Race, ethnicity, community-level socioeconomic factors, and risk of COVID-19 in the United States and the United Kingdom

Socioeconomic and temporal heterogeneity in SARS-CoV-2 exposure and disease in England from May 2020 to February 2023

The impact of COVID-19 varied significantly by deprivation, ethnicity, and policy measures. We analyzed individual-level data on 12,310,485 first SARS-CoV-2 Pillar 2-PCR-confirmed infections, 439,083 hospitalizations, 107,823 deaths, and vaccination records in England from May 2020 to February 2022. Poisson regression models adjusted for demographic and temporal factors showed higher incidence rate ratios (IRRs) for severe outcomes in the most deprived areas compared to the least. We note higher IRRs for severe outcomes for all non-white relative to white ethnicities. The magnitude of IRRs for both deprivation and ethnicities declined from the wild-type to the omicron periods for severe outcomes. For infections, we observed IRRs above one for non-white ethnicities during the wild-type and alpha periods. Vaccination significantly reduced risks across all groups. For severe outcomes, preexisting health inequalities led to large and persistent disparities. For infections, measures must be structured with ethnicity and deprivation in mind early in a pandemic.

Disparities in SARS-CoV-2 Infection Among Arab Americans Living in Southeast Michigan

COVID-19 has disproportionately affected racial and ethnic minority groups in the USA, nevertheless, there is little research regarding how it impacted the Arab American (ArA) population. In this retrospective study, we investigated potential disparities between ArA and Caucasian (CA) groups during the first 2 years of the pandemic. The study included 110,896 adult patients who were tested for SARS-CoV-2 at eight emergency departments (EDs) within a large health system in Southeast Michigan between March 1, 2020, and July 31, 2022. Univariate analysis revealed that ArA had greater odds (OR 2.16, 95% CI 2.03-2.29) of testing positive compared to CA and significantly lower odds (OR 0.69, 95% CI 0.62-0.77) of subsequent hospitalization compared to CA. There were no significant differences in hospital mortality, 30-day ED revisit, or 30-day rehospitalization. After adjusting for age, gender, health insurance type, and a variety of co-morbidities, ArA had significantly higher odds of infection (adjusted OR 2.10, 95% CI 1.97-2.25) compared to CA, while there were no differences in other outcomes. Our study showed significantly higher risk of COVID infections in ArA and necessitates further research to understand factors contributing to this finding and measures to decrease the infection risk in this population in future pandemics.

The causal effect of natural killer cells on COVID-19 infection, hospitalization and severity

BACKGROUND

Recent studies have suggested that alterations in natural killer (NK) cell function may contribute to the development of COVID-19. Additionally, dysregulated NK cells may increase susceptibility to COVID-19 and affect the severity of the infection.

PURPOSE

This study aimed to explore the causal relationship between NK cell-related immune traits and the risk of COVID-19 infection.

METHODS

A two-sample Mendelian randomization (MR) analysis was conducted to explore the causal relationship between NK cell-related immune traits and COVID-19. Exposure and outcome data were analyzed using the two-sample Mendelian Randomization (MR) method.

RESULTS

The results of the study suggest that there is a causal relationship between the absolute number of NK cells in COVID-19 infection and the risk of severe illness. The results also demonstrated that the morphological parameters are not causally related to COVID-19 infection but were causally related to COVID-19 hospitalization and COVID-19 severity.

CONCLUSION

This finding has important implications for our understanding of the pathophysiology of COVID-19 and the development of future therapies and interventions for this disease.

A Population-Based Epidemiologic Study of Symptomatic SARS-CoV-2 Infections and Fatalities in Brazilian Children over 3 Years

OBJECTIVE

To provide a comprehensive overview of the epidemiologic characteristics, outcomes, and risk factors of COVID-19-related deaths in children and adolescents in Brazil.

STUDY DESIGN

We conducted a population-based, retrospective cohort study that included all patients aged <18 years with laboratory-confirmed, symptomatic SARS-CoV-2 infection as registered in official Brazilian national surveillance systems for COVID-19 between February 2020 and February 2023. The primary outcome was COVID-19-related deaths. Odds ratios (ORs) of risk factors associated with death were estimated using multivariable logistic regression.

RESULTS

Over a 3-year period, 2 855 704 pediatric patients with symptomatic SARS-CoV-2 infection were registered in Brazil. Of these, 59 179 (2.1%) were hospitalized, 13 844 (0.48%) were admitted to the intensive care unit, and 4943 (0.17%) received mechanical ventilation. A total of 4740 (0.17%) patients had fatal outcomes. The case fatality rate increased to 7.9% among patients who required hospitalization; 2102 (44.3%) patients who died did not receive advanced critical support. Notably, 2 (65%, 95% CI 58-71) or 3 doses (86%, 95% CI 81-89) of the vaccine provided strong protection against death. The following adjusted covariates were significantly associated with increased odds of death: age (0-4 and 11-17 years), ethnicity (Brown and Indigenous), region (Northeast or North), dyspnea, nosocomial infection, and comorbidities. Conversely, living in the South or Central-West regions, admission in the later period of the pandemic, and receiving a vaccine were all associated with protection against death.

CONCLUSIONS

Our findings suggest that a complex interplay between individual factors and social inequities has shaped the impact of COVID-19 on Brazilian children and adolescents.

Neighbourhood immigrant density and COVID-19 infection and hospitalisation among healthcare workers in Sweden: a register-based observational study

Introduction

We investigated whether living in immigrant-dominated neighbourhoods constituted a risk factor for COVID-19 infection and hospitalisation among healthcare workers (HCWs) in Sweden, and if so, whether such exposure exacerbated the risk of COVID-19 among immigrant HCWs.

