Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform

The prevalence of common mental disorders across 18 ethnic groups in Britain during the COVID-19 pandemic: Evidence for Equality National Survey (EVENS)

BACKGROUND

The COVID-19 pandemic negatively impacted mental health in the general population in Britain. Ethnic minority people suffered disproportionately, in terms of health and economic outcomes, which may contribute to poorer mental health. We compare the prevalence of depression and anxiety across 18 ethnic groups in Britain during the COVID-19 pandemic.

METHODS

Secondary analysis of cross-sectional data (February-November 2021) from 12,161 participants aged 18-60 years old (N with data on outcomes = 11,540 for depression & 11,825 for anxiety), obtained from the Evidence for Equality National Survey (EVENS). Data were weighted to account for selection bias and coverage bias. Weighted regression models examined ethnic differences in depression (Centre for Epidemiologic Studies Depression Scale) and anxiety (Generalised Anxiety Disorder-7). Effect modification analyses explored whether ethnic differences in outcomes were consistent within age and sex sub-groups.

RESULTS

Compared to White British people, greater odds of anxiety caseness (and greater anxiety symptoms) were observed for Arab (OR = 2.57; 95 % CI = 1.35-4.91), Mixed White and Black Caribbean (1.57; 1.07-2.30), any other Black (2.22, 1.28-3.87) and any other Mixed (1.58; 1.08-2.31) ethnic groups. Lower odds of depression caseness (and lower depressive symptoms) were identified for Chinese (0.63; 0.46-0.85), Black African (0.60; 0.46-0.79), and any other Asian (0.55; 0.42-0.72) ethnic groups.

LIMITATIONS

Cross-sectional data limits the opportunity to identify changes in ethnic inequalities in mental health over time.

CONCLUSIONS

We have identified certain ethnic groups who may require more targeted mental health support to ensure equitable recovery post-pandemic. Despite finding lower levels of depression for some ethnic groups, approximately one third of people within each ethnic group met criteria for depression.

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: An observational cohort study using the OpenSAFELY platform

BACKGROUND

Obesity and rapid weight gain are established risk factors for noncommunicable diseases and have emerged as independent risk factors for severe disease following Coronavirus Disease 2019 (COVID-19) infection. Restrictions imposed to reduce COVID-19 transmission resulted in profound societal changes that impacted many health behaviours, including physical activity and nutrition, associated with rate of weight gain. We investigated which clinical and sociodemographic characteristics were associated with rapid weight gain and the greatest acceleration in rate of weight gain during the pandemic among adults registered with an English National Health Service (NHS) general practitioner (GP) during the COVID-19 pandemic.

METHODS AND FINDINGS

With the approval of NHS England, we used the OpenSAFELY platform inside TPP to conduct an observational cohort study of routinely collected electronic healthcare records. We investigated changes in body mass index (BMI) values recorded in English primary care between March 2015 and March 2022. We extracted data on 17,742,365 adults aged 18 to 90 years old (50.1% female, 76.1% white British) registered with an English primary care practice. We estimated individual rates of weight gain before (δ-prepandemic) and during (δ-pandemic) the pandemic and identified individuals with rapid weight gain (>0.5 kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period (δ-change = δ-pandemic-δ-prepandemic) and defined extreme accelerators as the 10% of individuals with the greatest increase in their rate of weight gain (δ-change ≥1.84 kg/m2/year) between these periods. We estimated associations with these outcomes using multivariable logistic regression adjusted for age, sex, index of multiple deprivation (IMD), and ethnicity. P-values were generated in regression models. The median BMI of our study population was 27.8 kg/m2, interquartile range (IQR) [24.3, 32.1] in 2019 (March 2019 to February 2020) and 28.0 kg/m2, IQR [24.4, 32.6] in 2021. Rapid pandemic weight gain was associated with sex, age, and IMD. Male sex (male versus female: adjusted odds ratio (aOR) 0.76, 95% confidence interval (95% CI) [0.76, 0.76], p < 0.001), older age (e.g., 50 to 59 years versus 18 to 29 years: aOR 0.60, 95% CI [0.60, 0.61], p < 0.001]); and living in less deprived areas (least-deprived-IMD-quintile versus most-deprived: aOR 0.77, 95% CI [0.77, 0.78] p < 0.001) reduced the odds of rapid weight gain. Compared to white British individuals, all other ethnicities had lower odds of rapid pandemic weight gain (e.g., Indian versus white British: aOR 0.69, 95% CI [0.68, 0.70], p < 0.001). Long-term conditions (LTCs) increased the odds, with mental health conditions having the greatest effect (e.g., depression (aOR 1.18, 95% CI [1.17, 1.18], p < 0.001)). Similar characteristics increased odds of extreme acceleration in the rate of weight gain between the prepandemic and pandemic periods. However, changes in healthcare activity during the pandemic may have introduced new bias to the data.

CONCLUSIONS

We found female sex, younger age, deprivation, white British ethnicity, and mental health conditions were associated with rapid pandemic weight gain and extreme acceleration in rate of weight gain between the prepandemic and pandemic periods. Our findings highlight the need to incorporate sociodemographic, physical, and mental health characteristics when formulating research, policies, and interventions targeting BMI in the period of post pandemic service restoration and in future pandemic planning.

Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics

The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.

The impact of social cohesion and risk communication on excess mortality due to COVID-19 in 213 countries: a retrospective analysis

BACKGROUND

Tools for assessing a country's capacity in the face of public health emergencies must be reviewed, as they were not predictive of the COVID-19 pandemic. Social cohesion and risk communication, which are related to trust in government and trust in others, may have influenced adherence to government measures and mortality rates due to COVID-19.

OBJECTIVE

To analyse the association between indicators of social cohesion and risk communication and COVID-19 outcomes in 213 countries.

RESULTS

Social cohesion and risk communication, in their dimensions (public trust in politicians, trust in others, social safety nets, and equal distribution of resources index), were associated with lower excess mortality due to COVID-19. The number of COVID-19-related disorder events and government transparency were associated with higher excess mortality due to COVID-19. The lower the percentage of unemployed people, the higher the excess mortality due to COVID-19. Most of the social cohesion and risk communication variables were associated with better vaccination indicators, except for social capital and engaged society, which had no statistically significant association. The greater the gender equality, the better the vaccination indicators, such as the number of people who received all doses.

CONCLUSION

Public trust in politicians, trust in others, equal distribution of resources and government that cares about the most vulnerable, starting with the implementation of programs, such as cash transfers and combating food insecurity, were factors that reduced the excess mortality due to COVID-19. Countries, especially those with limited resources and marked by social, economic, and health inequalities, must invest in strengthening social cohesion and risk communication, which are robust strategies to better cope with future pandemics.

A Bayesian spatio-temporal model of COVID-19 spread in England

Exploring the spatio-temporal variations of COVID-19 transmission and its potential determinants could provide a deeper understanding of the dynamics of disease spread. This study aimed to investigate the spatio-temporal spread of COVID-19 infections in England, and examine its associations with socioeconomic, demographic and environmental risk factors. We obtained weekly reported COVID-19 cases from 7 March 2020 to 26 March 2022 at Middle Layer Super Output Area (MSOA) level in mainland England from publicly available datasets. With these data, we conducted an ecological study to predict the COVID-19 infection risk and identify its associations with socioeconomic, demographic and environmental risk factors using a Bayesian hierarchical spatio-temporal model. The Bayesian model outperformed the ordinary least squares model and geographically weighted regression model in terms of prediction accuracy. The spread of COVID-19 infections over space and time was heterogeneous. Hotspots of infection risk exhibited inconsistent clustering patterns over time. Risk factors found to be positively associated with COVID-19 infection risk were: annual household income [relative risk (RR) = 1.0008, 95% Credible Interval (CI) 1.0005-1.0012], unemployment rate [RR = 1.0027, 95% CI 1.0024-1.0030], population density on the log scale [RR = 1.0146, 95% CI 1.0129-1.0164], percentage of Caribbean population [RR = 1.0022, 95% CI 1.0009-1.0036], percentage of adults aged 45-64 years old [RR = 1.0031, 95% CI 1.0024-1.0039], and particulate matter ( PM 2.5 ) concentrations [RR = 1.0126, 95% CI 1.0083-1.0167]. The study highlights the importance of considering socioeconomic, demographic, and environmental factors in analysing the spatio-temporal variations of COVID-19 infections in England. The findings could assist policymakers in developing tailored public health interventions at a localised level.

The impact of health inequity on spatial variation of COVID-19 transmission in England

Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative areas of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative areas of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We incorporate the impact of acquired immunity, of spatial exportation of cases, and 16 spatially-varying socio-economic, socio-demographic, health, and mobility variables. Model comparison assesses the relative contributions of these respective mechanisms. We find that spatially-varying and time-varying differences in week-to-week transmission were definitively associated with differences in: time spent at home, variant-of-concern proportion, and adult social care funding. However, model comparison demonstrates that the impact of these terms is negligible compared to the role of spatial exportation between administrative areas. While these results confirm the impact of some, but not all, static measures of spatially-varying inequity in England, our work corroborates the finding that observed differences in disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than aggregated metrics of demography and health inequity between areas. Further work is required to assess how health inequity more broadly contributes to these epidemiological factors.

Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

Regional variation of COVID-19 admissions, acute kidney injury and mortality in England - a national observational study using administrative data

BACKGROUND

This study explores regional variations in COVID-19 hospitalization rates, in-hospital mortality, and acute kidney injury (AKI) in England. We investigated the influence of population demographic characteristics, viral strain changes, and therapeutic advances on clinical outcomes.

METHODS

Using hospital episode statistics, we conducted a retrospective cohort study with 749,844 admissions in 337,029 adult patients with laboratory-confirmed COVID-19 infection (March 1, 2020, to March 31, 2021). Multivariable logistic regression identified factors predicting AKI and mortality in COVID-19 hospitalized patients.

RESULTS

London had the highest number of COVID-19 admissions (131,338, 18%), followed by the North-west region (122,683, 16%). The North-west had the highest population incidence of COVID-19 hospital admissions (21,167 per million population, pmp), while the South-west had the lowest (9,292 admissions pmp). Patients in London were relatively younger (67.0 ± 17.7 years) than those in the East of England (72.2 ± 16.8 years). The shortest length of stay was in the North-east (12.2 ± 14.9 days), while the longest was in the North-west (15.2 ± 17.9 days). All eight regions had higher odds of death compared to London, ranging from OR 1.04 (95% CI 1.00, 1.07) in the South-west to OR 1.24 (95% CI 1.21, 1.28) in the North-west. Older age, Asian ethnicity, emergency admission, transfers from other hospitals, AKI presence, ITU admission, social deprivation, and comorbidity were associated with higher odds of death. AKI incidence was 30.3%, and all regions had lower odds of developing AKI compared to London. Increasing age, mixed and black ethnicity, emergency admission, transfers from other providers, ITU care, and different levels of comorbidity were associated with higher odds of developing AKI.

CONCLUSIONS

London exhibited higher hospital admission numbers and AKI incidence, but lower odds of death compared to other regions in England.

TRIAL REGISTRATION

Registered on National Library of Medicine website ( www.

CLINICALTRIALS

gov ) with registration number NCT04579562 on 8/10/2020.

Socioeconomic and Demographic Risk Factors for SARS-CoV-2 Seropositivity Among Healthcare Workers in a UK Hospital: A Prospective Cohort Study

BACKGROUND

To protect healthcare workers (HCWs) from the consequences of disease due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is necessary to understand the risk factors that drive exposure and infection within hospitals. Insufficient consideration of key socioeconomic variables is a limitation of existing studies that can lead to bias and residual confounding of proposed risk factors for infection.

METHODS

The Co-STARs study prospectively enrolled 3679 HCWs between April 2020 and September 2020. We used multivariate logistic regression to comprehensively characterize the demographic, occupational, socioeconomic, and environmental risk factors for SARS-CoV-2 seropositivity.

RESULTS

After adjusting for key confounders, relative household overcrowding (odds ratio [OR], 1.4 [95% confidence interval {CI}, 1.1-1.9]; P = .006), Black, Black British, Caribbean, or African ethnicity (OR, 1.7 [95% CI, 1.2-2.3]; P = .003), increasing age (ages 50-60 years: OR, 1.8 [95% CI, 1.3-2.4]; P < .001), lack of access to sick pay (OR, 1.8 [95% CI, 1.3-2.4]; P < .001).

CONCLUSIONS

Socioeconomic and demographic factors outside the hospital were the main drivers of infection and exposure to SARS-CoV-2 during the first wave of the pandemic in an urban pediatric referral hospital. Overcrowding and out-of-hospital SARS-CoV-2 contact are less amenable to intervention. However, lack of access to sick pay among externally contracted staff is more easily rectifiable. Our findings suggest that providing easier access to sick pay would lead to a decrease in SARS-CoV-2 transmission and potentially that of other infectious diseases in hospital settings.

CLINICAL TRIALS REGISTRATION

NCT04380896.

One size doesn't fit all: methodological reflections in conducting community-based behavioural science research to tailor COVID-19 vaccination initiatives for public health priority populations

BACKGROUND

Promoting the uptake of vaccination for infectious diseases such as COVID-19 remains a global challenge, necessitating collaborative efforts between public health units (PHUs) and communities. Applied behavioural science can play a crucial role in supporting PHUs' response by providing insights into human behaviour and informing tailored strategies to enhance vaccination uptake. Community engagement can help broaden the reach of behavioural science research by involving a more diverse range of populations and ensuring that strategies better represent the needs of specific communities. We developed and applied an approach to conducting community-based behavioural science research with ethnically and socioeconomically diverse populations to guide PHUs in tailoring their strategies to promote COVID-19 vaccination. This paper presents the community engagement methodology and the lessons learned in applying the methodology.

METHODS

The community engagement methodology was developed based on integrated knowledge translation (iKT) and community-based participatory research (CBPR) principles. The study involved collaboration with PHUs and local communities in Ontario, Canada to identify priority groups for COVID-19 vaccination, understand factors influencing vaccine uptake and co-design strategies tailored to each community to promote vaccination. Community engagement was conducted across three large urban regions with individuals from Eastern European communities, African, Black, and Caribbean communities and low socioeconomic neighbourhoods.

RESULTS

We developed and applied a seven-step methodology for conducting community-based behavioural science research: (1) aligning goals with system-level partners; (2) engaging with PHUs to understand priorities; (3) understanding community strengths and dynamics; (4) building relationships with each community; (5) establishing partnerships (community advisory groups); (6) involving community members in the research process; and (7) feeding back and interpreting research findings. Research partnerships were successfully established with members of prioritized communities, enabling recruitment of participants for theory-informed behavioural science interviews, interpretation of findings, and co-design of targeted recommendations for each PHU to improve COVID-19 vaccination uptake. Lessons learned include the importance of cultural sensitivity and awareness of sociopolitical context in tailoring community engagement, being agile to address the diverse and evolving priorities of PHUs, and building trust to achieve effective community engagement.

CONCLUSION

Effective community engagement in behavioural science research can lead to more inclusive and representative research. The community engagement approach developed and applied in this study acknowledges the diversity of communities, recognizes the central role of PHUs, and can help in addressing complex public health challenges.

Long-Term Autoimmune Inflammatory Rheumatic Outcomes of COVID-19 : A Binational Cohort Study

BACKGROUND

Some data suggest a higher incidence of diagnosis of autoimmune inflammatory rheumatic diseases (AIRDs) among patients with a history of COVID-19 compared with uninfected patients. However, these studies had methodological shortcomings.

OBJECTIVE

To investigate the effect of COVID-19 on long-term risk for incident AIRD over various follow-up periods.

DESIGN

Binational, longitudinal, propensity-matched cohort study.

SETTING

Nationwide claims-based databases in South Korea (K-COV-N cohort) and Japan (JMDC cohort).

PARTICIPANTS

10 027 506 Korean and 12 218 680 Japanese patients aged 20 years or older, including those with COVID-19 between 1 January 2020 and 31 December 2021, matched to patients with influenza infection and to uninfected control patients.

MEASUREMENTS

The primary outcome was onset of AIRD (per appropriate codes from the International Classification of Diseases, 10th Revision) 1, 6, and 12 months after COVID-19 or influenza infection or the respective matched index date of uninfected control patients.

RESULTS

Between 2020 and 2021, among the 10 027 506 Korean participants (mean age, 48.4 years [SD, 13.4]; 50.1% men), 394 274 (3.9%) and 98 596 (0.98%) had a history of COVID-19 or influenza, respectively. After propensity score matching, beyond the first 30 days after infection, patients with COVID-19 were at increased risk for incident AIRD compared with uninfected patients (adjusted hazard ratio, 1.25 [95% CI, 1.18 to 1.31]) and influenza-infected control patients (adjusted hazard ratio, 1.30 [CI, 1.02 to 1.59]). The risk for incident AIRD was higher with more severe acute COVID-19. Similar patterns were observed in the Japanese cohort.

LIMITATIONS

Referral bias due to the pandemic; residual confounding.

CONCLUSION

SARS-CoV-2 infection was associated with increased risk for incident AIRD compared with matched patients without SARS-CoV-2 infection or with influenza infection. The risk for incident AIRD was higher with greater severity of acute COVID-19.

PRIMARY FUNDING SOURCE

National Research Foundation of Korea.

Visible minority status and occupation were associated with increased COVID-19 infection in Greater Vancouver British Columbia between June and November 2020: an ecological study

Background

The COVID-19 pandemic has highlighted health disparities, especially among specific population groups. This study examines the spatial relationship between the proportion of visible minorities (VM), occupation types and COVID-19 infection in the Greater Vancouver region of British Columbia, Canada.

Methods

Provincial COVID-19 case data between June 24, 2020, and November 7, 2020, were aggregated by census dissemination area and linked with sociodemographic data from the Canadian 2016 census. Bayesian spatial Poisson regression models were used to examine the association between proportion of visible minorities, occupation types and COVID-19 infection. Models were adjusted for COVID-19 testing rates and other sociodemographic factors. Relative risk (RR) and 95% Credible Intervals (95% CrI) were calculated.

Results

We found an inverse relationship between the proportion of the Chinese population and risk of COVID-19 infection (RR = 0.98 95% CrI = 0.96, 0.99), whereas an increased risk was observed for the proportions of the South Asian group (RR = 1.10, 95% CrI = 1.08, 1.12), and Other Visible Minority group (RR = 1.06, 95% CrI = 1.04, 1.08). Similarly, a higher proportion of frontline workers (RR = 1.05, 95% CrI = 1.04, 1.07) was associated with higher infection risk compared to non-frontline.

