576 patient cases subsequently confirmed for severe acute respiratory syndrome coronavirus 2 infection. Of these, 162 (28.1%) patients met the definition criteria for severe/critical disease, and 414 (71.2%) were classified as mild/moderate disease. The mean age was 47 (SD 16) years, the majority of which were men (59.5%), and the most frequent comorbidity was arterial hypertension (23.3%). The most common symptoms included fever (88.7%), headache (65.6%), and dry cough (63.9%). Severe/critical disease affected mostly older males with low schooling (p < 0.001). Similarly, higher levels of glycemia, urea, aminotransferases, total bilirubin, lactate dehydrogenase, and erythrocyte sedimentation rate were observed in severe/critical disease patients compared to those with mild/moderate disease. Overall mortality was 7.6% (44/576), with 41.7% (28/68) dying in hospital. We identified risk factors related to COVID-19 infection, which could help healthcare providers take appropriate measures and prevent severe clinical outcomes. Our results suggest that the mortality registered by this disease in Venezuela during the first epidemic wave was underestimated. An increase in fatalities is expected to occur in the coming months unless measures that are more effective are implemented to mitigate the epidemic while the vaccination process is ongoing.

The COVID-19 wave in Belgium during the Fall of 2020 and its association with higher education

Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, COVID-19 incidence fell slightly, to then enter two successive phases of rapid incline: in the first half of September, and then again in October 2020. The first of these coincided with the peak period of returning summer travelers; the second one coincided with the start of higher education's academic year. The largest observed COVID-19 incidence occurred in the period 16-31 October, particularly in the Walloon Region, the southern, French-speaking part of Belgium. We examine the potential association of the higher education population with spatio-temporal spread of COVID-19, using Bayesian spatial Poisson models for confirmed test cases, accounting for socio-demographic heterogeneity in the population. We find a significant association between the number of COVID-19 cases in the age groups 18-29 years and 30-39 years and the size of the higher education student population at the municipality level. These results can be useful towards COVID-19 mitigation strategies, particularly in areas where virus transmission from higher education students into the broader community could exacerbate morbidity and mortality of COVID-19 among populations with prevalent underlying conditions associated with more severe outcomes following infection.

Brief communication: Chest radiography score in young COVID-19 patients: Does one size fit all?

During the SARS-CoV-2 pandemic, chest X-Ray (CXR) scores are essential to rapidly assess patients’ prognoses. This study evaluates a published CXR score in a different national healthcare system. In our study, this CXR score maintains a prognostic role in predicting length of hospital stay, but not disease severity. However, our results show that the predictive role of CXR score could be influenced by socioeconomic status and healthcare system.

Results of the Adult COVID-19 Lifestyle Matching Study

Objective: The aim of our case-control study was to find the influence of lifestyle and comorbidities on COVID-19 susceptibility, identify risk factors and protective factors, and identify ways to encourage people to adopt a healthy lifestyle.

Methods: Patients with COVID-19 were matched with non-COVID-19 participants in a ratio of 1:2. Univariate analysis was performed using the chi-square test, and multivariate analysis was performed using conditional logistic regression.

Results: Multivariate analysis using conditional logistic regression found that alcohol consumption (AC) and a bland diet increased the risk of COVID-19, while college degrees and above, smoking, drinking tea, and exercise, especially walking, significantly reduced the risk of COVID-19.

Conclusion: After removing the effects of demographic factors, the study demonstrated that AC significantly reduced the ability of the body to resist COVID-19 infection. Moreover, following a bland diet increased the susceptibility to COVID-19. Notably, people who drank tea and performed regular exercises, especially walking, were significantly less likely to be infected with COVID-19. College degree or above relative illiteracy is COVID-19 protective factors of infection.

Investigating the effect of macro-scale estimators on worldwide COVID-19 occurrence and mortality through regression analysis using online country-based data sources

OBJECTIVE

To investigate macro-scale estimators of the variations in COVID-19 cases and deaths among countries.

DESIGN

Epidemiological study.

SETTING

Country-based data from publicly available online databases of international organisations.

PARTICIPANTS

The study involved 170 countries/territories, each of which had complete COVID-19 and tuberculosis data, as well as specific health-related estimators (obesity, hypertension, diabetes and hypercholesterolaemia).

PRIMARY AND SECONDARY OUTCOME MEASURES

The worldwide heterogeneity of the total number of COVID-19 cases and deaths per million on 31 December 2020 was analysed by 17 macro-scale estimators around the health-related, socioeconomic, climatic and political factors. In 139 of 170 nations, the best subsets regression was used to investigate all potential models of COVID-19 variations among countries. A multiple linear regression analysis was conducted to explore the predictive capacity of these variables. The same analysis was applied to the number of deaths per hundred thousand due to tuberculosis, a quite different infectious disease, to validate and control the differences with the proposed models for COVID-19.

RESULTS

In the model for the COVID-19 cases (R²=0.45), obesity (β=0.460), hypertension (β=0.214), sunshine (β=-0.157) and transparency (β=0.147); whereas in the model for COVID-19 deaths (R²=0.41), obesity (β=0.279), hypertension (β=0.285), alcohol consumption (β=0.173) and urbanisation (β=0.204) were significant factors (p<0.05). Unlike COVID-19, the tuberculosis model contained significant indicators like obesity, undernourishment, air pollution, age, schooling, democracy and Gini Inequality Index.

CONCLUSIONS

This study recommends the new predictors explaining the global variability of COVID-19. Thus, it might assist policymakers in developing health policies and social strategies to deal with COVID-19.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT04486508).

Changes in Active Behaviours, Physical Activity, Sedentary Time, and Physical Fitness in Chilean Parents during the COVID-19 Pandemic: A Retrospective Study

Strategies to reduce the spread of coronavirus disease 2019 (COVID-19) have caused different behavioural modifications in all populations. Therefore, this study aimed to determine changes in active commuting, moderate-to-vigorous physical activity (MVPA), physical fitness, and sedentary time during the COVID-19 pandemic in Chilean parents. Eighty-six fathers (41.30 ± 6.82 years) and 294 mothers (40.68 ± 6.92 years) of children from different schools from Valparaíso, Chile, participated. Inclusion criteria were adults with schoolchildren who were resident in Chile during the research period. Convenience sampling was used as a non-probabilistic sampling technique. Respondents completed a self-reported online survey about active commuting, MVPA, self-perceived physical fitness, and sedentary time July–September 2020 during the first pandemic period. Comparisons between before and during the pandemic were performed using t-tests and covariance analysis (ANCOVA), establishing a significance level at p < 0.05. Most participants stayed at home during the pandemic, whereas active and passive commuting significantly decreased in both fathers and mothers (p < 0.001). MVPA and physical fitness scores reduced considerably (p < 0.05), while sedentary time significantly increased (p < 0.05), independent of the sex of parents and children’s school type. Differences by age groups and the number of children were more heterogeneous, as younger parents showed a larger decrease in MVPA (p < 0.05) and physical fitness score (p < 0.05). Additionally, parents with one child showed a larger decrease in sedentary time (p < 0.05) than those with two or more children. The COVID-19 pandemic significantly affected healthy behaviours. Hence, health policies should promote more strategies to mitigate the long-term health effects of the pandemic on Chilean parents.

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis

With evidence-based measures, COVID-19 can be effectively controlled by advanced data analysis and prediction. However, while valuable insights are available, there is a shortage of robust and rigorous research on what factors shape COVID-19 transmissions at the city cluster level. Therefore, to bridge the research gap, we adopted a data-driven hierarchical modeling approach to identify the most influential factors in shaping COVID-19 transmissions across different Chinese cities and clusters. The data used in this study are from Chinese officials, and hierarchical modeling conclusions drawn from the analysis are systematic, multifaceted, and comprehensive. To further improve research rigor, the study utilizes SPSS, Python and RStudio to conduct multiple linear regression and polynomial best subset regression (PBSR) analysis for the hierarchical modeling. The regression model utilizes the magnitude of various relative factors in nine Chinese city clusters, including 45 cities at a different level of clusters, to examine these aspects from the city cluster scale, exploring the correlation between various factors of the cities. These initial 12 factors are comprised of ‘Urban population ratio’, ‘Retail sales of consumer goods’, ‘Number of tourists’, ‘Tourism Income’, ‘Ratio of the elderly population (> 60 year old) in this city’, ‘population density’, ‘Mobility scale (move in/inbound) during the spring festival’, ‘Ratio of Population and Health facilities’, ‘Jobless rate (%)’, ‘The straight-line distance from original epicenter Wuhan to this city’, ‘urban per capita GDP’, and ‘the prevalence of the COVID-19’. The study’s results provide rigorously-tested and evidence-based insights on most instrumental factors that shape COVID-19 transmissions across cities and regions in China. Overall, the study findings found that per capita GDP and population mobility rates were the most affected factors in the prevalence of COVID-19 in a city, which could inform health experts and government officials to design and develop evidence-based and effective public health policies that could curb the spread of the COVID-19 pandemic.