Methods

We used population-based register data from HCWs aged 20-62 years (N=86 187) resident in 14 Swedish municipalities (3 of which are Sweden's largest metropolitan cities) on 1 January 2020. Residential neighbourhoods of the HCWs were categorised into three groups: Swedish-dominated, mixed and immigrant-dominated. Multilevel mixed-effects survival regression was used for the association analyses, with control for relevant confounding variables. The results are reported as HRs, with 95% CIs.

Results

From 1 January 2020 to 30 September 2022, we recorded 39 746 COVID-19 infections and 860 COVID-19-related hospitalisations. Except during the first wave of the pandemic, living in immigrant-dominated (adjusted HR 0.98; 95% CI 0.94 to 1.01) or mixed (adjusted HR 1.02; 95% CI 0.99 to 1.05) neighbourhoods was not associated with COVID-19 infection, but living in these areas was associated with an increased risk of having COVID-19-related hospitalisation throughout the study period. Immigrant HCWs, regardless of their neighbourhood of residence, had approximately 2-fold higher risk of being hospitalised for COVID-19 than non-immigrant HCWs living in Swedish-dominated neighbourhoods.

Conclusions

Among HCWs in Sweden, neighbourhood immigrant density constituted a risk factor for COVID-19-related hospitalisation. However, immigrant HCWs had an elevated risk of COVID-19-related hospitalisation regardless of where they lived.

Metabolomic heterogeneity of ageing with ethnic diversity: a step closer to healthy ageing

INTRODUCTION

Outside of case-control settings, ethnicity specific changes in the human metabolome are understudied especially in community dwelling, ageing men. Characterising serum for age and ethnicity specific features can enable tailored therapeutics research and improve our understanding of the interplay between age, ethnicity, and metabolism in global populations.

OBJECTIVE

A metabolomics approach was adopted to profile serum metabolomes in middle-aged and elderly men of different ethnicities from the Northwest of England, UK.

METHODS

Serum samples from 572 men of White European (WE), South Asian (SA), and African-Caribbean (AC) ethnicities, ranging between 40 and 86 years were analysed. A combination of liquid chromatography (LC) and gas chromatography (GC) coupled to high-resolution mass spectrometry (MS) was used to generate the metabolomic profiles. Partial Least Squares Discriminant Analysis (PLS-DA) based classification models were built and validated using resampling via bootstrap analysis and permutation testing. Features were putatively annotated using public Human Metabolome Database (HMDB) and Golm Metabolite Database (GMD). Variable Importance in Projection (VIP) scores were used to determine features of interest, after which pathway enrichment analysis was performed.

RESULTS

Using profiles from our analysis we classify subjects by their ethnicity with an average correct classification rate (CCR) of 90.53% (LC-MS data) and 85.58% (GC-MS data). Similar classification by age (< 60 vs. ≥ 60 years) returned CCRs of 90.20% (LC-MS) and 71.13% (GC-MS). VIP scores driven feature selection revealed important compounds from putatively annotated lipids (subclasses including fatty acids and carboxylic acids, glycerophospholipids, steroids), organic acids, amino acid derivatives as key contributors to the classifications. Pathway enrichment analysis using these features revealed statistically significant perturbations in energy metabolism (TCA cycle), N-Glycan and unsaturated fatty acid biosynthesis linked pathways amongst others.

CONCLUSION

We report metabolic differences measured in serum that can be attributed to ethnicity and age in healthy population. These results strongly emphasise the need to consider confounding effects of inherent metabolic variations driven by ethnicity of participants in population-based metabolic profiling studies. Interpretation of energy metabolism, N-Glycan and fatty acid biosynthesis should be carefully decoupled from the underlying differences in ethnicity of participants.

COVID-19 and Mental Illnesses in Vaccinated and Unvaccinated People

Importance

Associations have been found between COVID-19 and subsequent mental illness in both hospital- and population-based studies. However, evidence regarding which mental illnesses are associated with COVID-19 by vaccination status in these populations is limited.

Objective

To determine which mental illnesses are associated with diagnosed COVID-19 by vaccination status in both hospitalized patients and the general population.

Design, Setting, and Participants

This study was conducted in 3 cohorts, 1 before vaccine availability followed during the wild-type/Alpha variant eras (January 2020-June 2021) and 2 (vaccinated and unvaccinated) during the Delta variant era (June-December 2021). With National Health Service England approval, OpenSAFELY-TPP was used to access linked data from 24 million people registered with general practices in England using TPP SystmOne. People registered with a GP in England for at least 6 months and alive with known age between 18 and 110 years, sex, deprivation index information, and region at baseline were included. People were excluded if they had COVID-19 before baseline. Data were analyzed from July 2022 to June 2024.

Exposure

Confirmed COVID-19 diagnosis recorded in primary care secondary care, testing data, or the death registry.

Main Outcomes and Measures

Adjusted hazard ratios (aHRs) comparing the incidence of mental illnesses after diagnosis of COVID-19 with the incidence before or without COVID-19 for depression, serious mental illness, general anxiety, posttraumatic stress disorder, eating disorders, addiction, self-harm, and suicide.

Results

The largest cohort, the pre-vaccine availability cohort, included 18 648 606 people (9 363 710 [50.2%] female and 9 284 896 [49.8%] male) with a median (IQR) age of 49 (34-64) years. The vaccinated cohort included 14 035 286 individuals (7 308 556 [52.1%] female and 6 726 730 [47.9%] male) with a median (IQR) age of 53 (38-67) years. The unvaccinated cohort included 3 242 215 individuals (1 363 401 [42.1%] female and 1 878 814 [57.9%] male) with a median (IQR) age of 35 (27-46) years. Incidence of most outcomes was elevated during weeks 1 through 4 after COVID-19 diagnosis, compared with before or without COVID-19, in each cohort. Incidence of mental illnesses was lower in the vaccinated cohort compared with the pre-vaccine availability and unvaccinated cohorts: aHRs for depression and serious mental illness during weeks 1 through 4 after COVID-19 were 1.93 (95% CI, 1.88-1.98) and 1.49 (95% CI, 1.41-1.57) in the pre-vaccine availability cohort and 1.79 (95% CI, 1.68-1.90) and 1.45 (95% CI, 1.27-1.65) in the unvaccinated cohort compared with 1.16 (95% CI, 1.12-1.20) and 0.91 (95% CI, 0.85-0.98) in the vaccinated cohort. Elevation in incidence was higher and persisted longer after hospitalization for COVID-19.