Conclusion

Despite adjustments for testing, housing, occupation, and other social economic status variables, there is still a substantial association between the proportion of visible minorities, occupation types, and the risk of acquiring COVID-19 infection in British Columbia. This ecological analysis highlights the existing disparities in the burden of diseases among different visible minority populations and occupation types.

Anti-racist interventions to reduce ethnic disparities in healthcare in the UK: an umbrella review and findings from healthcare, education and criminal justice

OBJECTIVES

To assess the evidence for anti-racist interventions which aim to reduce ethnic disparities in healthcare, with a focus on implementation in the UK healthcare system.

DESIGN

Umbrella review.

DATA SOURCES

Embase, Medline, Social Policy and Practice, Social Care Online and Web of Science were searched for publications from the year 2000 up to November 2023.

ELIGIBILITY CRITERIA

Only systematic and scoping reviews of anti-racist interventions reported in English were included. Reviews were excluded if no interventions were reported, no comparator interventions were reported or the study was primarily descriptive.

DATA EXTRACTION AND SYNTHESIS

A narrative synthesis approach was used to integrate and categorise the evidence on anti-racist interventions for healthcare. Quality appraisal (including risk of bias) was assessed using the AMSTAR-2 tool.

RESULTS

A total of 29 reviews are included in the final review. 26 are from the healthcare sector and three are from education and criminal justice. The most promising interventions targeting individuals include group-based health education and providing culturally tailored interventions. On a community level, participation in all aspects of care pathway development that empowers ethnic minority communities may provide an effective approach to reducing ethnic health disparities. Interventions to improve quality of care for conditions with disproportionately worse outcomes in ethnic minority communities show promise. At a policy level, structural interventions including minimum wage policies and integrating non-medical interventions such as housing support in clinical care has some evidence for improving outcomes in ethnic minority communities.

CONCLUSIONS

Many of the included studies were low or critically low quality due to methodological or reporting limitations. For programme delivery, different types of pathway integration, and providing a more person-centred approach with fewer steps for patients to navigate can contribute to reducing disparities. For organisations, there is an overemphasis on individual behaviour change and recommendations should include a shift in focus and resources to policies and practices that seek to dismantle institutional and systemic racism through a multilevel approach.

The incidence of COVID-19-related hospitalisation in migrants in the UK: Findings from the Virus Watch prospective community cohort study

Background

Migrants in the United Kingdom (UK) may be at higher risk of SARS-CoV-2 exposure; however, little is known about their risk of COVID-19-related hospitalisation during waves 1-3 of the pandemic.

Methods

We analysed secondary care data linked to Virus Watch study data for adults and estimated COVID-19-related hospitalisation incidence rates by migration status. To estimate the total effect of migration status on COVID-19 hospitalisation rates, we ran mixed-effect Poisson regression for wave 1 (01/03/2020-31/08/2020; wildtype), and mixed-effect negative binomial regressions for waves 2 (01/09/2020-31/05/2021; Alpha) and 3 (01/06/2020-31/11/2021; Delta). Results of all models were then meta-analysed.

Results

Of 30,276 adults in the analyses, 26,492 (87.5 %) were UK-born and 3,784 (12.5 %) were migrants. COVID-19-related hospitalisation incidence rates for UK-born and migrant individuals across waves 1-3 were 2.7 [95 % CI 2.2-3.2], and 4.6 [3.1-6.7] per 1,000 person-years, respectively. Pooled incidence rate ratios across waves suggested increased rate of COVID-19-related hospitalisation in migrants compared to UK-born individuals in unadjusted 1.68 [1.08-2.60] and adjusted analyses 1.35 [0.71-2.60].

Conclusion

Our findings suggest migration populations in the UK have excess risk of COVID-19-related hospitalisations and underscore the need for more equitable interventions particularly aimed at COVID-19 vaccination uptake among migrants.

Patterns of case fatality and hospitalization duration among nearly 1 million hospitalized COVID-19 patients covered by Iran Health Insurance Organization (IHIO) over two years of pandemic: An analysis of associated factors

BACKGROUND

Different populations and areas of the world experienced diverse COVID-19 hospitalization and mortality rates. Claims data is a systematically recorded source of hospitalized patients' information that could be used to evaluate the disease management course and outcomes. We aimed to investigate the hospitalization and mortality patterns and associated factors in a huge sample of hospitalized patients.

METHODS

In this retrospective registry-based study, we utilized claim data from the Iran Health Insurance Organization (IHIO) consisting of approximately one million hospitalized patients across various hospitals in Iran over a 26-month period. All records in the hospitalization dataset with ICD-10 codes U07.1/U07.2 for clinically/laboratory confirmed COVID-19 were included. In this study, a case referred to one instance of a patient being hospitalized. If a patient experienced multiple hospitalizations within 30 days, those were aggregated into a single case. However, if hospitalizations had longer intervals, they were considered independent cases. The primary outcomes of study were general and intensive care unit (ICU) hospitalization periods and case fatality rate (CFR) at the hospital. Besides, various demographic and hospitalization-associated factors were analyzed to derive the associations with study outcomes using accelerated failure time (AFT) and logistic regression models.

RESULTS

A total number of 1 113 678 admissions with COVID-19 diagnosis were recorded by IHIO during the study period, defined as 917 198 cases, including 51.9% females and 48.1% males. The 61-70 age group had the highest number of cases for both sexes. Among defined cases, CFR was 10.36% (95% CI: 10.29-10.42). The >80 age group had the highest CFR (26.01% [95% CI: 25.75-26.27]). The median of overall hospitalization and ICU days were 4 (IQR: 3-7) and 5 (IQR: 2-8), respectively. Male patients had a significantly higher risk for mortality both generally (odds ratio (OR) = 1.36 [1.34-1.37]) and among ICU admitted patients (1.12 [1.09-1.12]). Among various insurance funds, Foreign Citizens had the highest risk of death both generally (adjusted OR = 2.06 [1.91-2.22]) and in ICU (aOR = 1.71 [1.51-1.92]). Increasing age groups was a risk of longer hospitalization, and the >80 age group had the highest risk for overall hospitalization period (median ratio = 1.52 [1.51-1.54]) and at ICU (median ratio = 1.17 [1.16-1.18]). Considering Tehran as the reference province, Sistan and Balcuchestan (aOR = 1.4 [1.32-1.48]), Alborz (aOR = 1.28 [1.22-1.35]), and Khorasan Razavi (aOR = 1.24 [1.20-1.28]) were the provinces with the highest risk of mortality in hospitalized patients.

CONCLUSION

Hospitalization data unveiled mortality and duration associations with variables, highlighting provincial outcome disparities in Iran. Using enhanced registry systems in conjunction with other studies, empowers policymakers with evidence for optimizing resource allocation and fortifying healthcare system resilience against future health challenges.

Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond "White", "Black", "Asian", "Mixed" and "Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.

Occupational risk of COVID-19 in foreign-born employees in Denmark

BACKGROUND

Foreign-born workers in high-income countries experience higher rates of COVID-19 but the causes are only partially known.

AIMS

To examine if the occupational risk of COVID-19 in foreign-born workers deviates from the risk in native-born employees in Denmark.

METHODS

Within a registry-based cohort of all residents employed in Denmark (n = 2 451 542), we identified four-digit DISCO-08 occupations associated with an increased incidence of COVID-19-related hospital admission during 2020-21 (at-risk occupations). The sex-specific prevalence of at-risk employment in foreign born was compared with the prevalence in native born. Moreover, we examined if the country of birth modified the risk of a positive SARS-CoV-2 polymerase chain reaction (PCR) test and COVID-19-related hospital admission in at-risk occupations.

RESULTS

Workers born in low-income countries and male workers from Eastern Europe more often worked in at-risk occupations (relative risks between 1.16 [95% confidence interval {CI} 1.14-1.17] and 1.87 [95% CI 1.82-1.90]). Being foreign-born modified the adjusted risk of PCR test positivity (test for interaction P < 0.0001), primarily because of higher risk in at-risk occupations among men born in Eastern European countries (incidence rate ratio [IRR] 2.39 [95% CI 2.09-2.72] versus IRR 1.19 [95% CI 1.14-1.23] in native-born men). For COVID-19-related hospital admission, no overall interaction was seen, and in women, country of birth did not consistently modify the occupational risk.

CONCLUSIONS

Workplace viral transmission may contribute to an excess risk of COVID-19 in male workers born in Eastern Europe, but most foreign-born employees in at-risk occupations seem not to be at higher occupational risk than native born.

Social Inequalities in Long-Term Health Effects After COVID-19-A Scoping Review

Objectives: We aimed to map and synthesize evidence about social inequalities in long-term health effects after COVID-19 (LTHE), often referred to as "long COVID" or "post-COVID-19 conditions." Methods: We conducted a scoping review of peer-reviewed articles by searching the databases Embase and Scopus. According to predefined inclusion criteria, titles/abstracts and full texts were screened for eligibility. Additionally, reference lists of all included studies were hand-searched for eligible studies. This study followed the PRISMA guidelines for scoping reviews. Results: Nineteen articles were included. LTHE were analysed according to ethnicity, education, income, employment and deprivation indices. The studies varied significantly in their definitions of LTHE. Eighty-two analyses showed no statistically significant associations. At least 12 studies had a high risk of type II errors. Only studies associating deprivation indices and long COVID tended to show a higher prevalence of LTHE in deprived areas. Conclusion: Although some studies indicated social inequalities in LTHE, evidence was generally weak and inconclusive. Further studies with larger sample sizes specifically designed to detect social inequalities regarding LTHE are needed to inform future healthcare planning and public health policies.

Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study

OBJECTIVES

To identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk.

METHODS

We identified outbreaks of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work and the mode of commute to work, through data linkages based on Middle Layer Super Output Areas in England between 20 June 2021 and 20 February 2022. We estimated population-level associations between potential risk factors and workplace outbreaks, adjusting for plausible confounders identified using a directed acyclic graph.

RESULTS

For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 outbreaks, while increased vaccination was associated with reduced risk. Employee demographic risk factors varied across industry, but for the majority of industries, a higher proportion of black/African/Caribbean ethnicities and living in deprived areas, was associated with increased outbreak risk. A higher proportion of employees in the 60-64 age group was associated with reduced outbreak risk. There were significant associations between gender, work commute modes and staff contract type with outbreak risk, but these were highly variable across industries.

CONCLUSIONS

This study has used novel national data linkages to identify potential risk factors of workplace COVID-19 outbreaks, including possible protective effects of vaccination and increased physical distance at work. The same methodological approach can be applied to wider occupational and environmental health research.

Salivary IgA and vimentin differentiate in vitro SARS-CoV-2 infection: A study of 290 convalescent COVID-19 patients

SARS-CoV-2 initially infects cells in the nasopharynx and oral cavity. The immune system at these mucosal sites plays a crucial role in minimizing viral transmission and infection. To develop new strategies for preventing SARS-CoV-2 infection, this study aimed to identify proteins that protect against viral infection in saliva. We collected 551 saliva samples from 290 healthcare workers who had tested positive for COVID-19, before vaccination, between June and December 2020. The samples were categorized based on their ability to block or enhance infection using in vitro assays. Mass spectrometry and enzyme-linked immunosorbent assay experiments were used to identify and measure the abundance of proteins that specifically bind to SARS-CoV-2 antigens. Immunoglobulin (Ig)A specific to SARS-CoV-2 antigens was detectable in over 83% of the convalescent saliva samples. We found that concentrations of anti-receptor-binding domain IgA >500 pg/µg total protein in saliva correlate with reduced viral infectivity in vitro. However, there is a dissociation between the salivary IgA response to SARS-CoV-2, and systemic IgG titers in convalescent COVID-19 patients. Then, using an innovative technique known as spike-baited mass spectrometry, we identified novel spike-binding proteins in saliva, most notably vimentin, which correlated with increased viral infectivity in vitro and could serve as a therapeutic target against COVID-19.

Spatiotemporal variability in socioeconomic inequalities in COVID-19 vaccination in Catalonia, Spain

OBJECTIVES

Socioeconomic inequalities have played a significant role in the unequal coverage of the COVID-19 vaccine. The objectives of this study were to (1) assess the socioeconomic inequalities in COVID-19 vaccination coverage in Catalonia, Spain; (2) analyse the spatial variation over time of these inequalities; and (3) assess variations in time and space in the effect of vaccination on inequalities in COVID-19 outcomes.

STUDY DESIGN

A mixed longitudinal ecological study design was used.

METHODS

Catalonia is divided in to 373 Basic Health Areas. Weekly data from these Basic Health Areas were obtained from the last week of December 2020 until the first week of March of 2022. A joint spatio-temporal model was used with the dependent variables of vaccination and COVID-19 outcomes, which were estimated using a Bayesian approach. The study controlled for observed confounders, unobserved heterogeneity, and spatial and temporal dependencies. The study allowed the effect of the explanatory variables on the dependent variables to vary in space and in time.

RESULTS

Areas with lower socioeconomic level were those with the lowest vaccination rates and the highest risk of COVID-19 outcomes. In general, individuals in areas that were located in the upper two quartiles of average net income per person and in the lower two quartiles of unemployment rate (i.e., the least economically disadvantaged) had a higher propensity to be vaccinated than those in the most economically disadvantaged areas. In the same sense, the greater the percentage of the population aged ≥65 years, the higher the propensity to be vaccinated, while areas located in the two upper quartiles of population density and areas with a high percentage of poor housing had a lower propensity to be vaccinated. Higher vaccination rates reduced the risk of COVID-19 outcomes, while COVID-19 outcomes did not influence the propensity to be vaccinated. The effects of the explanatory variables were not the same in all areas or between the different waves of the pandemic, and clusters of excess risk of low vaccination in the most disadvantaged areas were detected.

CONCLUSIONS

COVID-19 vaccination inequalities in the most disadvantaged areas could be a result of structural barriers, such as the lack of access to information about the vaccination process, and/or logistical challenges, such as the lack of transportation, limited Internet access or difficulty in scheduling appointments. Public health strategies should be developed to mitigate these barriers and reduce vaccination inequalities.

Increased prevalence of the COVID-19 associated Neanderthal mutations in the Central European Roma population

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent COVID-19 has spread world-wide and become pandemic with about 7 million deaths reported so far. Interethnic variability of the disease has been described, but a significant part of the differences remain unexplained and may be attributable to genetic factors.

AIM

To analyse genetic factors potentially influencing COVID-19 susceptibility and severity in European Roma minority.

SUBJECTS AND METHODS

Two genetic determinants, within OAS-1 (2-prime,5-prime-oligoadenylate synthetase 1, a key protein in the defence against viral infection; it activates RNases that degrade viral RNAs; rs4767027 has been analysed) and LZTFL1 (leucine zipper transcription factor-like 1, expressed in the lung respiratory epithelium; rs35044562 has been analysed) genes were screened in a population-sample of Czech Roma (N = 302) and majority population (N = 2,559).

RESULTS

For both polymorphisms, Roma subjects were more likely carriers of at least one risky allele for both rs4767027-C (p < 0.001) and rs35044562-G (p < 0.00001) polymorphism. There were only 5.3% Roma subjects without at least one risky allele in comparison with 10.1% in the majority population (p < 0.01).

CONCLUSIONS

It is possible that different genetic background plays an important role in increased prevalence of COVID-19 in the Roma minority.

Risk of long COVID and associated symptoms after acute SARS-COV-2 infection in ethnic minorities: A nationwide register-linked cohort study in Denmark

BACKGROUND

Ethnic minorities living in high-income countries have been disproportionately affected by Coronavirus Disease 2019 (COVID-19) in terms of infection rates, hospitalisations, and deaths; however, less is known about long COVID in these populations. Our aim was to examine the risk of long COVID and associated symptoms among ethnic minorities.

METHODS AND FINDINGS

We used nationwide register-based cohort data on individuals diagnosed with COVID-19 aged ≥18 years (n = 2,287,175) between January 2020 and August 2022 in Denmark. We calculated the risk of long COVID diagnosis and long COVID symptoms among ethnic minorities compared with native Danes using multivariable Cox proportional hazard regression and logistic regression, respectively. Among individuals who were first time diagnosed with COVID-19 during the study period, 39,876 (1.7%) were hospitalised and 2,247,299 (98.3%) were nonhospitalised individuals. Of the diagnosed COVID-19 cases, 1,952,021 (85.3%) were native Danes and 335,154 (14.7%) were ethnic minorities. After adjustment for age, sex, civil status, education, family income, and Charlson comorbidity index, ethnic minorities from North Africa (adjusted hazard ratio [aHR] 1.41, 95% confidence interval [CI] [1.12,1.79], p = 0.003), Middle East (aHR 1.38, 95% CI [1.24,1.55], p < 0.001), Eastern Europe (aHR 1.35, 95% CI [1.22,1.49], p < 0.001), and Asia (aHR 1.23, 95% CI [1.09,1.40], p = 0.001) had significantly greater risk of long COVID diagnosis than native Danes. In the analysis by largest countries of origin, the greater risks of long COVID diagnosis were found in people of Iraqi origin (aHR 1.56, 95% CI [1.30,1.88], p < 0.001), people of Turkish origin (aHR 1.42, 95% CI [1.24,1.63], p < 0.001), and people of Somali origin (aHR 1.42, 95% CI [1.07,1.91], p = 0.016). A significant factor associated with an increased risk of long COVID diagnosis was COVID-19 hospitalisation. The risk of long COVID diagnosis among ethnic minorities was more pronounced between January 2020 and June 2021. Furthermore, the odds of reporting cardiopulmonary symptoms (including dyspnoea, cough, and chest pain) and any long COVID symptoms were higher among people of North African, Middle Eastern, Eastern European, and Asian origins than among native Danes in both unadjusted and adjusted models. Despite including the nationwide sample of individuals diagnosed with COVID-19, the precision of our estimates on long COVID was limited to the sample of patients with symptoms who had contacted the hospital.

CONCLUSIONS

Belonging to an ethnic minority group was significantly associated with an increased risk of long COVID, indicating the need to better understand long COVID drivers and address care and treatment strategies in these populations.

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study

OBJECTIVE

This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.

DESIGN

Population-based cohort study.

SETTING

UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records.

PARTICIPANTS

Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes).

PRIMARY AND SECONDARY OUTCOME MEASURES

COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity.