Prevalence of Antibodies to SARS-CoV-2 Following Natural Infection and Vaccination in Irish Hospital Healthcare Workers: Changing Epidemiology as the Pandemic Progresses

BACKGROUND

In October 2020 SARS-CoV-2 seroprevalence among hospital healthcare workers (HCW) of two Irish hospitals was 15 and 4. 1%, respectively. We compare seroprevalence in the same HCW population 6 months later, assess changes in risk factors for seropositivity with progression of the pandemic and serological response to vaccination.

METHODS

All staff of both hospitals (N = 9,038) were invited to participate in an online questionnaire and SARS-CoV-2 antibody testing in April 2021. We measured anti-nucleocapsid and anti-spike antibodies. Frequencies and percentages for positive SARS-CoV-2 antibodies were calculated and adjusted relative risks for participant characteristics were calculated using multivariable regression analysis.

RESULTS

Five thousand and eighty-five HCW participated. Seroprevalence increased to 21 and 13%, respectively; 26% of infections were previously undiagnosed. Black ethnicity (aRR 1.7, 95% CI 1.3-2.2, p < 0.001), lower level of education (aRR 1.4 for secondary level education, 95% CI 1.1-1.8, p = 0.002), living with other HCW (aRR 1.2, 95% CI 1.0-1.4, p = 0.007) were significantly associated with seropositivity. Having direct patient contact also carried a significant risk being a healthcare assistant (aRR 1.8, 95% CI 1.3-2.3, p < 0.001), being a nurse (aRR 1.4, 95% CI 1.0-1.8, p = 0.022), daily contact with COVID-19 patients (aRR 1.4, 95% CI 1.1-1.7, p = 0.002), daily contact with patients without suspected or confirmed COVID-19 (aRR 1.3, 95% CI 1.1-1.5, p = 0.013). Breakthrough infection occurred in 23/4,111(0.6%) of fully vaccinated participants; all had anti-S antibodies.

CONCLUSION

The increase in seroprevalence reflects the magnitude of the third wave of the pandemic in Ireland. Genomic sequencing is needed to apportion risk to the workplace vs. the household/community. Concerted efforts are needed to mitigate risk factors due to ethnicity and lower level of education, even at this stage of the pandemic. The undiagnosed and breakthrough infections call for ongoing infection prevention and control measures and testing of HCW in the setting of close contact. Vaccinated HCW with confirmed infection should be actively assessed, including SARS-CoV-2 whole genome sequencing (WGS), serology testing and assessment of host determinants, to advance understanding of the reasons for breakthrough infection.

Human mobility impacts on the surging incidence of COVID‐19 in India

Human mobility triggers how fast and where infectious diseases spread and modelling community flows helps assess the impact of social distancing policies and advance our understanding of community behaviour in such circumstances. This study investigated the relationship between human mobility and the surging incidence of COVID‐19 in India. We performed a generalised estimating equation with a Poisson log‐linear model to analyse the daily mobility rate and new cases of COVID‐19 between 14 March and 11 September 2020. We found that mobility to grocery and retail locations was significantly associated (p < 0.01) with the incidence of COVID‐19, these being crowded and unorganised in most parts of India. In contrast, visits to parks, workplaces, and transit stations did not considerably affect the changing COVID‐19 cases over time. In particular, workplaces equipped with social distancing protocols or low‐density open spaces are much less susceptible to the spread of the virus. These findings suggest that human mobility data, geographic information, and health geography modelling have significant potential to inform strategic decision‐making during pandemics because they provide actionable knowledge of when and where communities might be exposed to the disease.

COVID-19 mortality in Istanbul in association with air pollution and socioeconomic status: an ecological study

This study aims to reveal the relationship between the COVID-19 mortality indicators and socioeconomic status (SES) and air pollution. In this ecological study, the focus was put on the relationship between COVID-19 mortality and both air quality and socioeconomic status at the district level in Istanbul. The mortality variables of the study are the excess deaths due to the pandemic, the proportion of deaths due to the pandemic among all deaths, COVID-19 mortality rate (per 100,000), and the proportion of COVID-19 deaths among older people (above the age of 65). The daily air quality measurements of PM10, SO2, NO2, and NOx of the pre-pandemic term were included in the research to avoid bias due to decreasing traffic burden during the pandemic. Partial correlation was applied to analyze the relationship between air quality and mortality measures by controlling socioeconomic status, the percentage of the older population, and household size. Every 20% deterioration in the SES stratum has contributed to a 4% increase in excess mortality at the district level. The elderly population ratio of over 10% in the districts was found to increase the COVID-19 deaths in the total population by 35% and the deaths in the population over 65 years old by 3%. Average household size was correlated with COVID-19 deaths in the population over 65. A moderate correlation was found between the COVID-19 mortality rate per 100,000 population and PM10, SO2, and NO2 (r = 0.413, 0.421, and 0.431, respectively). Mortality during the COVID-19 pandemic in Istanbul is related to an interaction of socioeconomic characteristics and air pollution as an environmental issue.

Using behavioural theory to understand adherence to behaviours that reduce transmission of COVID-19; evidence from the CHARIS representative national study

OBJECTIVES

To examine the ability of four models of behaviour, namely, Protection Motivation Theory (PMT), the Common Sense Self-Regulation Model (CS-SRM), and Social Cognitive Theory and the Reasoned Action Approach (SCT and RAA) to understand adherence to transmission-reducing behaviours (TRBs) advised by national governments for suppression of SARS-CoV2.

DESIGN

A series of six cross-sectional telephone surveys of a random representative sample of adults living in Scotland.

METHODS

Self-reported adherence to three TRBs (physical distancing, wearing a face covering and handwashing), PMT, CS-SRM, and SCT/RAA constructs, and sociodemographic variables were measured each week for 6 weeks (n = ~500 p/w; third June-15th July) via a 15 min telephone survey.

RESULTS

Adherence was high ('Always' or 'Most times') throughout for physical distancing and handwashing, and, when mandated, for wearing a face covering. Older people were more adherent to all TRBs. Constructs from all three models predicted all three TRBs. Intention and self-efficacy (SCT/RAA) were the only beliefs to predict to all three TRBs each week and for all groups equally; intention was the strongest predictor. The predictive utility of PMT and CS-SRM varied by TRB and by group. Of note was the observation that several illness beliefs were associated with adherence only for those who believed they had not had COVID-19.

CONCLUSIONS

The CHARIS project has identified beliefs about specific behaviours, the illness and the risks associated with lower adherence rates that might be addressed in national interventions. It confirms previous findings that some groups show lower levels of adherence and might be specially targeted.

Efficacy of Severe Acute Respiratory Syndrome Coronavirus-2 Vaccine in Patients With Thoracic Cancer: A Prospective Study Supporting a Third Dose in Patients With Minimal Serologic Response After Two Vaccine Doses

INTRODUCTION

Coronavirus disease 2019 resulted in a 30% mortality rate in patients with thoracic cancer. Given that patients with cancer were excluded from serum antisevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccine registration trials, it is still unknown whether they would develop a protective antispike antibody response after vaccination. This prospective vaccine monitoring study primarily aimed to assess humoral responses to the SARS-CoV-2 vaccine in patients with thoracic cancer.

METHODS

SARS-CoV-2-spike antibodies were measured using the Abbot Architect SARS-CoV-2 immunoglobulin G immunoassay before the first injection of BNT162b2 mRNA vaccine, at week 4, and 2 to 16 weeks after the second vaccine dose administration. The factors associated with antibody response were analyzed.

RESULTS

Overall, 306 patients, with a median age of 67.0 years (interquartile range: 58-74), were vaccinated. Of these, 283 patients received two vaccine doses at 28-day intervals. After a 6.7-month median follow-up, eight patients (2.6%) contracted proven symptomatic SARS-CoV-2 infection, with rapid favorable evolution. Of the 269 serologic results available beyond day 14 after the second vaccine dose administration, 17 patients (6.3%) were still negative (<50 arbitrary units/mL, whereas 34 (11%) were less than 300 arbitrary units/mL (12.5th percentile). In multivariate analysis, only age (p < 0.01) and long-term corticosteroid treatment (p = 0.01) were significantly associated with a lack of immunization. A total of 30 patients received a third vaccine dose, with only three patients showing persistently negative serology thereafter, whereas the others exhibited clear seroconversion.