Conclusions and Relevance

In this study, incidence of mental illnesses was elevated for up to a year following severe COVID-19 in unvaccinated people. These findings suggest that vaccination may mitigate the adverse effects of COVID-19 on mental health.

COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys

BACKGROUND

Understanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour during an infectious disease outbreak can help to protect vulnerable populations and guide equity-driven interventions. The COVID-19 pandemic probably exerted different stresses on individuals in different sociodemographic groups and ensuring fair access to and usage of COVID-19 tests was a crucial element of England's testing programme. We aimed to investigate the relationship between sociodemographic factors and COVID-19 testing behaviours in England during the COVID-19 pandemic.

METHODS

We did a population-based study of COVID-19 testing behaviours with mass COVID-19 testing data for England and data from community prevalence surveillance surveys (REACT-1 and ONS-CIS) from Oct 1, 2020, to March 30, 2022. We used mass testing data for lateral flow device (LFD; data for approximately 290 million tests performed and reported) and PCR (data for approximately 107 million tests performed and returned from the laboratory) tests made available for the general public and provided by date and self-reported age and ethnicity at the lower tier local authority (LTLA) level. We also used publicly available data on mean population size estimates for individual LTLAs, and data on ethnic groups, age groups, and deprivation indices for LTLAs. We did not have access to REACT-1 or ONS-CIS prevalence data disaggregated by sex or gender. Using a mechanistic causal model to debias the PCR testing data, we obtained estimates of weekly SARS-CoV-2 prevalence by both self-reported ethnic groups and age groups for LTLAs in England. This approach to debiasing the PCR (or LFD) testing data also estimated a testing bias parameter defined as the odds of testing in infected versus not infected individuals, which would be close to zero if the likelihood of test seeking (or seeking and reporting) was the same regardless of infection status. With confirmatory PCR data, we estimated false positivity rates, sensitivity, specificity, and the rate of decline in detection probability subsequent to reporting a positive LFD for PCR tests by sociodemographic groups. We also estimated the daily incidence, allowing us to calculate the fraction of cases captured by the testing programme.

FINDINGS

From March, 2021 onwards, individuals in the most deprived regions reported approximately half as many LFD tests per capita as individuals in the least deprived areas (median ratio 0·50 [IQR 0·44-0·54]). During the period October, 2020, to June, 2021, PCR testing patterns showed the opposite trend, with individuals in the most deprived areas performing almost double the number of PCR tests per capita than those in the least deprived areas (1·8 [1·7-1·9]). Infection prevalences in Asian or Asian British individuals were considerably higher than those of other ethnic groups during the alpha (B.1.1.7) and omicron (B.1.1.529) BA.1 waves. Our estimates indicate that the England Pillar 2 COVID-19 testing programme detected 26-40% of all cases (including asymptomatic cases) over the study period with no consistent differences by deprivation levels or ethnic groups. Testing biases for PCR were generally higher than those for LFDs, in line with the general policy of symptomatic and asymptomatic use of these tests. Deprivation and age were associated with testing biases on average; however, the uncertainty intervals overlapped across deprivation levels, although the age-specific patterns were more distinct. We also found that ethnic minorities and older individuals were less likely to use confirmatory PCR tests through most of the pandemic and that delays in reporting a positive LFD test were possibly longer in populations self-reporting as "Black; African; Black British or Caribbean".

INTERPRETATION

Differences in testing behaviours across sociodemographic groups might be reflective of the higher costs of self-isolation to vulnerable populations, differences in test accessibility, differences in digital literacy, and differing perceptions about the utility of tests and risks posed by infection. This study shows how mass testing data can be used in conjunction with surveillance surveys to identify gaps in the uptake of public health interventions both at fine-scale levels and across sociodemographic groups. It provides a framework for monitoring local interventions and yields valuable lessons for policy makers in ensuring an equitable response to future pandemics.

FUNDING

UK Health Security Agency.

An intelligent garment for long COVID-19 real-time monitoring

As monitoring and diagnostic tools for long COVID-19 cases, wearable systems and supervised learning-based medical image analysis have proven to be useful. Current research on these two technical roadmaps has various drawbacks, despite their respective benefits. Wearable systems allow only the real-time monitoring of physiological parameters (heart rate, temperature, blood oxygen saturation, or SpO2). Therefore, they are unable to conduct in-depth investigations or differentiate COVID-19 from other illnesses that share similar symptoms. Medical image analysis using supervised learning-based models can be used to conduct in-depth analyses and provide precise diagnostic decision support. However, these methods are rarely used for real-time monitoring. In this regard, we present an intelligent garment combining the precision of supervised learning-based models with real-time monitoring capabilities of wearable systems. Given the relevance of electrocardiogram (ECG) signals to long COVID-19 symptom severity, an explainable data fusion strategy based on multiple machine learning models uses heart rate, temperature, SpO2, and ECG signal analysis to accurately assess the patient's health status. Experiments show that the proposed intelligent garment achieves an accuracy of 97.5 %, outperforming most of the existing wearable systems. Furthermore, it was confirmed that the two physiological indicators most significantly affected by the presence of long COVID-19 were SpO2 and the ST intervals of ECG signals.