RESULTS

In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis.

CONCLUSIONS

Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections.

Risk Factors for Community and Intrahousehold Transmission of SARS-CoV-2: Modeling in a Nationwide French Population-Based Cohort Study, the EpiCoV Study

We assessed the risk of acquiring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from household and community exposure according to age, family ties, and socioeconomic and living conditions using serological data from a nationwide French population-based cohort study, the Epidémiologie et Conditions de Vie (EpiCoV) Study. A history of SARS-CoV-2 infection was defined by a positive anti-SARS-CoV-2 enzyme-linked immunosorbent assay immunoglobulin G result in November-December 2020. We applied stochastic chain binomial models fitted to the final distribution of household infections to data from 17,983 individuals aged ≥6 years from 8,165 households. Models estimated the competing risks of being infected from community and household exposure. The age group 18-24 years had the highest risk of extrahousehold infection (8.9%, 95% credible interval (CrI): 7.5, 10.4), whereas the oldest (≥75 years) and youngest (6-10 years) age groups had the lowest risk, at 2.6% (95% CrI: 1.8, 3.5) and 3.4% (95% CrI: 1.9, 5.2), respectively. Extrahousehold infection was also associated with socioeconomic conditions. Within households, the probability of person-to-person transmission increased with age, from 10.6% (95% CrI: 5.0, 17.9) among children aged 6-10 years to 43.1% (95% CrI: 32.6, 53.2) among adults aged 65-74 years. Transmission was higher between partners (29.9%, 95% CrI: 25.6, 34.3) and from mother to child (29.1%, 95% CrI: 21.4, 37.3) than between individuals related by other family ties. In 2020 in France, the main factors identified for extrahousehold SARS-CoV-2 infection were age and socioeconomic conditions. Intrahousehold infection mainly depended on age and family ties.

Trends in inequalities in avoidable hospitalisations across the COVID-19 pandemic: a cohort study of 23.5 million people in England

OBJECTIVE

To determine whether periods of disruption were associated with increased 'avoidable' hospital admissions and wider social inequalities in England.

DESIGN

Observational repeated cross-sectional study.

SETTING

England (January 2019 to March 2022).

PARTICIPANTS

With the approval of NHS England we used individual-level electronic health records from OpenSAFELY, which covered ~40% of general practices in England (mean monthly population size 23.5 million people).

PRIMARY AND SECONDARY OUTCOME MEASURES

We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity and geographical region.

RESULTS

There were large declines in avoidable hospitalisations during the first national lockdown (March to May 2020). Trends increased post-lockdown but never reached 2019 levels. The exception to these trends was for vaccine-preventable ambulatory care sensitive admissions which remained low throughout 2020-2021. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed across levels of neighbourhood socioeconomic deprivation, Asian ethnicity (compared with white ethnicity) and geographical region (especially in northern regions).

CONCLUSIONS

We found no evidence that periods of healthcare disruption from the COVID-19 pandemic resulted in more avoidable hospitalisations. Falling avoidable hospital admissions has coincided with declining inequalities most strongly by level of deprivation, but also for Asian ethnic groups and northern regions of England.

Association of psychological distress and DNA methylation: A 5-year longitudinal population-based twin study

AIM

To identify the psychological distress (PD)-associated 5'-cytosine-phosphate-guanine-3' sites (CpGs), and investigate the temporal relationship between dynamic changes in DNA methylation (DNAm) and PD.

METHODS

This study included 1084 twins from the Chinese National Twin Register (CNTR). The CNTR conducted epidemiological investigations and blood withdrawal twice in 2013 and 2018. These included twins were used to perform epigenome-wide association studies (EWASs) and to validate the previously reported PD-associated CpGs selected from previous EWASs in PubMed, Embase, and the EWAS catalog. Next, a cross-lagged study was performed to examine the temporality between changes in DNAm and PD in 308 twins who completed both 2013 and 2018 surveys.

RESULTS

The EWAS analysis of our study identified 25 CpGs. In the validation analysis, 741 CpGs from 29 previous EWASs on PD were selected for validation, and 101 CpGs were validated to be significant at a false discovery rate <0.05. The cross-lagged analysis found a unidirectional path from PD to DNAm at 14 CpGs, while no sites showed significance from DNAm to PD.

CONCLUSIONS

This study identified and validated PD-related CpGs in a Chinese twin population, and suggested that PD may be the cause of changes in DNAm over time. The findings provide new insights into the molecular mechanisms underlying PD pathophysiology.

Outcomes of SARS-CoV-2 and Seasonal Viruses Among Children Hospitalized in Brazil

BACKGROUND AND OBJECTIVES

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with other respiratory viruses is crucial for developing effective public health strategies in the postpandemic era. This study aimed to compare the outcomes of SARS-CoV-2 and seasonal viruses in children and adolescents hospitalized with severe acute respiratory infection (SARI).

METHODS

This population-based, retrospective cohort study included children and adolescents hospitalized with SARI from February 2020 to February 2023 in Brazil. The main exposure of interest was viral etiology. The primary outcome was in-hospital mortality. Competing risk analysis was used to account for time dependency and competing events.

RESULTS

A total of 235 829 patients had available results of the viral tests, with SARS-CoV-2 predominance. According to the competing-risk survival analysis, the estimated probability of a fatal outcome at 30 days of hospitalization according to the viral strain was 6.5%, 3.4%, 2.9%, 2.3%, 2.1%, and 1.8%, for SARS-CoV-2, coinfection, adenovirus, influenza, other viruses, and respiratory syncytial virus, respectively. Individuals with a positive test for SARS-CoV-2 had hazard of death 3 times higher than subjects with a negative test (hazard ratio, 3.3; 95% confidence interval, 3.1-3.5). After adjustment by the competing-risk multivariable analysis, admission in Northeast and North regions, oxygen saturation <95%, and the presence of comorbidities were risk factors for death in all viral strains.

CONCLUSIONS

SARS-CoV-2 infection had the highest hazard of in-hospital mortality in this pediatric cohort hospitalized with SARI. Regardless of viral etiology, the presence of underlying medical conditions was a risk factor for death.

Excess mortality in US Veterans during the COVID-19 pandemic: an individual-level cohort study

BACKGROUND

Most analyses of excess mortality during the COVID-19 pandemic have employed aggregate data. Individual-level data from the largest integrated healthcare system in the US may enhance understanding of excess mortality.

METHODS

We performed an observational cohort study following patients receiving care from the Department of Veterans Affairs (VA) between 1 March 2018 and 28 February 2022. We estimated excess mortality on an absolute scale (i.e. excess mortality rates, number of excess deaths) and a relative scale by measuring the hazard ratio (HR) for mortality comparing pandemic and pre-pandemic periods, overall and within demographic and clinical subgroups. Comorbidity burden and frailty were measured using the Charlson Comorbidity Index and Veterans Aging Cohort Study Index, respectively.

RESULTS

Of 5 905 747 patients, the median age was 65.8 years and 91% were men. Overall, the excess mortality rate was 10.0 deaths/1000 person-years (PY), with a total of 103 164 excess deaths and pandemic HR of 1.25 (95% CI 1.25-1.26). Excess mortality rates were highest among the most frail patients (52.0/1000 PY) and those with the highest comorbidity burden (16.3/1000 PY). However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46).

CONCLUSIONS

Individual-level data offered crucial clinical and operational insights into US excess mortality patterns during the COVID-19 pandemic. Notable differences emerged among clinical risk groups, emphasizing the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.

Social determinants of ethnic disparities in SARS-CoV-2 infection: UK Biobank SARS-CoV-2 Serology Study

BACKGROUND

The social determinants of ethnic disparities in risk of SARS-CoV-2 infection during the first wave of the pandemic in the UK remain unclear.

METHODS

In May 2020, a total of 20 195 adults were recruited from the general population into the UK Biobank SARS-CoV-2 Serology Study. Between mid-May and mid-November 2020, participants provided monthly blood samples. At the end of the study, participants completed a questionnaire on social factors during different periods of the pandemic. Logistic regression yielded ORs for the association between ethnicity and SARS-CoV-2 immunoglobulin G antibodies (indicating prior infection) using blood samples collected in July 2020, immediately after the first wave.

RESULTS

After exclusions, 14 571 participants (mean age 56; 58% women) returned a blood sample in July, of whom 997 (7%) had SARS-CoV-2 antibodies. Seropositivity was strongly related to ethnicity: compared with those of White ethnicity, ORs (adjusted for age and sex) for Black, South Asian, Chinese, Mixed and Other ethnic groups were 2.66 (95% CI 1.94-3.60), 1.66 (1.15-2.34), 0.99 (0.42-1.99), 1.42 (1.03-1.91) and 1.79 (1.27-2.47), respectively. Additional adjustment for social factors reduced the overall likelihood ratio statistics for ethnicity by two-thirds (67%; mostly from occupational factors and UK region of residence); more precise measurement of social factors may have further reduced the association.

CONCLUSIONS

This study identifies social factors that are likely to account for much of the ethnic disparities in SARS-CoV-2 infection during the first wave in the UK, and highlights the particular relevance of occupation and residential region in the pathway between ethnicity and SARS-CoV-2 infection.

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic

The COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of 'experimentation' in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of 'team science', the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a 'call to actions' for both policy-makers and researchers.