CONCLUSIONS

SARS-CoV2 vaccines were found to be efficient in patients with thoracic cancer, most of them being immunized after two doses. A third shot given to 1% of patients with persistent low antibody titers resulted in an 88% immunization rate.

COVID-19: Regional Differences in Austria

In the turbulent year 2020, overshadowed by the global COVID-19 pandemic, Austria experienced multiple waves of increased case incidence. While governmental measures to curb the numbers were based on current knowledge of infection risk factors, a retrospective analysis of incidence and lethality at the district level revealed correlations of relative infection risk with socioeconomic, geographical, and behavioral population parameters. We identified unexpected correlations between political orientation and smoking behavior and COVID-19 infection risk and/or mortality. For example, a decrease in daily smokers by 2.3 percentage points would be associated with an increase in cumulative incidence by 10% in the adjusted model, and an increase in voters of the right-wing populist party by 1.6 percentage points with an increase in cumulative mortality by 10%. While these parameters are apparently only single elements of complex causal chains that finally lead to individual susceptibility and vulnerability levels, our findings might have identified ecological parameters that can be utilized to develop fine-tuned communications and measures in upcoming challenges of this and other pandemics.

Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China

The COVID-19 pandemic has led to many deaths and economic disruptions across the world. Several studies have examined the effect of corresponding health risk factors in different places, but the problem of spatial heterogeneity has not been adequately addressed. The purpose of this paper was to explore how selected health risk factors are related to the pandemic infection rate within different study extents and to reveal the spatial varying characteristics of certain health risk factors. An eigenvector spatial filtering-based spatially varying coefficient model (ESF-SVC) was developed to find out how the influence of selected health risk factors varies across space and time. The ESF-SVC was able to take good control of over-fitting problems compared with ordinary least square (OLS), eigenvector spatial filtering (ESF) and geographically weighted regression (GWR) models, with a higher adjusted R2 and lower cross validation RMSE. The impact of health risk factors varied as the study extent changed: In Hubei province, only population density and wind speed showed significant spatially constant impact; while in mainland China, other factors including migration score, building density, temperature and altitude showed significant spatially varying impact. The influence of migration score was less contributive and less significant in cities around Wuhan than cities further away, while altitude showed a stronger contribution to the decrease of infection rates in high altitude cities. The temperature showed mixed correlation as time passed, with positive and negative coefficients at 2.42 °C and 8.17 °C, respectively. This study could provide a feasible path to improve the model fit by considering the problem of spatial autocorrelation and heterogeneity that exists in COVID-19 modeling. The yielding ESF-SVC coefficients could also provide an intuitive method for discovering the different impacts of influencing factors across space in large study areas. It is hoped that these findings improve public and governmental awareness of potential health risks and therefore influence epidemic control strategies.

COVID-19 infections in day care centres in Germany: social and organisational determinants of infections in children and staff in the second and third wave of the pandemic

BACKGROUND

During the SARS-CoV-2 pandemic, German early childhood education and care (ECEC) centres organised children's attendance in different ways, they reduced opening hours, provided emergency support for a few children, or closed completely. Further, protection and hygiene measures like fixed children-staff groups, ventilation and surface disinfection were introduced in ECEC centres. To inform or modify public health measures in ECEC, we investigate the occurrence of SARS-CoV-2 infections among children and staff in ECEC centres in light of social determinants (i.e. the socioeconomic status of the children) and recommended structural and hygiene measures. We focus on the question if the relevant factors differ between the 2nd (when no variant of concern (VOC) circulated) and the 3rd wave (when VOC B.1.1.7 (Alpha) predominated).

METHODS

Based on panel data from a weekly online survey of ECEC centre managers (calendar week 36/2020 to 22/2021, ongoing) including approx. 8500 centres, we estimate the number of SARS-CoV-2 infections in children and staff using random-effect-within-between (REWB) panel models for count data in the 2nd and 3rd wave.

RESULTS

ECEC centres with a high proportion of children with low socioeconomic status (SES) have a higher risk of infections in staff and children. Strict contact restrictions between groups like fixed group assignments for children and fixed staff assignments to groups prevent infections. Both effects tend to be stronger in the 3rd wave.

CONCLUSION

ECEC centres with a large proportion of children with a low SES background and lack of using fixed child/staff cohorts experience higher COVID-19 rates. Over the long run, centres should be supported in maintaining recommended measures. Preventive measures such as the vaccination of staff should be prioritised in centres with large proportions of low SES children.

COVID-19-Related Mortality Risk in People With Severe Mental Illness: A Systematic and Critical Review

Background: Increasing clinical evidence suggests that people with severe mental illness (SMI), including schizophrenia spectrum disorders, bipolar disorder (BD), and major depressive disorder (MDD), are at higher risk of dying from COVID-19. Several systematic reviews examining the association between psychiatric disorders and COVID-19-related mortality have recently been published. Although these reviews have been conducted thoroughly, certain methodological limitations may hinder the accuracy of their research findings. Methods: A systematic literature search, using the PubMed, Embase, Web of Science, and Scopus databases (from inception to July 23, 2021), was conducted for observational studies assessing the risk of death associated with COVID-19 infection in adult patients with pre-existing schizophrenia spectrum disorders, BD, or MDD. Methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: Of 1,446 records screened, 13 articles investigating the rates of death in patients with pre-existing SMI were included in this systematic review. Quality assessment scores of the included studies ranged from moderate to high. Most results seem to indicate that patients with SMI, particularly patients with schizophrenia spectrum disorders, are at significantly higher risk of COVID-19-related mortality, as compared to patients without SMI. However, the extent of the variation in COVID-19-related mortality rates between studies including people with schizophrenia spectrum disorders was large because of a low level of precision of the estimated mortality outcome(s) in certain studies. Most studies on MDD and BD did not include specific information on the mood state or disease severity of patients. Due to a lack of data, it remains unknown to what extent patients with BD are at increased risk of COVID-19-related mortality. A variety of factors are likely to contribute to the increased mortality risk of COVID-19 in these patients. These include male sex, older age, somatic comorbidities (particularly cardiovascular diseases), as well as disease-specific characteristics. Conclusion: Methodological limitations hamper the accuracy of COVID-19-related mortality estimates for the main categories of SMIs. Nevertheless, evidence suggests that SMI is associated with excess COVID-19 mortality. Policy makers therefore must consider these vulnerable individuals as a high-risk group that should be given particular attention. This means that targeted interventions to maximize vaccination uptake among these patients are required to address the higher burden of COVID-19 infection in this already disadvantaged group.

Genetically Predicted Higher Educational Attainment Decreases the Risk of COVID-19 Susceptibility and Severity: A Mendelian Randomization Study

Background: Prior observational studies indicated that lower educational attainment (EA) is associated with higher COVID-19 risk, while these findings were vulnerable to bias from confounding factors. We aimed to clarify the causal effect of EA on COVID-19 susceptibility, hospitalization, and severity using Mendelian randomization (MR).

Methods: We identified genetic instruments for EA from a large genome-wide association study (GWAS) (n = 1,131,881). Summary statistics for COVID-19 susceptibility (112,612 cases and 2,474,079 controls), hospitalization (24,274 cases and 2,061,529 controls), and severity (8,779 cases and 1,001,875 controls) were obtained from the COVID-19 Host Genetics Initiative. We used the single-variable MR (SVMR) and the multivariable MR (MVMR) controlling intelligence, income, body mass index, vigorous physical activity, sedentary behavior, smoking, and alcohol consumption to estimate the total and direct effects of EA on COVID-19 outcomes. Inverse variance weighted was the primary analysis method. All the statistical analyses were performed using R software.

Results: Results from the SVMR showed that genetically predicted higher EA was correlated with a lower risk of COVID-19 susceptibility [odds ratio (OR) 0.86, 95% CI 0.84–0.89], hospitalization (OR 0.67, 95% CI 0.62–0.73), and severity (OR 0.67, 95% CI 0.58–0.79). EA still maintained its effects in most of the MVMR.

Conclusion: Educational attainment is a predictor for susceptibility, hospitalization, and severity of COVID-19 disease. Population with lower EA should be provided with a higher prioritization to public health resources to decrease the morbidity and mortality of COVID-19.

COVID-19 collateral damage-psychological burden and behavioural changes among older adults during the first outbreak in Stockholm, Sweden: a cross-sectional study

OBJECTIVES

To explore the indirect negative effects of COVID-19 restrictions (collateral damage) on the lives and health of older adults living in central Stockholm, and to characterise the sociodemographic profile of those with the highest susceptibility to this damage.

DESIGN

Cross-sectional study.

SETTING

District of Kungsholmen in Stockholm, Sweden.