Ethico-racial positioning in campaigns for COVID-19 research and vaccination featuring public figures

This article analyses a set of videos which featured public figures encouraging racially minoritised people in the UK to take the COVID-19 vaccine or get involved in related research. As racially targeted health communication has both potentially beneficial and problematic consequences, it is important to examine this uniquely high-profile case. Using a purposive sample of 10 videos, our thematic content analysis aimed to reveal how racially minoritised people were represented and the types of concerns about the vaccine that were expressed. We found representations of racialised difference that centred on 'community' and invoked shared social experiences. The expressed concerns centred on whether ethnic difference was accounted for in the vaccine's design and development, plus the overarching issue of trust. Our analysis adopts and develops the concept of 'racialisation'; we explore how 'mutuality' underpinned normative calls to action ('ethico-racial imperatives') and how the videos 'responsibilised' racially minoritised people. We discuss two points of tension in this case: the limitations for addressing the causes of mistrust and the risks of reductivism that accompanied the ambiguous notion of community. Our analysis develops scholarship on racialisation in health contexts and provides public health practitioners with insights into the socio-political considerations of racially targeted communications.

Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence

Background

Depression is one of the most significant public health issues, but evidence of geographic patterns and trends of depression is limited. We aimed to examine the spatio-temporal patterns and trends of depression prevalence among adults in a nationwide longitudinal spatial study in England and evaluate the influence of neighbourhood socioeconomic deprivation in explaining patterns.

Methods

Information on recorded depression prevalence was obtained from the indicator Quality and Outcomes Framework: Depression prevalence that measured the annual percentage of adults diagnosed with depression for Lower Super Output Areas (LSOA) from 2011 to 2022. We applied Cluster and Outlier Analysis using the Local Moran's I algorithm. Local effects of deprivation on depression in 2020 examined with Geographically Weighted Regression (GWR). Inequalities in recorded prevalence were presented using Prevalence Rate Ratios (PRR).

Results

The North West Region of England had the highest concentration of High-High clusters of depression, with 17.4% of the area having high values surrounded by high values in both space and time and the greatest percentage of areas with a high rate of increase (43.1%). Inequalities widened among areas with a high rate of increase in prevalence compared to those with a lower rate of increase, with the PRR increasing from 1.66 (99% CI 1.61-1.70) in 2011 to 1.81 (99% CI 1.76-1.85) by 2022. Deprivation explained 3%-39% of the variance in depression in 2020 across the country.

Conclusions

It is crucial to monitor depression's spatial patterns and trends and investigate mechanisms of mental health inequalities. Our findings can help identify priority areas and target prevention and intervention strategies in England. Evaluating mental health interventions in different geographic contexts can provide valuable insights to policymakers on the most effective and context-sensitive strategies, enabling them to allocate resources towards preventing the worsening of mental health inequalities.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study

INTRODUCTION

Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation.

METHODS

This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression.

RESULTS

Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study.

DISCUSSION

Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

Socioeconomic inequalities in cardiovascular disease: a causal perspective

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Pandemic phase-related racial and ethnic disparities in COVID-19 positivity and outcomes among patients presenting to emergency departments during the first two pandemic waves in the USA

BACKGROUND

In many countries including the USA, the UK and Canada, the impact of COVID-19 on people of colour has been disproportionately high but examination of disparities in patients presenting to ED has been limited. We assessed racial and ethnic differences in COVID-19 positivity and outcomes in patients presenting to EDs in the USA, and the effect of the phase of the pandemic on these outcomes.

METHODS

This is a retrospective cohort study of adult patients tested for COVID-19 during, or 14 days prior to, the index ED visit in 2020. Data were obtained from the National Registry of Suspected COVID-19 in Emergency Care network which has data from 155 EDs across 27 US states. Hierarchical models were used to account for clustering by hospital. The outcomes included COVID-19 diagnosis, hospitalisation at index visit, subsequent hospitalisation within 30 days and 30-day mortality. We further stratified the analysis by time period (early phase: March-June 2020; late phase: July-September 2020).

RESULTS

Of the 26 111 adult patients, 38% were non-Hispanic White (NHW), 29% Black, 20% Hispanic/Latino, 3% Asian and 10% all others; half were female. The median age was 56 years (IQR 40-69), and 53% were diagnosed with COVID-19; of those, 59% were hospitalised at index visit. Of those discharged from ED, 47% had a subsequent hospitalisation in 30 days. Hispanic/Latino patients had twice (adjusted OR (aOR) 2.3; 95% CI 1.8 to 3.0) the odds of COVID-19 diagnosis than NHW patients, after adjusting for age, sex and comorbidities. Black, Asian and other minority groups also had higher odds of being diagnosed (compared with NHW patients). On stratification, this association was observed in both phases for Hispanic/Latino patients. Hispanic/Latino patients had lower odds of hospitalisation at index visit, but when stratified, this effect was only observed in early phase. Subsequent hospitalisation was more likely in Asian patients (aOR 3.1; 95% CI 1.1 to 8.7) in comparison with NHW patients. Subsequent ED visit was more likely in Blacks and Hispanic/Latino patients in late phase.

CONCLUSION

We found significant differences in ED outcomes that are not explained by comorbidity burden. The gap decreased but persisted during the later phase in 2020.

State variation in neighborhood COVID-19 burden across the United States

BACKGROUND

A lack of fine, spatially-resolute case data for the U.S. has prevented the examination of how COVID-19 infection burden has been distributed across neighborhoods, a key determinant of both risk and resilience. Without more spatially resolute data, efforts to identify and mitigate the long-term fallout from COVID-19 in vulnerable communities will remain difficult to quantify and intervene on.

METHODS

We leveraged spatially-referenced data from 21 states collated through the COVID Neighborhood Project to examine the distribution of COVID-19 cases across neighborhoods and states in the U.S. We also linked the COVID-19 case data with data on the neighborhood social environment from the National Neighborhood Data Archive. We then estimated correlations between neighborhood COVID-19 burden and features of the neighborhood social environment.