Antibody response to four doses of SARS-CoV-2 vaccine in rare autoimmune rheumatic diseases: an observational study

Objective

Antibody responses to coronavirus disease 2019 (COVID-19) vaccines are reduced among immunocompromised patients but are not well quantified among people with rare disease. We conducted an observational study to evaluate the antibody responses to the booster SARS-CoV-2 vaccine in people with rare autoimmune rheumatic diseases (RAIRD).

Methods

Blood samples were collected after second, before third, after third and after fourth vaccine doses. Anti-spike and anti-nucleocapsid antibody levels were measured using an in-house ELISA. Logistic regression models were built to determine the predictors for non-response. Results were compared with age- and sex-matched healthy controls.

Results

Forty-three people with RAIRD were included, with a median age of 56 years. Anti-spike seropositivity increased from 42.9% after second dose to 51.2% after third dose and 65.6% after fourth dose. Median anti-spike antibody levels increased from 33.6 (interquartile range 7.8-724.5) binding antibody units after second dose to 239.4 (interquartile range 35.8-1051.1) binding antibody units after the booster dose (third dose, or fourth dose if eligible). Of the participants who had sufficient antibody levels post-second dose, 22.2% had insufficient levels after the booster, and 34.9% of participants had lower antibodies after the booster than the lowest healthy control had after the second dose. Rituximab in the 6 months prior to booster (P = 0.02) and non-White ethnicity (P = 0.04) were associated with non-response. There was a dose-response relationship between the timing of rituximab and generation of sufficient antibodies (P = 0.03).

Conclusion

Although the booster dose increased anti-spike IgG and seropositivity rates, some people with RAIRD, particularly those on rituximab, had insufficient antibody levels despite three or four doses.

Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study

BACKGROUND

The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear.

AIMS

To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity.

METHOD

This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic.

RESULTS

Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39-1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12-1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01-1.10) in the SMI stratum and 1.16 (95% CI 1.15-1.17) in the non-SMI stratum (P for interaction = 0.001).

CONCLUSIONS

Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

National governance and excess mortality due to COVID-19 in 213 countries: a retrospective analysis and perspectives on future pandemics

BACKGROUND

National governance may have influenced the response of institutions to the Covid-19 pandemic, being a key factor in preparing for the next pandemics. The objective was to analyze the association between excess mortality due to COVID-19 (daily and cumulative per 100 thousand people) and national governance indicators in 213 countries.

METHOD

Multiple linear regression models using secondary data from large international datasets that are in the public domain were performed. Governance indicators corresponded to six dimensions: (i) Voice and Accountability; (ii) Political Stability and Absence of Violence/Terrorism; (iii) Government Effectiveness; (iv) Regulatory Quality; (v) Rule of Law and (vi) Control of Corruption. The statistical analysis consisted of adjusting a multiple linear regression model. Excess mortality due to COVID-19 was adjusted for potential confounding factors (demographic, environmental, health, economic, and ethnic variables).

RESULTS

The indicators Control of Corruption, Government Effectiveness, Regulatory Quality and Rule of Law had a significant inverse association (p < 0.0001) with the estimated excess mortality in 2020, 2021 and 2022. Furthermore, the governance indicators had a direct significant association (p < 0.0001) with the vaccination variables (People_fully_vaccinated; Delivered population; The total number of vaccination doses administered per 100 people at the country level), except for the variables Vaccination policies and Administration of first dose, which were inversely associated. In countries with better governance, COVID-19 vaccination was initiated earlier.

CONCLUSION

Better national governance indicators were associated with lower excess mortality due to COVID-19 and faster administration of the first dose of the COVID-19 vaccine.

The value of the neutrophil to lymphocyte ratio and PLT count for the diagnosis and prediction of COVID-19 severity

BACKGROUND

COVID-19 and influenza A can cause severe respiratory illness. Differentiating between the two diseases and identifying critically ill patients in times of epidemics become a challenge for frontline medical staff. We sought to investigate whether both diseases and their severity could be recognized by routine blood parameters.

METHODS

Our retrospective study analysed the clinical data and first-time routine blood parameters of 80 influenza A patients and 123 COVID-19 patients. COVID-19 patients were divided into three groups according to treatment modalities and outcomes: outpatient group, inpatient without invasive mechanical ventilation (IMV) group, and inpatient with IMV group. We used the Mann-Whitney and Kruskal-Wallis tests to analyze the differences in routine blood parameters between the two or three groups. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess the diagnostic accuracy.

RESULTS

Compared with outpatient influenza A patients, outpatient COVID-19 patients had a higher neutrophil to lymphocyte ratio (NLR) (6.63 vs 3.55). ROC analysis showed that the NLR had a high diagnostic value for differentiating COVID-19 from influenza A (AUC = 0.739). The best cut-off point of the NLR was 6.48, the diagnostic sensitivity was 0.523, and the specificity was 0.925. The median platelet (PLT) count in the different COVID-19 groups was as follows: outpatient group (189×109/L), inpatient without IMV group (161×109/L), and inpatient with IMV group (94×109/L). Multivariate logistic regression analysis found a significant association between PLT and treatment modality and outcome in COVID-19 patients (p<0.001).

CONCLUSIONS

NLR can be used as a potential biological indicator to distinguish COVID-19 and influenza A. Decreased PLT predicts the critical condition of COVID-19 patients and helps stratify the treatment of COVID-19 patients.

A co-produced service evaluation of ethnic minority community service user experiences of a specialist mental health service during the COVID-19 pandemic

BACKGROUND

For ethnic minority communities in the UK, the COVID-19 pandemic amplified existing health inequalities and created other consequential disadvantages like increased vulnerability to COVID-19, higher rates of hospital admissions, increased mortality and poorer mental health outcomes. While longer-term impacts of COVID-19 are considered, it is crucial for NHS mental health services to understand the specific barriers and needs of ethnic minority communities to provide consistent and equitable access to mental health services. These aspects were the focus of a service evaluation of a Sussex-wide mental health service conducted in co-production with experts-by-experience, public members, health professionals and researchers from ethnic minority communities.

METHODS

Co-designed creative workshops (n = 13) and semi-structured qualitative interviews (n = 13) were used to explore experiences of accessing specialist mental health services during the COVID-19 pandemic. Participants were: Sussex Partnership NHS Foundation Trust (SPFT) service users recruited between October 2021 and January 2022; aged 16+; from ethnic minority community backgrounds. Data was analysed using Thematic Analysis.

RESULTS

The analysis yielded five overarching themes contextualising service users' experiences: (1) limited awareness of SPFT mental health services; (2) effects of COVID-19 in gaining access to SPFT; (3) SPFT reaching out to ethnic minorities; (4) being supported, 4a) hiding my mental health status from friends and families, 4b) lack of ethnic diversity in services, and 4c) better provision of information and support services, (5) relationship between childhood experiences and current mental health. These findings led to seven key recommendations for future service developments within SPFT.

CONCLUSIONS

Although this evaluation was set in the context of COVID-19, findings have highlighted specific mental health service needs for ethnic minorities that are applicable beyond the confines of the pandemic. Many benefited from online sessions seen as more inclusive. Mental health advocates, outreach and joint working with communities could help further reduce stigmatising attitudes and improve engagement with mental health services. Improved service awareness of the impact of childhood or historical traumas experienced by ethnic minority communities on current mental health, the role of cultural awareness training and availability of culturally adapted therapies is also needed. Many service improvement recommendations provided could impact all service users.

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes

BACKGROUND

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort.

METHODS

We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups.

RESULTS

We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease.

CONCLUSIONS

These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations.

TRIAL REGISTRATION

NCT04357366.

SARS-CoV-2 infections in migrants and the role of household overcrowding: a causal mediation analysis of Virus Watch data

BACKGROUND

Migrants are over-represented in SARS-CoV-2 infections globally; however, evidence is limited for migrants in England and Wales. Household overcrowding is a risk factor for SARS-CoV-2 infection, with migrants more likely to live in overcrowded households than UK-born individuals. We aimed to estimate the total effect of migration status on SARS-CoV-2 infection and to what extent household overcrowding mediated this effect.

METHODS

We included a subcohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1 September 2020-30 April 2021) who were aged ≥18 years, self-reported the number of rooms in their household and had no evidence of SARS-CoV-2 infection pre-September 2020. We estimated total, indirect and direct effects using Buis' logistic decomposition regression controlling for age, sex, ethnicity, clinical vulnerability, occupation, income and whether they lived with children.

RESULTS

In total, 23 478 individuals were included. 9.07% (187/2062) of migrants had evidence of infection during the study period vs 6.27% (1342/21 416) of UK-born individuals. Migrants had 22% higher odds of infection during the second wave (total effect; OR 1.22, 95% CI 1.01 to 1.47). Household overcrowding accounted for approximately 36% (95% CI -4% to 77%) of these increased odds (indirect effect, OR 1.07, 95% CI 1.03 to 1.12; proportion accounted for: indirect effect on log odds scale/total effect on log odds scale=0.36).

CONCLUSION

Migrants had higher odds of SARS-CoV-2 infection during the second wave compared with UK-born individuals and household overcrowding explained 36% of these increased odds. Policy interventions to reduce household overcrowding for migrants are needed as part of efforts to tackle health inequalities during the pandemic and beyond.