PARTICIPANTS

Older adults aged 68 years and above (n=1231) who participated in the ad hoc COVID-19-related phone questionnaire administered by trained staff between May and June 2020 and who had previously attended the regular follow-up assessment of the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) during 2016-2019.

PRIMARY AND SECONDARY OUTCOME MEASURES

Three dimensions of collateral damage: psychological burden (feelings of worry, stress and loneliness), reductions in social and physical activities, and reductions in medical and social care use since the beginning of the pandemic. Logistic regression models were used to test the association between age, sex, education and living arrangement, and the risk of collateral damage.

RESULTS

Vast majority of participants adhered to the national public health recommendations, with over three-quarters practising self-isolation (n=928). Half of the sample reported psychological burden, 55.3% reported reductions in social or physical activity, and 11.3% reported decreased medical or social care use. Over three quarters of participants (77.8%) were affected by at least one of the three collateral damage dimensions. Female sex was the strongest sociodemographic predictor of both individual and co-occurring dimensions of collateral damage.

CONCLUSIONS

COVID-19 and its restrictions during the first half of 2020 had a negative effect on the health and lives of a majority of the elderly living in central Stockholm. Women were at a higher risk of these negative consequences. We emphasise the need for predefined, evidence-based interventions to support those who are most susceptible to these consequences, both during the pandemic and once the outbreak is overcome.

Essential metals, vitamins and antioxidant enzyme activities in COVID-19 patients and their potential associations with the disease severity

The role of micronutrient deficiency in the pathogenesis of COVID-19 has been reviewed in the literature; however, the data are limited and conflicting. This study investigated the association between the status of essential metals, vitamins, and antioxidant enzyme activities in COVID-19 patients and disease severity. We recruited 155 patients, who were grouped into four classes based on the Adults guideline for the Management of Coronavirus Disease 2019 at King Faisal Specialist & Research Centre (KFSH&RC): asymptomatic (N = 16), mild (N = 49), moderate (N = 68), and severe (N = 22). We measured serum levels of copper (Cu), zinc (Zn), selenium (Se), vitamin D₃, vitamin A, vitamin E, total antioxidant capacity, and superoxide dismutase (SOD). Among the patients, 30%, 25%, 37%, and 68% were deficient in Se (< 70.08 µg/L), Zn (< 0.693 µg/mL), vitamin A (< 0.343 µg/mL), and vitamin D₃ (< 20.05 µg/L), respectively, and SOD activity was low. Among the patients, 28% had elevated Cu levels (> 1.401 µg/mL, KFSH&RC upper reference limit). Multiple regression analysis revealed an 18% decrease in Se levels in patients with severe symptoms, which increased to 30% after adjusting the model for inflammatory markers. Regardless of inflammation, Se was independently associated with COVID-19 severity. In contrast, a 50% increase in Cu levels was associated with disease severity only after adjusting for C-reactive protein, reflecting its possible inflammatory and pro-oxidant role in COVID-19 pathogenesis. We noted an imbalance in the ratio between Cu and Zn, with ~ 83% of patients having a Cu/Zn ratio > 1, which is an indicator of inflammation. Cu-to-Zn ratio increased to 45% in patients with mild symptoms and 34%–36% in patients with moderate symptoms compared to asymptomatic patients. These relationships were only obtained when one of the laboratory parameters (lymphocyte or monocyte) or inflammatory markers (neutrophil-to-lymphocyte ratio) was included in the regression model. These findings suggest that Cu/Zn might further exacerbate inflammation in COVID-19 patients and might be synergistically associated with disease severity. A 23% decrease in vitamin A was seen in patients with severe symptoms, which disappeared after adjusting for inflammatory markers. This finding may highlight the potential role of inflammation in mediating the relationship between COVID-19 severity and vitamin A levels. Despite our patients’ low status of Zn, vitamin D₃, and antioxidant enzyme (SOD), there is no evidence of their role in COVID-19 progression. Our findings reinforce that deficiency or excess of certain micronutrients plays a role in the pathogenesis of COVID-19. More studies are required to support our results.

The Social and Natural Environment's Impact on SARS-CoV-2 Infections in the UK Biobank

COVID-19 has caused a global pandemic with considerable impact. Studies have examined the influence of socioeconomic status and air pollution on COVID-19 risk but in low detail. This study seeks to further elucidate the nuances of socioeconomic status, as defined by the Index of Multiple Deprivation (IMD), air pollution, and their relationship. We examined the effect of IMD and air pollution on the likelihood of testing positive for SARS-CoV-2 among 66,732 UKB participants tested for SARS-CoV-2 from 16 March 2020 through 16 March 2021. Logistic regression was performed controlling for age, sex, ancestry and IMD or air pollution in the respective models. IMD and its sub-scores were significantly associated with increased risk of testing positive for SARS-CoV-2. All particulate matter less than 2.5 μm (PM2.5), nitrogen oxide (NO_x), and nitrogen dioxide (NO₂) levels were associated with increased likelihood of testing positive for SARS-CoV-2. Measures of green space and natural environment around participants' homes were associated with reduced likelihood of SARS-CoV-2. Socioeconomic status and air pollution have independent effects on the risk of testing positive for SARS-CoV-2. Green space and natural environment space in the proximity of people's homes may mediate the effect of air pollution on the risk of testing positive for SARS-CoV-2.

Excess mortality according to group of causes in the first year of the COVID-19 pandemic in Brazil

ABSTRACT Objective: To estimate excess mortality by cause of death in Brazil and states in 2020. Methods: We estimated the expected number of deaths considering a linear trend analysis with the number of deaths between 2015 and 2019 for each group of causes and each federative unit. We calculated standardized mortality ratios (SMR) and 95% confidence intervals for each SMR assuming a Poisson distribution. We performed the analyses in the R program, version 4.1.3. Results: We observed a 19% excess in deaths in 2020 (SMR=1.19; 95%CI=1.18–1.20). The Infectious and Parasitic Diseases group stood out among the defined causes (SMR=4.80; 95%CI 4.78–4.82). The ill-defined causes showed great magnitude in this period (SMR=6.08; 95%CI 6.06–6.10). Some groups had lower-than-expected deaths: respiratory diseases (10% lower than expected) and external causes (4% lower than expected). In addition to the global analysis of the country, we identified significant heterogeneity among the federative units. States with the highest SMR are concentrated in the northern region, and those with the lowest SMR are concentrated in the southern and southeastern regions. Conclusion: Excess mortality occurs during the COVID-19 pandemic. This excess results not only from COVID-19 itself, but also from the social response and the management of the health system in responding to a myriad of causes that already had a trend pattern before it.

COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria

COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance data from all 37 States in Nigeria between February 27, 2020, and April 3, 2021. The outcome variable was mortality amongst persons who tested positive for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction. Incidence rates of COVID-19 mortality was calculated by dividing the number of deaths by total person-time (in days) contributed by the entire study population and presented per 100,000 person-days with 95% Confidence Intervals (95% CI). Adjusted negative binomial regression was used to identify factors associated with COVID-19 mortality. Findings are presented as adjusted Incidence Rate Ratios (aIRR) with 95% CI. The first wave included 65,790 COVID-19 patients, of whom 994 (1∙51%) died; the second wave included 91,089 patients, of whom 513 (0∙56%) died. The incidence rate of COVID-19 mortality was higher in the first wave [54∙25 (95% CI: 50∙98-57∙73)] than in the second wave [19∙19 (17∙60-20∙93)]. Factors independently associated with increased risk of COVID-19 mortality in both waves were: age ≥45 years, male gender [first wave aIRR 1∙65 (1∙35-2∙02) and second wave 1∙52 (1∙11-2∙06)], being symptomatic [aIRR 3∙17 (2∙59-3∙89) and 3∙04 (2∙20-4∙21)], and being hospitalised [aIRR 4∙19 (3∙26-5∙39) and 7∙84 (4∙90-12∙54)]. Relative to South-West, residency in the South-South and North-West was associated with an increased risk of COVID-19 mortality in both waves. In conclusion, the rate of COVID-19 mortality in Nigeria was higher in the first wave than in the second wave, suggesting an improvement in public health response and clinical care in the second wave. However, this needs to be interpreted with caution given the inherent limitations of the country's surveillance system during the study.