RESULTS

We find that the distribution of COVID-19 at the neighborhood-level varies within and between states. The median case count per neighborhood (coefficient of variation (CV)) in Wisconsin is 3078.52 (0.17) per 10,000 population, indicating a more homogenous distribution of COVID-19 burden, whereas in Vermont the median case count per neighborhood (CV) is 810.98 (0.84) per 10,000 population. We also find that correlations between features of the neighborhood social environment and burden vary in magnitude and direction by state.

CONCLUSIONS

Our findings underscore the importance that local contexts may play when addressing the long-term social and economic fallout communities will face from COVID-19.

COVID-19 among Black people in Canada: a scoping review

INTRODUCTION

The COVID-19 pandemic exacerbated health inequities worldwide. Research conducted in Canada shows that Black populations were disproportionately exposed to COVID-19 and more likely than other ethnoracial groups to be infected and hospitalized. This scoping review sought to map out the nature and extent of current research on COVID-19 among Black people in Canada.

METHODS

Following a five-stage methodological framework for conducting scoping reviews, studies exploring the effects of the COVID-19 pandemic on Black people in Canada, published up to May 2023, were retrieved through a systematic search of seven databases. Of 457 identified records, 124 duplicates and 279 additional records were excluded after title and abstract screening. Of the remaining 54 articles, 39 were excluded after full-text screening; 2 articles were manually picked from the reference lists of the included articles. In total, 17 articles were included in this review.

RESULTS

Our review found higher rates of COVID-19 infections and lower rates of COVID-19 screening and vaccine uptake among Black Canadians due to pre-COVID-19 experiences of institutional and structural racism, health inequities and a mistrust of health care professionals that further impeded access to health care. Misinformation about COVID-19 exacerbated mental health issues among Black Canadians.

CONCLUSIONS

Our findings suggest the need to address social inequities experienced by Black Canadians, particularly those related to unequal access to employment and health care. Collecting race-based data on COVID-19 could inform policy formulation to address racial discrimination in access to health care, quality housing and employment, resolve inequities and improve the health and well-being of Black people in Canada.

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.

Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium

Introduction

COVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often subject to considerable heterogeneity. In this study, we aim to investigate the association between various socio-demographic factors and the complexity of the COVID-19 curve as quantified through its fractal dimension.

Methods

We collected population indicators data (ethnic composition, socioeconomic status, number of inhabitants, population density, the older adult population proportion, vaccination rate, satisfaction, and trust in the government) at the level of the statistical sector in Belgium. We compared these data with fractal dimension indicators of COVID-19 incidence between 1 January - 31 December 2021 using canonical correlation analysis.

Results

Our results showed that these population indicators have a significant association with COVID-19 incidences, with the highest explanatory and predictive power coming from the number of inhabitants, population density, and ethnic composition.

Conclusion

It is important to monitor these population indicators during a pandemic, especially when dealing with targeted interventions for a specific population.

Impact of age, race, and family history on COVID-19-related changes in breast cancer screening among the Boston mammography cohort study

PURPOSE

We studied women enrolled in the Boston Mammography Cohort Study to investigate whether subgroups defined by age, race, or family history of breast cancer experienced differences in the incidence of screening or diagnostic imaging rates during the COVID-19 lockdown and had slower rebound in the incidence of these rates during reopening.

METHODS

We compared the incidence of monthly breast cancer screening and diagnostic imaging rates over during the pre-COVID-19 (January 2019-February 2020), lockdown (March-May 2020), and reopening periods (June-December 2020), and tested for differences in the monthly incidence within the same period by age (< 50 vs ≥ 50), race (White vs non-White), and first-degree family history of breast cancer (yes vs no).

RESULTS

Overall, we observed a decline in breast cancer screening and diagnostic imaging rates over the three time periods (pre-COVID-19, lockdown, and reopening). The monthly incidence of breast cancer screening rates for women age ≥ 50 was 5% higher (p = 0.005) in the pre-COVID-19 period (January 2019-February 2020) but was 19% lower in the reopening phase (June-December 2020) than that of women aged < 50 (p < 0.001). White participants had 36% higher monthly incidence of breast cancer diagnostic imaging rates than non-White participants (p = 0.018).

CONCLUSION

The rebound in screening was lower in women age ≥ 50 and lower in non-White women for diagnostic imaging. Careful attention must be paid as the COVID-19 recovery continues to ensure equitable resumption of care.

Physical Activity Message Framing and Ethnicity Before and During COVID-19

People of Black ethnicities are well known to be disproportionately burdened by coronavirus and have poorer health outcomes. Public health messages encouraged physical activity during the pandemic as it is evidenced to positively affect the immune system, however people of Black ethnicities are often reported as failing to achieve the recommended daily amount. Health message framing during COVID-19 specifically in relation to ethnicity and physical activity motivation has yet to be investigated. Two studies examined message frame effect on physical activity motivation prior to and at the onset of the pandemic and how this differed by ethnicity. Gain framed messages were found to positively affect physical activity motivation pre-COVID-19 and during the pandemic fear framed messages were found to positively affect physical activity motivation. Neither of these effects differed by ethnicity. Implications for future physical activity health message framing are discussed.

Where are you really from? Racial microaggressions and how to be an ally or active bystander

Racial microaggressions are often subtle and frequent occurences in the lives of people from marginalised racial groups. There is a broad lack of acknowledgement that they exist and when perpetrators are confronted, victims are often met with defensiveness or dismissal. However, the impacts on the physical and mental health of the victims make it essential that clinicians understand not only the concept of racial microaggressions but also how they may be challenged and addressed. There is no single way to address microaggressions, but the authors propose some ways to identify and tackle them in the medical setting and beyond. It is hoped that this will encourage allyship and empower those who are bystanders to become more actively involved.