Ethnic inequalities in positive SARS-CoV-2 tests, infection prognosis, COVID-19 hospitalisations and deaths: analysis of 2 years of a record linked national cohort study in Scotland

BACKGROUND

This study aims to estimate ethnic inequalities in risk for positive SARS-CoV-2 tests, COVID-19 hospitalisations and deaths over time in Scotland.

METHODS

We conducted a population-based cohort study where the 2011 Scottish Census was linked to health records. We included all individuals ≥ 16 years living in Scotland on 1 March 2020. The study period was from 1 March 2020 to 17 April 2022. Self-reported ethnic group was taken from the census and Cox proportional hazard models estimated HRs for positive SARS-CoV-2 tests, hospitalisations and deaths, adjusted for age, sex and health board. We also conducted separate analyses for each of the four waves of COVID-19 to assess changes in risk over time.

FINDINGS

Of the 4 358 339 individuals analysed, 1 093 234 positive SARS-CoV-2 tests, 37 437 hospitalisations and 14 158 deaths occurred. The risk of COVID-19 hospitalisation or death among ethnic minority groups was often higher for White Gypsy/Traveller (HR 2.21, 95% CI (1.61 to 3.06)) and Pakistani 2.09 (1.90 to 2.29) groups compared with the white Scottish group. The risk of COVID-19 hospitalisation or death following confirmed positive SARS-CoV-2 test was particularly higher for White Gypsy/Traveller 2.55 (1.81-3.58), Pakistani 1.75 (1.59-1.73) and African 1.61 (1.28-2.03) individuals relative to white Scottish individuals. However, the risk of COVID-19-related death following hospitalisation did not differ. The risk of COVID-19 outcomes for ethnic minority groups was higher in the first three waves compared with the fourth wave.

INTERPRETATION

Most ethnic minority groups were at increased risk of adverse COVID-19 outcomes in Scotland, especially White Gypsy/Traveller and Pakistani groups. Ethnic inequalities persisted following community infection but not following hospitalisation, suggesting differences in hospital treatment did not substantially contribute to ethnic inequalities.

Association between ethnic background and COVID-19 morbidity, mortality and vaccination in England: a multistate cohort analysis using the UK Biobank

OBJECTIVES

Despite growing evidence suggesting increased COVID-19 mortality among people from ethnic minorities, little is known about milder forms of SARS-CoV-2 infection. We sought to explore the association between ethnic background and the probability of testing, testing positive, hospitalisation, COVID-19 mortality and vaccination uptake.

DESIGN

A multistate cohort analysis. Participants were followed between 8 April 2020 and 30 September 2021.

SETTING

The UK Biobank, which stores medical data on around half a million people who were recruited between 2006 and 2010.

PARTICIPANTS

405 541 subjects were eligible for analysis, limited to UK Biobank participants living in England. 23 891 (6%) of participants were non-white.

PRIMARY AND SECONDARY OUTCOME MEASURES

The associations between ethnic background and testing, testing positive, hospitalisation and COVID-19 mortality were studied using multistate survival analyses. The association with single and double-dose vaccination was also modelled. Multistate models adjusted for age, sex and socioeconomic deprivation were fitted to estimate adjusted HRs (aHR) for each of the multistate transitions.

RESULTS

18 172 (4.5%) individuals tested positive, 3285 (0.8%) tested negative and then positive, 1490 (6.9% of those tested positive) were hospitalised, and 129 (0.6%) tested positive at the moment of hospital admission (ie, direct hospitalisation). Finally, 662 (17.4%) died after admission. Compared with white participants, Asian participants had an increased risk of negative to positive transition (aHR 1.24 (95% CI 1.02 to 1.52)), testing positive (95% CI 1.44 (1.33 to 1.55)) and direct hospitalisation (1.61 (95% CI 1.28 to 2.03)). Black participants had an increased risk of hospitalisation following a positive test (1.71 (95% CI 1.29 to 2.27)) and direct hospitalisation (1.90 (95% CI 1.51 to 2.39)). Although not the case for Asians (aHR 1.00 (95% CI 0.98 to 1.02)), black participants had a reduced vaccination probability (0.63 (95% CI 0.62 to 0.65)). In contrast, Chinese participants had a reduced risk of testing negative (aHR 0.64 (95% CI 0.57 to 0.73)), of testing positive (0.40 (95% CI 0.28 to 0.57)) and of vaccination (0.78 (95% CI 0.74 to 0.83)).

CONCLUSIONS

We identified inequities in testing, vaccination and COVID-19 outcomes according to ethnicity in England. Compared with whites, Asian participants had increased risks of infection and admission, and black participants had almost double hospitalisation risk, and a 40% lower vaccine uptake.

Polymorphisms within the SARS-CoV-2 Human Receptor Genes Associate with Variable Disease Outcomes across Ethnicities

The contribution of human genes to the variability of disease outcomes has been shown to be important across infectious diseases. Studies have shown mutations within specific human genes are associated with variable COVID-19 outcomes. We focused on the SARS-CoV-2 receptors/co-receptors to identify the role of specific polymorphisms within ACE2, TMPRSS2, NRP1 and CD147. Polymorphisms within ACE2 (rs2285666), TMPRSS2 (rs12329760), CD147 (rs8259) and NRP1 (rs10080) have been shown to associate with COVID-19 severity. Using cryopreserved samples from COVID-19-positive African, European and South Asian individuals within South Africa, we determined genotype frequencies. The genetic variant rs2285666 was associated with COVID-19 severity with an ethnic bias. African individuals with a CC genotype demonstrate more severe COVID-19 outcomes (OR = 7.5; 95% CI 1.164-80.89; p = 0.024) compared with those with a TT genotype. The expressions of ACE2 and SARS-CoV-2 viral load were measured using droplet digital PCR. Our results demonstrate rs2285666 and rs10080 were significantly associated with increased SARS-CoV-2 viral load and worse outcomes in certain ethnicities. This study demonstrates two important findings. Firstly, SARS-CoV-2 viral load is significantly lower in Africans compared with individuals of European and South Asian descent (p = 0.0002 and p < 0.0001). Secondly, SARS-CoV-2 viral load associates with specific SARS-CoV-2 receptor variants. A limited number of studies have examined the receptor/co-receptor genes within Africa. This study investigated genetic variants within the SARS-CoV-2 receptor/co-receptor genes and their association with COVID-19 severity and SARS-CoV-2 viral load across different ethnicities. We provide a genetic basis for differences in COVID-19 severity across ethnic groups in South Africa, further highlighting the importance of further investigation to determine potential therapeutic targets and to guide vaccination strategies that may prioritize specific genotypes.

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity

Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 patients (mean age: 59.7 ± 20.1 years; 54.2% male) who underwent ECGs at our emergency department before severity classification. The AI-ECG algorithm was evaluated for severity assessment during admission, compared to the Early Warning Scores (EWSs) using the area under the curve (AUC) of the receiver operating characteristic curve, precision, recall, and F1 score. During the internal and external validation, the AI algorithm demonstrated reasonable outcomes in predicting COVID-19 severity with AUCs of 0.735 (95% CI: 0.662-0.807) and 0.734 (95% CI: 0.688-0.781). Combined with EWSs, it showed reliable performance with an AUC of 0.833 (95% CI: 0.830-0.835), precision of 0.764 (95% CI: 0.757-0.771), recall of 0.747 (95% CI: 0.741-0.753), and F1 score of 0.747 (95% CI: 0.741-0.753). In Cox proportional hazards models, the AI-ECG revealed a significantly higher hazard ratio (HR, 2.019; 95% CI: 1.156-3.525, p = 0.014) for mortality, even after adjusting for relevant parameters. Therefore, application of AI-ECG has the potential to assist in early COVID-19 severity prediction, leading to improved patient management.

Clinical outcomes following COVID-19 infection in ethnic minority groups in the UK: a systematic review and meta-analysis

OBJECTIVES

This study evaluated the differences in clinical outcomes of COVID-19 infection between ethnic minorities and the White ethnic group in the UK.

STUDY DESIGN

Systematic review and meta-analysis.

METHODS

This study included adult residents in the UK with confirmed COVID-19 infection. The outcomes evaluated in this study were mortality, intensive care unit (ICU) admission and invasive mechanical ventilation (IMV). Outcome data were compared between individuals from ethnic minority groups and individuals from a White ethnic background. MEDLINE, Embase, Cochrane, medRxiv and PROSPERO were searched for articles published between May 2020 and April 2021. The risk of bias was evaluated using the Newcastle-Ottawa Scale checklist.

PROSPERO ID

CRD42021248117.

RESULTS

Fourteen studies (767,177 participants) were included in the current review. In the adjusted analysis, the pooled odds ratio (OR) for mortality following COVID-19 infection was higher for Black (OR 1.83, 95% confidence interval [CI]: 1.21-2.76, number of studies [k] = 6), Asian (OR 1.16, 95% CI: 0.85-1.57, k = 6) and Mixed and Other (MO) ethnic groups (OR 1.12, 95% CI: 1.04-1.20, k = 5) compared with the White ethnic group. The adjusted and unadjusted ORs of ICU admission for many of the ethnic minority groups were more than double the OR values for the White ethnic group (Black ethnic group = OR 2.32, 95% CI: 1.73-3.11, k = 5; Asian ethnic group = OR 2.34, 95% CI: 1.89-2.90, k = 5; and MO ethnic group = OR 2.26, 95% CI: 1.64-3.11, k = 4). In the adjusted analysis for IMV, the ORs were similarly significantly raised in ethnic minority groups compared with the White ethnic group (Black ethic group = OR 2.03, 95% CI: 1.80-2.29, k = 3; Asian ethnic group = OR 1.84, 95% CI: 1.20-2.80, k = 3; and MO ethnic group = OR 2.09, 95% CI: 1.35-3.22, k = 3).