Seroepidemiological investigation of COVID-19: A cross-sectional study in Jundiai, São Paulo, Brazil

The dramatic increase in the number of COVID-19 cases has been a threat to global health and a challenge for health systems. Estimating the prevalence of infection in the population is essential to provide support for action planning. Within this scenario, the aim of the present study was to analyze the seroprevalence and associated factors of COVID-19 Jundiaí, São Paulo, Brazil. This cross-sectional study was conducted from June 1st to June 19th, 2020. The participants were patients with respiratory symptoms who sought Primary Care Units (UBS) (n = 1,181) and subjects recruited from randomly selected households by probability sampling (n = 3,065), as screening strategy. All participants, in both phases, were submitted to SARS-CoV-2 rapid antigen tests (IgG and IgM) and responded to a questionnaire including sociodemographic characteristics based on Behavioural Insights for COVID-19. Total seroprevalence (positive/negative) was the outcome and the independent variables were sociodemographic variables, health behavior and signs/symptoms. The chi-squared test was used for association analysis (p<0.05) and variables with p<0.20 were entered into the logistic regression model (p<0.05). A total of 1,181 subjects from the UBS and 3,065 from the selected households participated in the study. The seroprevalence was 30.8% in the UBS and 3.1% in the households. The adjusted logistic regression identified that lower educational level (OR 2.68; 95%CI 1.59-4.54), household member testing positive (OR 1.67; 95%CI 1.16-2.39), presence of anosmia (OR 3.68, 95%CI 2.56-5.28) and seeking UBS (OR 3.76; 95%CI 2.08-6.82) was risk factors to test positive for SARS-CoV-2. Estimating the seroprevalence in the population was important to know the disease extension that was higher than the notified cases. These results showed socioeconomic aspects associated with COVID-19 even adjusted by symptoms. Populational epidemiologic studies that investigate the associated factors of COVID-19 are relevant to plan strategies to control the pandemic.

Surveillance of COVID-19 outbreaks in prisons in the US South: The role of economic distress in the communities surrounding prison facilities

Introduction:

The US South is the epicenter of the epidemic of mass incarceration. Prisons have experienced substantial challenges in preventing COVID-19. Incarcerated individuals and prison staff are at a high risk for infection due to minimal available preventive measures. Prisons are not closed systems and many staff come from communities in close proximity to the facility. Characteristics of the communities immediately surrounding prisons are an overlooked but critical factor to better understand the role prisons play in pandemics.

Methods:

We used facility-level COVID-19 data from the COVID Prison Project to identify the number of unique outbreaks between May 2019 and May 2020. We used a county-level composite indicator of economic distress (DCI score) to identify the environment surrounding each prison (2015–2019). We modeled the number of outbreaks to DCI scores using negative binomial regression, adjusting for race/ethnicity (African American and Latino/Hispanic), age (65 and older), and rurality level.

Results:

Our sample included 570 prisons in 368 counties across 13 Southern states. We found that score was positively and significantly associated with prison COVID-19 outbreaks (aRR, 1.012; p < 0.0001), and rurality was potentially a stronger surrogate measure of economic distress (aRR, 1.35; p, 0.02). Economic stability is a key precursor to physical health. Poorer communities have been disproportionately impacted by the pandemic, and we found that prisons located in these communities were more susceptible to recurring outbreaks. Prison-based disease prevention interventions should consider the impact that the outside world has on the health of incarcerated individuals.

Excesso de mortalidade segundo grupo de causas no primeiro ano de pandemia de COVID-19 no Brasil

RESUMO Objetivo: Estimar o excesso de mortalidade segundo causa de óbito no Brasil e estados em 2020. Métodos: O número de óbitos esperado foi estimado considerando análise de tendência linear com o número de mortes entre os anos de 2015 e 2019, para cada grupo de causas e cada unidade da federação. Calculamos as razões de mortalidade padronizadas, e os intervalos com 95% de confiança para cada SMR foram calculados assumindo uma distribuição Poisson. As análises foram realizadas no programa R, versão 4.1.3. Resultados: Observamos um excesso de 19% nos óbitos em 2020 (SMR=1,19; IC=1,18–1,20). O grupo de Doenças Infecciosas e Parasitárias obteve maior destaque entre as causas definidas (SMR=4,80; IC95% 4,78–4,82). As causas mal definidas apresentaram grande magnitude neste período (SMR=6,08; IC95% 6,06–6,10). Há, ainda, grupos que apresentaram número de óbitos abaixo do esperado: doenças do aparelho respiratório (10% abaixo do esperado) e causas externas (4% abaixo do esperado). Além da análise global para o país, identificamos grande heterogeneidade entre as unidades da federação. Os estados com maiores SMR estão concentrados na região norte, e os que possuem menores SMR estão concentrados nas regiões sul e sudeste. Conclusões: Há um excesso de mortalidade ocorrendo durante a pandemia de COVID-19. Este excesso é resultado não apenas da COVID-19 em si, mas da resposta social e da gestão do sistema de saúde em responder a uma miríade de causas que já possuíam um ritmo de tendência anterior a ela.

Host Genetic Liability for Severe COVID-19 Associates with Alcohol Drinking Behavior and Diabetic Outcomes in Participants of European Descent

Risk factors and long-term consequences of COVID-19 infection are unclear but can be investigated with large-scale genomic data. To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N > 1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use (genetic causality proportion (gĉp) with severe respiratory COVID-19 = 0.576, p = 1.07 × 10⁻⁵ and hospitalized COVID-19 = 0.713, p = 0.003), and alcohol drinking status (gĉp with severe respiratory COVID-19 = 0.633, p = 7.04 × 10⁻⁵ and hospitalized COVID-19 = 0.848, p = 4.13 × 10⁻¹³). COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors and potential long-term health effects of severe response to infection.

An analysis of the COVID-19 vaccination campaigns in France, Israel, Italy and Spain and their impact on health and economic outcomes

Objectives

This paper presents an overview of the vaccination campaigns in France, Israel, Italy and Spain during the first eleven months from the first COVID-19 vaccine approval (Dec 2020 - Nov 2021). These four countries were chosen as they share similar socioeconomic, and epidemiological profiles and adopted similar vaccination strategies.

Methods

A rapid review of available primary data from each country was conducted. Data were collected from official government documents whenever possible, supplemented by information from international databases and local reports. The data were analysed via descriptive and graphical analysis to identify common patterns as well as significant divergences in the structural changes of countries’ healthcare systems during the pandemic, outcomes of the vaccination roll-out, and their impact on contextual policies.

Results

The four countries adopted similar interventions to protect and strengthen their healthcare systems. The effective coordination between the governance levels, ability to ensure a large supply of doses, and trust towards health authorities were amongst the determinants for more successful vaccination outcomes. The analysis reports a positive impact of the COVID-19 vaccines on epidemiological, political and economic outcomes. We observed some evidence of a negative association between increased vaccine coverage and fatalities and hospitalisation trends.

Conclusions

The strengths and weaknesses of COVID-19 pandemic crisis management along with the various strategies surrounding the vaccination roll-out campaigns may yield lessons for policymakers amidst such decisions, including for future pandemics.

Lay summary

This paper presents an overview of the vaccination campaigns in France, Israel, Italy and Spain during the first eleven months following approval of the first COVID-19 vaccine (Dec 2020 - Nov 2021). These four countries were chosen as they share similar demographic, socioeconomic, and epidemiological profiles, and adopted similar vaccinations strategies. Effective coordination between governance levels, ability to ensure a large supply of doses, and trust towards health authorities were amongst the determinants for successful outcomes of vaccination campaigns. The strengths and weaknesses of COVID-19 pandemic crisis management, along with the various strategies surrounding the vaccination roll-out campaigns may yield lessons for policymakers amidst such decisions, including for future pandemics.

Overweight and Obesity Are Associated With Acute Kidney Injury and Acute Respiratory Distress Syndrome, but Not With Increased Mortality in Hospitalized COVID-19 Patients: A Retrospective Cohort Study

Objective

To evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19.

Design

Retrospective, observational cohort study.

Methods

We performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes.

Results

Out of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients.

Conclusion

In this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.

Social Determinants of Health Correlating with Mechanical Ventilation of COVID-19 Patients: A Multi-Center Observational Study

Importance

Several studies have relayed the disproportionate impact of COVID-19 on marginalized communities; however, few have specifically examined the association between social determinants of health and mechanical ventilation (MV).

Objective

To determine which demographics impact MV rates among COVID-19 patients.

Design

This observational study included COVID-19 patient data from eight hospitals’ electronic medical records (EMR) between February 25, 2020, to December 31, 2020. Associations between demographic data and MV rates were evaluated using uni- and multivariate analyses.

Setting

Multicenter (eight hospitals), largest health system in Southeast Michigan.

Participants

Inpatients with a positive RT-PCR for SARS-CoV-2 on nasopharyngeal swab. Exclusion criteria were missing demographic data or non-permanent Michigan residents.

Exposure

Patients were divided into two groups: MV and non-MV.

Main Outcome and Measures

The primary outcome was MV rate per demographic. A multivariate model then predicted the odds of MV per demographic descriptor. Hypotheses were formulated prior to data collection.