Racial differences in COVID-19 severity associated with history of substance use disorders and overdose: Findings from multi-site electronic health records in New York City

Substance use disorders (SUD) are associated with increased risk of worse COVID-19 outcomes. Likewise, racial/ethnic minority patients experience greater risk of severe COVID-19 disease compared to white patients. Providers should understand the role of race and ethnicity as an effect modifier on COVID-19 severity among individuals with SUD. This retrospective cohort study assessed patient race/ethnicity as an effect modifier of the risk of severe COVID-19 disease among patients with histories of SUD and overdose. We used merged electronic health record data from 116,471 adult patients with a COVID-19 encounter between March 2020 and February 2021 across five healthcare systems in New York City. Exposures were patient histories of SUD and overdose. Outcomes were risk of COVID-19 hospitalization and subsequent COVID-19-related ventilation, acute kidney failure, sepsis, and mortality. Risk factors included patient age, sex, and race/ethnicity, as well as medical comorbidities associated with COVID-19 severity. We tested for interaction between SUD and patient race/ethnicity on COVID-19 outcomes. Findings showed that Non-Hispanic Black, Hispanic/Latino, and Asian/Pacific Islander patients experienced a higher prevalence of all adverse COVID-19 outcomes compared to non-Hispanic white patients. Past-year alcohol (OR 1.24 [1.01-1.53]) and opioid use disorders (OR 1.91 [1.46-2.49]), as well as overdose history (OR 4.45 [3.62-5.46]), were predictive of COVID-19 mortality, as well as other adverse COVID-19 outcomes. Among patients with SUD, significant differences in outcome risk were detected between patients of different race/ethnicity groups. Findings indicate that providers should consider multiple dimensions of vulnerability to adequately manage COVID-19 disease among populations with SUDs.

Racial disparities in lifestyle habits and dietary patterns in university students during the COVID-19 pandemic

Objectives

To evaluate lifestyle habits and dietary patterns among university students during the COVID-19 pandemic and their association with skin color.

Methods

This cross-sectional study was conducted with 1315 undergraduate students from a public higher education institution. Sociodemographic characteristics, lifestyle habits, and food consumption were collected. Factor analysis was used to identify dietary patterns and multivariate logistic regression was conducted to estimate the associations between race/skin color and outcomes.

Results

Black individuals were less likely to show behaviors associated with the use of cigarettes or tobacco products (OR = 0.61; 95% CI 0.42-0.89). However, black individuals with higher income (greater than, or equal to one minimum wage per person) were less likely to show behaviors associated with illicit drug use (OR = 0.54; 95% CI 0.31-0.96), use of cigarettes or tobacco products (OR = 0.46; 95% CI 0.24-0.87) and alcohol consumption (OR = 0.64; CI 95% 0.42-0.98). In addition, individuals of race/skin color black with lower income (less than one minimum wage per person) showed decreased consumption of vegetables (OR = 0.68; CI 95% 0.48-0.96).

Conclusions

Black college students with higher income were less likely to show undesirable behaviors related to the use of psychoactive substances. In contrast, individuals with lower income had lower consumption of foods from the vegetable group, which can be considered an unfavorable health-related behavior.

Understanding comorbidities and health disparities related to COVID-19: a comprehensive study of 776 936 cases and 1 362 545 controls in the state of Indiana, USA

Objective

To characterize COVID-19 patients in Indiana, United States, and to evaluate their demographics and comorbidities as risk factors to COVID-19 severity.

Materials and Methods

EHR data of 776 936 COVID-19 cases and 1 362 545 controls were collected from the COVID-19 Research Data Commons (CoRDaCo) in Indiana. Data regarding county population and per capita income were obtained from the US Census Bureau. Statistical analysis was conducted to determine the association of demographic and clinical variables with COVID-19 severity. Predictive analysis was conducted to evaluate the predictive power of CoRDaCo EHR data in determining COVID-19 severity.

Results

Chronic obstructive pulmonary disease, cardiovascular disease, and type 2 diabetes were found in 3.49%, 2.59%, and 4.76% of the COVID-19 patients, respectively. Such COVID-19 patients have significantly higher ICU admission rates of 10.23%, 14.33%, and 11.11%, respectively, compared to the entire COVID-19 patient population (1.94%). Furthermore, patients with these comorbidities have significantly higher mortality rates compared to the entire COVID-19 patient population. Health disparity analysis suggests potential health disparities among counties in Indiana. Predictive analysis achieved F1-scores of 0.8011 and 0.7072 for classifying COVID-19 cases versus controls and ICU versus non-ICU cases, respectively.

Discussion

Black population in Indiana was more adversely affected by COVID-19 than the White population. This is consistent to findings from existing studies. Our findings also indicate other health disparities in terms of demographic and economic factors.

Conclusion

This study characterizes the relationship between comorbidities and COVID-19 outcomes with respect to ICU admission across a large COVID-19 patient population in Indiana.

Ethnic differences in cellular and humoral immune responses to SARS-CoV-2 vaccination in UK healthcare workers: a cross-sectional analysis

Background

Few studies have compared SARS-CoV-2 vaccine immunogenicity by ethnic group. We sought to establish whether cellular and humoral immune responses to SARS-CoV-2 vaccination differ according to ethnicity in UK Healthcare workers (HCWs).

Methods

In this cross-sectional analysis, we used baseline data from two immunological cohort studies conducted in HCWs in Leicester, UK. Blood samples were collected between March 3, and September 16, 2021. We excluded HCW who had not received two doses of SARS-CoV-2 vaccine at the time of sampling and those who had serological evidence of previous SARS-CoV-2 infection. Outcome measures were SARS-CoV-2 spike-specific total antibody titre, neutralising antibody titre and ELISpot count. We compared our outcome measures by ethnic group using univariable (t tests and rank-sum tests depending on distribution) and multivariable (linear regression for antibody titres and negative binomial regression for ELISpot counts) tests. Multivariable analyses were adjusted for age, sex, vaccine type, length of interval between vaccine doses and time between vaccine administration and sample collection and expressed as adjusted geometric mean ratios (aGMRs) or adjusted incidence rate ratios (aIRRs). To assess differences in the early immune response to vaccination we also conducted analyses in a subcohort who provided samples between 14 and 50 days after their second dose of vaccine.