CONCLUSION

This review found that in the UK, Black, Asian and MO ethnic groups experienced increased COVID-19-related disease severity and mortality compared with the White ethnic group majority.

Revisiting ethnic discrepancies in COVID-19 hospitalized cohorts: a correction for collider bias

OBJECTIVES

Studies from the first waves of the coronavirus disease 2019 (COVID-19) pandemic suggest that individuals from minority ethnicities are at an increased risk of worse outcomes. Concerns exist that this relationship is potentially driven by bias from analyzing hospitalized patients only. We investigate this relationship and the possible presence of bias.

STUDY DESIGN AND SETTING

Using data from South London hospitals across two COVID-19 waves (February 2020 - May 2021), the relationship between ethnicity and COVID-19 outcomes was examined using regression models. Three iterations of each model were completed: 1) an unadjusted analysis, 2) adjusting for covariates (medical history and deprivation), and 3) adjusting for covariates and bias induced by conditioning on hospitalization.

RESULTS

Among 3,133 patients, those who were Asian had a two-fold increased risk of death during the hospital stay that was consistent across the two COVID-19 waves and was not affected by correcting for conditioning on hospitalization. However, wave-specific effects demonstrate significant differences between ethnic groups until bias from using a hospitalized cohort was corrected for.

CONCLUSION

Worsened COVID-19 outcomes in minority ethnicities may be minimized by correcting for bias induced by conditioning on hospitalization. Consideration of this bias should be a key component of study design.

Socio-Economic Factors Associated with Ethnic Disparities in SARS-CoV-2 Infection and Hospitalization

BACKGROUND

There is evidence that non-Italians presented higher incidence of infection and worse health outcomes if compared to native populations in the COVID-19 pandemic. The aim of the study was to compare Italian- and non-Italian-born health outcomes, accounting for socio-economic levels.

METHODS

We analyzed data relative to 906,463 people in Umbria (Italy) from 21 February 2020 to 31 May 2021. We considered the National Deprivation Index, the Urban-Rural Municipalities Index and the Human Development Index (HDI) of the country of birth. We used a multilevel logistic regression model to explore the influence of these factors on SARS-CoV-2 infection and hospitalization rates. Diagnosis in the 48 h preceding admission was an indicator of late diagnosis among hospitalized cases.

RESULTS

Overall, 54,448 persons tested positive (6%), and 9.7% of them were hospitalized. The risk of hospital admission was higher among non-Italians and was inversely related to the HDI of the country of birth. A diagnosis within 48 h before hospitalization was more frequent among non-Italians and correlated to the HDI level.

CONCLUSIONS

COVID-19 had unequal health outcomes among the population in Umbria. Reduced access to primary care services in the non-Italian group could explain our findings. Policies on immigrants' access to primary healthcare need to be improved.

Risk analysis of COVID-19 hospitalization and critical care by race and region in the United States: a cohort study

BACKGROUND

This study aimed to identify the current risk factors for coronavirus disease 2019 severity and examine its association with medication use.

METHODS

We used data from a large United States electronic health record database to conduct an anonymized cohort study of 171,491 patients with coronavirus disease 2019. The study was conducted from January 1, 2020, to August 27, 2021. Data on age, race, sex, history of diseases, and history of medication prescriptions were analyzed using the Cox proportional hazards model analysis to calculate hazard ratios for hospitalization and severe risk.

RESULTS

Factors that increased the risk of hospitalization and critical care were age ≥ 65 years, male sex, type 2 diabetes, hypertension, interstitial pneumonia, and cardiovascular disease. In particular, age ≥ 65 years significantly increased the risk of hospitalization (hazard ratio, 2.81 [95% confidence interval, 2.58-3.07]; P < 0.001) and critical care (hazard ratio, 3.45 [2.88-4.14]; P < 0.001). In contrast, patients with hyperlipidemia had a reduced risk. However, patients with hyperlipidemia who were not taking statins had a significantly increased risk of hospitalization (hazard ratio, 1.24 [1.16-1.34]; P < 0.001). Sodium-glucose cotransporter-2 inhibitors, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, glucocorticoids, and statins significantly reduced the risk of hospitalization and critical care. The risk of hospitalization and critical care increased in patients of all ethnicities with type 2 diabetes. The factors that significantly increased the risk of hospitalization in all regions were older age, hypertension, chronic obstructive pulmonary disease, and cardiovascular disease.

CONCLUSION

This study identified factors that increase or reduce the risk of severe coronavirus disease. The provision of appropriate drug treatment and modification of lifestyle-related risk factors may reduce coronavirus disease severity.

COVID-19 mortality and use of intensive care among ethnic minorities - a national register-based Danish population study

Migrants and ethnic minorities are disproportionately affected by the Coronavirus Disease 2019 (COVID-19) pandemic compared to the majority population. Therefore, we studied mortality and use of mechanical ventilation (MV) by country of birth and migrant status in a nationwide cohort in Denmark. Nationwide register data on all cases hospitalized for > 24-hours with COVID-19 between February 2020 and March 2021. Main outcome measures were mortality and MV within 30 days of hospitalization for COVID-19. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated by region of origin and migrant status using logistic regression analyses, adjusting for age, sex, comorbidity and sociodemographic factors. Of 6,406 patients, 977 (15%) died and 342 (5%) were treated with mechanical ventilation. Immigrants (OR:0.55;95%CI: 0.44-0.70) and individuals of non-Western origin had a lower odds (OR: 0.49; 95% CI: 0.37-0.65) of death upon admission with COVID-19 compared to Danish born individuals. Immigrants and descendants (OR: 1.62; 95% CI: 1.22-2.15) as well as individuals of non-Western origin (OR: 1.83; 95% CI: 1.35-2.47) had a significantly higher odds of MV compared to Danish born individuals. Outcomes of individuals with Western origin did not differ. Immigrants and individuals of non-Western origin had a significantly lower COVID-19 associated mortality compared to individuals of Danish origin after adjustment for sociodemographic factors and comorbidity. In contrast, the odds of MV was higher for immigrants and individuals of non-Western origin compared to individuals of Danish origin.

A panel dataset of COVID-19 vaccination policies in 185 countries

We present a panel dataset of COVID-19 vaccine policies, with data from 01 January 2020 for 185 countries and a number of subnational jurisdictions, reporting on vaccination prioritization plans, eligibility and availability, cost to the individual and mandatory vaccination policies. For each of these indicators, we recorded who is targeted by a policy using 52 standardized categories. These indicators document a detailed picture of the unprecedented scale of international COVID-19 vaccination rollout and strategy, indicating which countries prioritized and vaccinated which groups, when and in what order. We highlight key descriptive findings from these data to demonstrate uses for the data and to encourage researchers and policymakers in future research and vaccination planning. Numerous patterns and trends begin to emerge. For example: 'eliminator' countries (those that aimed to prevent virus entry into the country and community transmission) tended to prioritize border workers and economic sectors, while 'mitigator' countries (those that aimed to reduce the impact of community transmission) tended to prioritize the elderly and healthcare sectors for the first COVID-19 vaccinations; high-income countries published prioritization plans and began vaccinations earlier than low- and middle-income countries. Fifty-five countries were found to have implemented at least one policy of mandatory vaccination. We also demonstrate the value of combining this data with vaccination uptake rates, vaccine supply and demand data, and with further COVID-19 epidemiological data.

Risk factors for SARS-CoV-2 infection during the early stages of the COVID-19 pandemic: a systematic literature review

Introduction

Identifying SARS-CoV-2 infection risk factors allows targeted public health and social measures (PHSM). As new, more transmissible variants of concern (VoC) emerge, vaccination rates increase and PHSM are eased, it is important to understand any potential change to infection risk factors. The aim of this systematic literature review is to describe the risk factors for SARS-CoV-2 infection by VoC.

Methods

A literature search was performed in MEDLINE, PubMed and Embase databases on 5 May 2022. Eligibility included: observational studies published in English after 1 January 2020; any age group; the outcome of SARS-CoV-2 infection; and any potential risk factors investigated in the study. Results were synthesized into a narrative summary with respect to measures of association, by VoC. ROBINS-E tool was utilized for risk of bias assessment.

Results

Of 6,197 studies retrieved, 43 studies were included after screening. Common risk factors included older age, minority ethnic group, low socioeconomic status, male gender, increased household size, occupation/lower income level, inability to work from home, public transport use, and lower education level. Most studies were undertaken when the ancestral strain was predominant. Many studies had some selection bias due to testing criteria and limited laboratory capacity.

Conclusion

Understanding who is at risk enables the development of strategies that target priority groups at each of the different stages of a pandemic and helps inform vaccination strategies and other interventions which may also inform public health responses to future respiratory infection outbreaks. While it was not possible to determine changes to infection risk by recent VoC in this review, the risk factors identified will add to the overall understanding of the groups who are at greatest risk of infection in the early stages of a respiratory virus outbreak.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022330706, PROSPERO [CRD42022330706].