Results

Among 11,304 COVID-19 inpatients investigated, 1621 (14.34%) were MV, and 49.96% were male with a mean age of 63.37 years (17.79). Significant social determinants for MV included Black race (40.19% MV vs 31.31% non-MV, p<0.01), poverty (14.60% vs. 13.21%, p<0.01), and disability (12.65% vs 9.14%; p<0.01). Black race (AOR 1.61 (CI 1.41–1.83; p<0.01)), median income (AOR 0.99 (CI 0.99–0.99; p<0.01)), disability (AOR 1.55 (CI 1.26, 1.90; p<0.01)), and non-English-speaking status (AOR 1.26 (CI 1.05, 1.53)) had significantly higher odds of MV.

Conclusions and Relevance

Black race, low socioeconomic status, disability, and non-English-speaking status were significant risk factors for MV from COVID-19. An urgent need remains for a pandemic response program that strategizes care for marginalized communities.

State and Trait Risk and Resilience Factors Associated with COVID-19 Impact and Obsessive-Compulsive Symptom Trajectories

The COVID-19 pandemic may exacerbate common symptoms of obsessive-compulsive disorder, such as fears of contamination or causing harm to others. To investigate the potential impact of COVID-19 on obsessive-compulsive (OC) symptoms, we utilized a frequent sampling prospective design to assess changes in OC symptoms between April 2020 and January 2021. We examined in a broad clinical and non-clinical sample whether baseline risk (e.g., emotion dysregulation, anxiety sensitivity, intolerance of uncertainty) and protective (e.g., resilience) factors would predict OC symptom changes, and whether coping strategies would mediate week-to-week changes in COVID-19 impact and OC symptoms. Emotion dysregulation was associated with greater likelihood of OC symptom worsening, whereas resilience was associated with lower likelihood. Longitudinal mediation analyses revealed that coping strategies were not significant mediators; however, changes in adaptive coping were associated with subsequent-week OC symptom reductions. Regardless of perceived COVID-19 impact, implementing adaptive coping strategies may prospectively reduce OC symptoms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41811-021-00128-4.

Prevalence of unwillingness and uncertainty to vaccinate against COVID-19 in older people: A systematic review and meta-analysis

The coronavirus disease 2019 (COVID-19) has been shown to have more severe health outcomes in older people specifically in relation to mortality and disability. Vaccination seems to be efficacious and safe for preventing the negative consequences of COVID-19, but vaccine hesitancy seems to be high in older adults. We therefore aimed to investigate the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in older people and the factors that can be associated with the unwillingness to vaccinate. For this work, we searched several databases until 18th June 2021 for studies reporting the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in people aged >60 years. A meta-analysis of the prevalence, with the correspondent 95% confidence intervals (CIs), was proposed. Factors that can be associated with the unwillingness to vaccinate against COVID-19 were explored through multivariable analyses and reported as odds ratios (ORs). Among 662 papers initially screened, we included 15 studies for a total of 9753 older adults. The prevalence of unwillingness to vaccinate against COVID-19 in older people was 27.03% (95%CI: 15.10-38.95%), whilst the correspondent figure of uncertainty was 19.33% (95%CI: 12.28-26.39). The risk of being unvaccinated was significantly higher in Hispanics (OR=1.197; 95%CI: 1.010-1.418) and in case of low education (OR=1.678; 95%CI: 1.170-2.408) and low income (OR=1.287; 95%CI: 1.127-1.469). In conclusion, the hesitancy for COVID-19 vaccination is a relevant problem in older people, particularly in those with a low income, a low level of education, and in Hispanics living in the United States.

Changes in social support of pregnant and postnatal mothers during the COVID-19 pandemic

OBJECTIVE

Our objectives were to assess in perinatal women: the most effective methods used to meet social support needs during COVID-19, the impact of COVID-19 on self-reported social support levels, and how perceived change in social support related to distress, depression, and mental health.

DESIGN

One-time survey administered from April to August 2020 SETTING: Online PARTICIPANTS: Pregnant and postpartum women with infants less than 6 months of age MEASUREMENT AND FINDINGS: Participants indicated the methods they used to meet social support needs during COVID-19. They self-rated their social support level pre- and during pandemic and their distress, depressive symptoms, and mental health changes on a Likert scale. Out of 1142 participants, the most effective methods for obtaining social support during the pandemic were virtual means (e.g. video call) and interaction with friends. There was a significant difference in distribution of self-reported levels of social support before and during the pandemic, with more respondents reporting a decrease in support. Decreases in social support were associated with higher distress levels, higher levels of depressive symptoms, and poorer mental health.

KEY CONCLUSIONS

Perinatal women reported decreased social support during the COVID-19 pandemic which was associated with poorer mental health. Using virtual means of social support and support provided by friends had the largest positive effect on perceived social support levels.

IMPLICATIONS FOR PRACTICE

Interventions using virtual support means from friends may be helpful to improve social support and mental health in this population.

Influences of climatic and non-climatic factors on COVID-19 outbreak: A review of existing literature

Coronavirus disease 2019 (COVID-19) has become a significant global public health issue resulting from SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). COVID-19 outbreak approaches an unprecedented challenge for human health, the economy, and societies. The transmission of the COVID-19 is influenced by many factors, including climatic, environmental, socioeconomic, and demographic. This study aimed to investigate the influences of climatic and sociodemographic determinants on COVID-19 transmission. The climatic variables considered herein were air temperature, relative humidity, wind speed, air pollution, and cumulative precipitation. Sociodemographic variables included population density, socioeconomic conditions, misinformation, and personal hygiene practices towards the pandemic. Review results indicated that lower temperatures and greater incidence of COVID-19 are reported in a more significant number of studies. Another factor linked to COVID-19 occurrence was the humidity. However, the results were varied; some research reported positive, and others reported negative relationships. In addition, poor air quality, along with strong winds, makes the virus more vulnerable to spreading, leading to a spike in COVID-19 cases. PM2.5, O3, and NO2 also showed a strong correlation with the recent epidemic. The findings on rainfall were inconsistent between studies. Among the non-climatic factors, population density, education, and income were credited as potential determinants for the coronavirus outbreak. Climatic and sociodemographic factors showed a significant correlation on the COVID-19 outbreak. Thus, our review emphasizes the critical importance of considering climatic and non-climatic factors while developing intervention measures. This study's core findings will support the decision-makers in identifying climatic and socioeconomic elements that influence the risks of future pandemics.

Local Characteristics Related to SARS-CoV-2 Transmissions in the Seoul Metropolitan Area, South Korea

The Seoul metropolitan area is one of the most populated metropolitan areas in the world; hence, Seoul's COVID-19 cases are highly concentrated. This study identified local demographic and socio-economic characteristics that affected SARS-CoV-2 transmission to provide locally targeted intervention policies. For the effective control of outbreaks, locally targeted intervention policies are required since the SARS-CoV-2 transmission process is heterogeneous over space. To identify the local COVID-19 characteristics, this study applied the geographically weighted lasso (GWL). GWL provides local regression coefficients, which were used to account for the spatial heterogeneity of SARS-CoV-2 outbreaks. In particular, the GWL pinpoints statistically significant regions with specific local characteristics. The applied explanatory variables involving demographic and socio-economic characteristics that were associated with higher SARS-CoV-2 transmission in the Seoul metropolitan area were as follows: young adults (19~34 years), older population, Christian population, foreign-born population, low-income households, and subway commuters. The COVID-19 case data were classified into three periods: the first period (from January 2020 to July 2021), the second period (from August to November 2020), and the third period (from December 2020 to February 2021), and the GWL was fitted for the entire period (from January 2020 to February 2021). The result showed that young adults, the Christian population, and subway commuters were the most significant local characteristics that influenced SARS-CoV-2 transmissions in the Seoul metropolitan area.

Comprehensive and long-term surveys of COVID-19 sequelae in Japan, an ambidirectional multicentre cohort study: study protocol

INTRODUCTION

The rapid spread of COVID-19 posed a global burden. Substantial number of people died of the disease in the acute phase of infection. In addition, a significant proportion of patients have been reported to suffer from post-acute phase symptoms, sequelae of COVID-19, which may negatively influence the quality of daily living and/or socioeconomic circumstances of the patients. However, no previous study has comprehensively and objectively assessed the quality of life of patients by using existing international scales. Further, evidence of socioeconomic consequences among patients with COVID-19 is scarce. To address the multidimensional issues from sequelae of COVID-19, evidence from comprehensive surveys beyond clinical perspectives is critical that investigates health, and social determinants of disease progression as well as socioeconomic consequences at a large scale.