Findings

The total number of HCWs in each analysis were 401 for anti-spike antibody titres, 345 for neutralising antibody titres and 191 for ELISpot. Overall, 25.4% (19.7% South Asian and 5.7% Black/Mixed/Other) were from ethnic minority groups. In analyses including the whole cohort, neutralising antibody titres were higher in South Asian HCWs than White HCWs (aGMR 1.47, 95% CI [1.06-2.06], P = 0.02) as were T cell responses to SARS-CoV-2 S1 peptides (aIRR 1.75, 95% CI [1.05-2.89], P = 0.03). In a subcohort sampled between 14 and 50 days after second vaccine dose, SARS-CoV-2 spike-specific antibody and neutralising antibody geometric mean titre (GMT) was higher in South Asian HCWs compared to White HCWs (9616 binding antibody units (BAU)/ml, 95% CI [7178-12,852] vs 5888 BAU/ml [5023-6902], P = 0.008 and 2851 95% CI [1811-4487] vs 1199 [984-1462], P < 0.001 respectively), increments which persisted after adjustment (aGMR 1.26, 95% CI [1.01-1.58], P = 0.04 and aGMR 2.01, 95% CI [1.34-3.01], P = 0.001). SARS-CoV-2 ELISpot responses to S1 and whole spike peptides (S1 + S2 response) were higher in HCWs from South Asian ethnic groups than those from White groups (S1: aIRR 2.33, 95% CI [1.09-4.94], P = 0.03; spike: aIRR, 2.04, 95% CI [1.02-4.08]).

Interpretation

This study provides evidence that, in an infection naïve cohort, humoral and cellular immune responses to SARS-CoV-2 vaccination are stronger in South Asian HCWs than White HCWs. These differences are most clearly seen in the early period following vaccination. Further research is required to understand the underlying mechanisms, whether differences persist with further exposure to vaccine or virus, and the potential impact on vaccine effectiveness.

Funding

DIRECT and BELIEVE have received funding from UK Research and Innovation (UKRI) through the COVID-19 National Core Studies Immunity (NCSi) programme (MC_PC_20060).

Dynamic Trends in Sociodemographic Disparities and COVID-19 Morbidity and Mortality—A Nationwide Study during Two Years of a Pandemic

Social epidemiological research has documented that health outcomes, such as the risk of becoming diseased or dying, are closely tied to socioeconomic status. The aim of the current study was to investigate the impact of socioeconomic status on morbidity, hospitalization, and mortality outcomes throughout five waves of the pandemic amongst the Israeli population. A retrospective archive study was conducted in Israel from March 2020 to February 2022 in which data were obtained from the Israeli Ministry of Health’s (MOH) open COVID-19 database. Our findings, though requiring careful and cautious interpretation, indicate that the socioeconomic gradient patterns established in previous COVID-19 literature are not applicable to Israel throughout the five waves of the pandemic. The conclusions of this study indicate a much more dynamic and complex picture, where there is no single group that dominates the realm of improved outcomes or bears the burden of disease with respect to morbidity, hospitalization, and mortality. We show that health trends cannot necessarily be generalized to all countries and are very much dynamic and contingent on the socio-geographical context and must be thoroughly examined throughout distinct communities with consideration of the specific characteristics of the disease. Furthermore, the implications of this study include the importance of identifying the dynamic interplay and interactions of sociodemographic characteristics and health behavior in order to enhance efforts toward achieving improved health outcomes by policymakers and researchers.

Public health interventions successfully mitigated multiple incursions of SARS-CoV-2 Delta variant in the Australian Capital Territory

The COVID-19 pandemic has presented a unique opportunity to understand how real-time pathogen genomics can be used for large-scale outbreak investigations. On 12 August 2021, the Australian Capital Territory (ACT) detected an incursion of the SARS-CoV-2 Delta (B.1.617.2) variant. Prior to this date, SARS-CoV-2 had been eliminated locally since 7 July 2020. Several public health interventions were rapidly implemented in response to the incursion, including a territory-wide lockdown and comprehensive contact tracing. The ACT has not previously used pathogen genomics at a population level in an outbreak response; therefore, this incursion also presented an opportunity to investigate the utility of genomic sequencing to support contact tracing efforts in the ACT. Sequencing of >75% of the 1793 laboratory-confirmed cases during the 3 months following the initial notification identified at least 13 independent incursions with onwards spread in the community. Stratification of cases by genomic cluster revealed that distinct cohorts were affected by the different incursions. Two incursions resulted in most of the community transmission during the study period, with persistent transmission in vulnerable sections of the community. Ultimately, both major incursions were successfully mitigated through public health interventions, including COVID-19 vaccines. The high rates of SARS-CoV-2 sequencing in the ACT and the relatively small population size facilitated detailed investigations of the patterns of virus transmission, revealing insights beyond those gathered from traditional contact tracing alone. Genomic sequencing was critical to disentangling complex transmission chains to target interventions appropriately.

Trends in Risk Factors and Symptoms Associated With SARS-CoV-2 and Rhinovirus Test Positivity in King County, Washington, June 2020 to July 2022

IMPORTANCE

Few US studies have reexamined risk factors for SARS-CoV-2 positivity in the context of widespread vaccination and new variants or considered risk factors for cocirculating endemic viruses, such as rhinovirus.

OBJECTIVES

To evaluate how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these with the risk factors associated with rhinovirus test positivity.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study used a test-negative design with multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 25-month period. The study was conducted among symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study in King County, Washington, from June 2020 to July 2022.

EXPOSURES

Self-reported data for 15 demographic and health behavior variables and 16 symptoms.

MAIN OUTCOMES AND MEASURES

Reverse transcription-polymerase chain reaction-confirmed SARS-CoV-2 or rhinovirus infection.