METHODS AND ANALYSIS

In this study, we plan to conduct a nationwide and comprehensive survey for the sequelae of COVID-19 in a total of 1000 patients diagnosed at 27 hospitals throughout Japan. This study will evaluate not only the health-related status of patients from clinical perspectives but also the Health-related Quality of Life (HRQoL) scores, socioeconomic status and consequences to discuss the sequelae of the disease and the related risk factors. The primary endpoint is the frequency of long-term complications of COVID-19 infection. The secondary endpoints are risk factors for progression to sequelae of COVID-19 infection. The study will provide robust and important evidence as a resource to tackle the issues from the sequelae of COVID-19 from the multi-dimensional perspectives.

ETHICS AND DISSEMINATION

This trial was approved by the Keio University School of Medicine Ethics Committee (20200243, UMIN000042299). The results of this study will be reported at a society meeting or published in a peer-reviewed journal.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020190105.

COVID-19 and Historic Influenza Vaccinations in the United States: A Comparative Analysis

The COVID-19 vaccination effort is a monumental global challenge. Recognizing and addressing the causes of vaccine hesitancy will improve vaccine uptake. The primary objective of this study was to compare the COVID-19 vaccination rates in US counties to historical vaccination rates for influenza in persons aged 65 and older. The secondary objective was to identify county-level demographic, socioeconomic, and political factors that influence vaccination rates. County level data were obtained from publicly available databases for comparison and to create predictive models. Overall, in US counties the COVID-19 vaccination rate exceeded influenza vaccination rates amongst those aged 65 or older (69.4.0% vs. 44%, p < 0.0001). 2690 (83.4%) of 3224 counties had vaccinated 50% or more of their 65 and older residents in the first seven months of the COVID-19 vaccination roll out. There were 467 (14.5%) of 3223 counties in which the influenza vaccination rate exceeded the COVID-19 vaccination rate. Most of these counties were in the Southern region, were considered politically "red" and had a significantly higher non-Hispanic Black resident population (14.4% vs. 8.2%, p < 0.0001). Interventions intended to improve uptake should account for nuances in vaccine access, confidence, and consider factual social media messaging, especially in vulnerable counties.

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.

Disparities in telemedicine utilization among surgical patients during COVID-19

Background

Telemedicine has been rapidly adopted in the wake of the COVID-19 pandemic. There is limited work surrounding demographic and socioeconomic disparities that may exist in telemedicine utilization. This study aimed to examine demographic and socioeconomic differences in surgical patient telemedicine usage during the COVID-19 pandemic.

Methods

Department of Surgery outpatients seen from July 1, 2019 to May 31, 2020 were stratified into three visit groups: pre-COVID-19 in-person, COVID-19 in-person, or COVID-19 telemedicine. Generalized linear models were used to examine associations of sex, race/ethnicity, Distressed Communities Index (DCI) scores, MyChart activation, and insurance status with telemedicine usage during the COVID-19 pandemic.

Results

14,792 patients (median age 60, female [57.0%], non-Hispanic White [76.4%]) contributed to 21,980 visits. Compared to visits before the pandemic, telemedicine visits during COVID-19 were more likely to be with patients from the least socioeconomically distressed communities (OR, 1.31; 95% CI, 1.08,1.58; P = 0.005), with an activated MyChart (OR, 1.38; 95% CI, 1.17–1.64; P < .001), and with non-government or commercial insurance (OR, 2.33; 95% CI, 1.84–2.94; P < .001). Adjusted comparison of telemedicine visits to in person visits during COVID-19 revealed telemedicine users were more likely to be female (OR, 1.38, 95% CI, 1.10–1.73; P = 0.005) and pay with non-government or commercial insurance (OR, 2.77; 95% CI, 1.85–4.16; P < .001).

Conclusions

During the first three months of the COVID-19 pandemic, telemedicine was more likely utilized by female patients and those without government or commercial insurance compared to patients who used in-person visits. Interventions using telemedicine to improve health care access might consider such differences in utilization.

Impact of disruptions and recovery for established cervical screening programs across a range of high-income country program designs, using COVID-19 as an example: A modelled analysis

COVID-19 has disrupted cervical screening in several countries, due to a range of policy-, health-service and participant-related factors. Using three well-established models of cervical cancer natural history adapted to simulate screening across four countries, we compared the impact of a range of standardised screening disruption scenarios in four countries that vary in their cervical cancer prevention programs. All scenarios assumed a 6- or 12-month disruption followed by a rapid catch-up of missed screens. Cervical screening disruptions could increase cervical cancer cases by up to 5-6%. In all settings, more than 60% of the excess cancer burden due to disruptions are likely to have occurred in women aged less than 50 years in 2020, including settings where women in their 30s have previously been offered HPV vaccination. Approximately 15-30% of cancers predicted to result from disruptions could be prevented by maintaining colposcopy and precancer treatment services during any disruption period. Disruptions to primary screening had greater adverse effects in situations where women due to attend for screening in 2020 had cytology (vs. HPV) as their previous primary test. Rapid catch-up would dramatically increase demand for HPV tests in 2021, which it may not be feasible to meet because of competing demands on the testing machines and reagents due to COVID tests. These findings can inform future prioritisation strategies for catch-up that balance potential constraints on resourcing with clinical need.

Mapping the geodemographics of racial, economic, health, and COVID-19 deaths inequalities in the conterminous US

A large number of studies have examined individual-level factors that increase COVID-19 fatalities. However, no research has focused on the geodemographic classification of the most susceptible communities to COVID-19. In this cross-sectional ecological study, we used local fuzzy geographically-weighted clustering to create the socioeconomic profile of the US counties in relation to COVID-19 death rates. We demonstrate that living in a county which has households with lower income, people with a lack of health insurance, a high African-American percentage, and lower education level, lead to 27.12% higher COVID-19 death rates than the national median, and 72.56% higher compared to the least vulnerable counties. Compared to counties with a high COVID-19 death rate, counties with a low COVID-19 death rate have 44.90% higher annual median household income and nearly double house worth (89.51% more). Results show that the effects of the COVID-19 pandemic are not universal and that the minoritised and impoverished populations suffer more. Our analysis can effectively pinpoint the most vulnerable counties and importantly allows for understanding the socioeconomic context in which tailored interventions can be applied to mitigate COVID-19 deaths.

Cardiovascular and Renal Risk Factors and Complications Associated With COVID-19

The current COVID-19 pandemic, caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) virus, represents the largest medical challenge in decades. It has exposed unexpected cardiovascular vulnerabilities at all stages of the disease (pre-infection, acute phase, and subsequent chronic phase). The major cardiometabolic drivers identified as having epidemiologic and mechanistic associations with COVID-19 are abnormal adiposity, dysglycemia, dyslipidemia, and hypertension. Hypertension is of particular interest, because components of the renin-angiotensin system (RAS), which are critically involved in the pathophysiology of hypertension, are also implicated in COVID-19. Specifically, angiotensin-converting enzyme-2 (ACE2), a multifunctional protein of the RAS, which is part of the protective axis of the RAS, is also the receptor through which SARS-CoV-2 enters host cells, causing viral infection. Cardiovascular and cardiometabolic comorbidities not only predispose people to COVID-19, but also are complications of SARS-CoV-2 infection. In addition, increasing evidence indicates that acute kidney injury is common in COVID-19, occurs early and in temporal association with respiratory failure, and is associated with poor prognosis, especially in the presence of cardiovascular risk factors. Here, we discuss cardiovascular and kidney disease in the context of COVID-19 and provide recent advances on putative pathophysiological mechanisms linking cardiovascular disease and COVID-19, focusing on the RAS and ACE2, as well as the immune system and inflammation. We provide up-to-date information on the relationships among hypertension, diabetes, and COVID-19 and emphasize the major cardiovascular diseases associated with COVID-19. We also briefly discuss emerging cardiovascular complications associated with long COVID-19, notably postural tachycardia syndrome (POTS).

From swab testing to health outcomes within the T2DM population: Impact of diabetes background on COVID19 progression

BACKGROUND

We aimed to study the impact of diabetes background on COVID-19 progression from swab testing to health outcomes in type 2 diabetes (T2DM).

METHODS

From the database of the diabetes units of Piedmont-Italy we extracted records of T2DM patients, which were linked with the swab-testing-database, and the database of hospital discharges. Five outcomes (PCR testing, PCR testing positivity, hospitalization, Intensive Care Unit (ICU), death) were evaluated using robust Poisson models.

RESULTS

Among 125,021 T2DM patients, 1882 had a positive PCR test. Of these patients, 49.4% were hospitalized within 30 days, 11.8% were admitted to an ICU, and 27.1% died. Greater probability of death was associated with age, male sex, liver and renal impairment, Hba1c above 8%, and former smoking. Hospitalization and ICU admission were mainly affected by age, male sex, hypertension, and metabolic control. Notably, ICU admissions were reduced in very elderly people. No outcomes were associated with educational level.

CONCLUSIONS

Hospitalization and ICU admission are heavily affected by age and local triage policy. A key finding was that men who were > 75 years old and poorly compensated were highly vulnerable patients. Renal and/or hepatic impairment are additional factors. This information may be useful for addressing intervention priorities.

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA

This research aimed to quantify the racial disparities of COVID-19 for primarily positive tests and deaths across the US and territories individually and collectively. The first research hypothesis investigated whether positive cases and death rates were higher for people of color (POC) than the White ethnic group. The second hypothesis examined whether there is a significant difference in confirmed positive cases and death rates between ethnic groups across the US and territories. The third hypothesis investigated if political party control and governmental policies affected the number of cases and death proportion rates across ethnic groups. The research findings suggest that POC positive cases and death rates were higher in some states. Black ethnic groups were dying at a high rate in the southeastern states, the District of Columbia, and in Maryland. Specifically, in the District of Columbia, the death rate is five times higher than the White ethnic group. For Latinx ethnic groups, the high cases and death rates have mostly occurred in western states, including Texas. The Latinx ethnic group accounted for half the total deaths in Texas and California. The Latinx ethnic group death rate is higher than the White ethnic group in four states: Texas, California, New Mexico, and the District of Columbia. The research findings also show that the rate of deaths and cases per ethnic group for policies and political factors were significant except for the mask mandate policy. Based on the analyzed data, mask mandates were not a factor in the cases or death rates of any ethnic group. Each state's policies for bars, curfews, public schools, and travel-along with legislative party control-had the most influences across ethnic groups. The research results for the death rates and number of cases due to these implemented policies varied between ethnic groups.

Risk factors for Covid-19 in India

Like many developing countries, India was devastated by the raging pandemic of Covid 19. With the active involvement of the government and the community, the disaster was fought with. However, the impact was uneven across the country. The present study aimed to identify the factors responsible for variation in case burden of Covid-19. Data on demographic factors and co-morbidities were obtained from different sources available in the public domain. Descriptive statistics were used for comparison between states. A total of 30 states were taken into account. Correlation was used to find out association between different factors and the burden of Covid-19. Data on Covid were collected till 9th May, 2021. The burden of Covid-19 was strongly related to the literacy status and economy of the state (r = 0.574 and 0.730, respectively). The burden of self-reported hypertension and diabetes was also statistically linked to the burden of Covid-19 (r = 0.539 and 0.721, respectively). Overweight and obesity were also associated with the burden of Covid-19 (r = 0.614 and 0.561, respectively). Therefore, in areas with a high proportion of patients with co-morbidities, limited resources may be mobilized for a better outcome. As the states with poor literacy and health condition suffered the most. Tailored intervention is wanted to reach the poor and vulnerable.

Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina

Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal-geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial error model (SEM), spatial lag model (SLM), and conditional autoregressive model (CAR) as global models and the geographically weighted regression model (GWR) as a local model. The data were retrieved from multiple sources including USAFacts, U.S. Census Bureau, and the Population Estimates Program. The percentage of males and the unemployed population were positively associated with geodistributions of COVID-19 infection (p values < 0.05) in global models throughout the time. The percentage of the white population and the obesity rate showed divergent spatial correlations at different times of the pandemic. GWR models fit better than global models, suggesting nonstationary correlations between a region and its neighbors. Characterized by temporal-geospatial patterns, disparities in COVID-19 infection rate and their PIDRs are different from the mortality and morbidity of COVID-19 patients. Our findings suggest the importance of prioritizing different populations and developing tailored interventions at different times of the pandemic.

Geographic and Socioeconomic Disparities in Major Lower Extremity Amputation Rates in Metropolitan Areas

Background Rates of major lower extremity amputation in patients with peripheral artery disease are higher in rural communities with markers of low socioeconomic status, but most Americans live in metropolitan areas. Whether amputation rates vary within US metropolitan areas is unclear, as are characteristics of high amputation rate urban communities. Methods and Results We estimated rates of major lower extremity amputation per 100 000 Medicare beneficiaries between 2010 and 2018 at the ZIP code level among ZIP codes with ≥100 beneficiaries. We described demographic characteristics of high and low amputation ZIP codes, and the association between major amputation rate and 3 ZIP code-level markers of socioeconomic status-the proportion of patients with dual eligibility for Medicaid, median household income, and Distressed Communities Index score-for metropolitan, micropolitan, and rural ZIP code cohorts. Between 2010 and 2018, 188 995 Medicare fee-for-service patients living in 31 391 ZIP codes with ≥100 beneficiaries had a major lower extremity amputation. The median (interquartile range) ZIP code-level number of amputations per 100 000 beneficiaries was 262 (75-469). Though nonmetropolitan ZIP codes had higher rates of major amputation than metropolitan areas, 78.2% of patients undergoing major amputation lived in metropolitan areas. Compared with ZIP codes with lower amputation rates, top quartile amputation rate ZIP codes had a greater proportion of Black residents (4.4% versus 17.5%, P<0.001). In metropolitan areas, after adjusting for clinical comorbidities and demographics, every $10 000 lower median household income was associated with a 4.4% (95% CI, 3.9-4.8) higher amputation rate, and a 10-point higher Distressed Communities Index score was associated with a 3.8% (95% CI, 3.4%-4.2%) higher amputation rate; there was no association between the proportion of patients eligible for Medicaid and amputation rate. These findings were comparable to the associations identified across all ZIP codes. Conclusions In metropolitan areas, where most individuals undergoing lower extremity amputation live, markers of lower socioeconomic status and Black race were associated with higher rates of major lower extremity amputation. Development of community-based tools for peripheral artery disease diagnosis and management targeted to communities with high amputation rates in urban areas may help reduce inequities in peripheral artery disease outcomes.

Pre-Vaccine Positivity of SARS-CoV-2 Antibodies in Alberta, Canada during the First Two Waves of the COVID-19 Pandemic

We systematically evaluated SARS-CoV-2 IgG positivity in a provincial cohort to understand the local epidemiology of COVID-19 and support evidence-based public health decisions. Residual blood samples were collected for serology testing over 5-day periods monthly from June 2020 to January 2021 from six clinical laboratories across the province of Alberta, Canada. A total of 93,993 individual patient samples were tested with a SARS-CoV-2 nucleocapsid antibody assay with positives confirmed using a spike antibody assay. Population-adjusted SARS-CoV-2 IgG seropositivity was 0.92% (95% confidence interval [CI]: 0.91 to 0.93%) shortly after the first COVID-19 wave in June 2020, increasing to 4.63% (95% CI: 4.61 to 4.65%) amid the second wave in January 2021. There was no significant difference in seropositivity between males and females (1.39% versus 1.27%; P = 0.11). Ages with highest seropositivity were 0 to 9 years (2.71%, 95% CI: 1.64 to 3.78%) followed by 20 to 29 years (1.58%, 95% CI: 1.12 to 2.04%), with the lowest rates seen in those aged 70 to 79 (0.79%, 95% CI: 0.65 to 0.93%) and >80 (0.78%, 95% CI: 0.60 to 0.97%). Compared to the seronegative group, seropositive patients inhabited geographic areas with lower household income ($87,500 versus $97,500; P < 0.001), larger household sizes, and higher proportions of people with education levels of secondary school or lower, as well as immigrants and visible minority groups (all P < 0.05). A total of 53.7% of seropositive individuals were potentially undetected cases with no prior positive COVID-19 nucleic acid test (NAAT). Antibodies were detectable in some patients up to 9 months post positive NAAT result. This seroprevalence study will continue to inform public health decisions by identifying at-risk demographics and geographical areas. IMPORTANCE Using SARS-CoV-2 serology testing, we assessed the proportion of people in Alberta, Canada (population 4.4 million) positive for COVID-19 antibodies, indicating previous infection, during the first two waves of the COVID-19 pandemic (prior to vaccination programs). Linking these results with sociodemographic population data provides valuable information as to which groups of the population are more likely to have been infected with the SARS-CoV-2 virus to help facilitate public health decision-making and interventions. We also compared seropositivity data with previous COVID-19 molecular testing results. Absence of antibody and molecular testing were highly correlated (95% negative concordance). Positive antibody correlation with a previous positive molecular test was low, suggesting the possibility of mild/asymptomatic infection or other reasons leading individuals from seeking medical attention. Our data highlight that the true estimate of population prevalence of COVID-19 is likely best informed by combining data from both serology and molecular testing.