RESULTS

Analyses included data from 23 498 individuals. The median (IQR) age of participants was 34.33 (22.42-45.08) years, 13 878 (59.06%) were female, 4018 (17.10%) identified as Asian, 654 (2.78%) identified as Black, and 2193 (9.33%) identified as Hispanic. Close contact with an individual with SARS-CoV-2 (adjusted odds ratio [aOR], 3.89; 95% CI, 3.34-4.57) and loss of smell or taste (aOR, 3.49; 95% CI, 2.77-4.41) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated individual with SARS-CoV-2 (aOR, 2.03; 95% CI, 1.56-2.79) was associated with lower odds of testing positive than contact with an unvaccinated individual with SARS-CoV-2 (aOR, 4.04; 95% CI, 2.39-7.23). Sore throat was associated with Omicron infection (aOR, 2.27; 95% CI, 1.68-3.20) but not Delta infection. Vaccine effectiveness for participants fully vaccinated with a booster dose was 93% (95% CI, 73%-100%) for Delta, but not significant for Omicron. Variables associated with rhinovirus test positivity included being younger than 12 years (aOR, 3.92; 95% CI, 3.42-4.51) and experiencing a runny or stuffy nose (aOR, 4.58; 95% CI, 4.07-5.21). Black race, residing in south King County, and households with 5 or more people were significantly associated with both SARS-CoV-2 and rhinovirus test positivity.

CONCLUSIONS AND RELEVANCE

In this case-control study of 23 498 symptomatic individuals, estimated risk factors and symptoms associated with SARS-CoV-2 infection changed over time. There was a shift in reported symptoms between the Delta and Omicron variants as well as reductions in the protection provided by vaccines. Racial and sociodemographic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection. Trends in testing behavior and availability may influence these results.

Data needs for integrated economic-epidemiological models of pandemic mitigation policies

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

Longitudinal Aging Study Amsterdam COVID-19 exposure index: a cross-sectional analysis of the impact of the pandemic on daily functioning of older adults

OBJECTIVES

The aim of this study was to develop an index to measure older adults' exposure to the COVID-19 pandemic and to study its association with various domains of functioning.

DESIGN

Cross-sectional study.

SETTING

The Longitudinal Aging Study Amsterdam (LASA), a cohort study in the Netherlands.

PARTICIPANTS

Community-dwelling older adults aged 62-102 years (n=1089) who participated in the LASA COVID-19 study (June-September 2020), just after the first wave of the pandemic.

PRIMARY OUTCOME MEASURES

A 35-item COVID-19 exposure index with a score ranging between 0 and 1 was developed, including items that assess the extent to which the COVID-19 situation affected daily lives of older adults. Descriptive characteristics of the index were studied, stratified by several sociodemographic factors. Logistic regression analyses were performed to study associations between the exposure index and several indicators of functioning (functional limitations, anxiety, depression and loneliness).

RESULTS

The mean COVID-19 exposure index score was 0.20 (SD 0.10). Scores were relatively high among women and in the southern region of the Netherlands. In models adjusted for sociodemographic factors and prepandemic functioning (2018-2019), those with scores in the highest tertile of the exposure index were more likely to report functional limitations (OR: 2.24; 95% CI: 1.48 to 3.38), anxiety symptoms (OR: 3.14; 95% CI: 1.82 to 5.44), depressive symptoms (OR: 2.49; 95% CI: 1.55 to 4.00) and loneliness (OR: 2.97; 95% CI: 2.08 to 4.26) than those in the lowest tertile.

CONCLUSIONS

Among older adults in the Netherlands, higher exposure to the COVID-19 pandemic was associated with worse functioning in the physical, mental and social domain. The newly developed exposure index may be used to identify persons for whom targeted interventions are needed to maintain or improve functioning during the pandemic or postpandemic.

Longitudinal Aging Study Amsterdam COVID-19 exposure index: a cross-sectional analysis of the impact of the pandemic on daily functioning of older adults

OBJECTIVES

The aim of this study was to develop an index to measure older adults' exposure to the COVID-19 pandemic and to study its association with various domains of functioning.

DESIGN

Cross-sectional study.

SETTING

The Longitudinal Aging Study Amsterdam (LASA), a cohort study in the Netherlands.

PARTICIPANTS

Community-dwelling older adults aged 62-102 years (n=1089) who participated in the LASA COVID-19 study (June-September 2020), just after the first wave of the pandemic.

PRIMARY OUTCOME MEASURES

A 35-item COVID-19 exposure index with a score ranging between 0 and 1 was developed, including items that assess the extent to which the COVID-19 situation affected daily lives of older adults. Descriptive characteristics of the index were studied, stratified by several sociodemographic factors. Logistic regression analyses were performed to study associations between the exposure index and several indicators of functioning (functional limitations, anxiety, depression and loneliness).

RESULTS

The mean COVID-19 exposure index score was 0.20 (SD 0.10). Scores were relatively high among women and in the southern region of the Netherlands. In models adjusted for sociodemographic factors and prepandemic functioning (2018-2019), those with scores in the highest tertile of the exposure index were more likely to report functional limitations (OR: 2.24; 95% CI: 1.48 to 3.38), anxiety symptoms (OR: 3.14; 95% CI: 1.82 to 5.44), depressive symptoms (OR: 2.49; 95% CI: 1.55 to 4.00) and loneliness (OR: 2.97; 95% CI: 2.08 to 4.26) than those in the lowest tertile.

CONCLUSIONS

Among older adults in the Netherlands, higher exposure to the COVID-19 pandemic was associated with worse functioning in the physical, mental and social domain. The newly developed exposure index may be used to identify persons for whom targeted interventions are needed to maintain or improve functioning during the pandemic or postpandemic.

Same storm, different boats: the impact of COVID-19 on Black students and academic staff in UK and US higher education

The permanence of systemic racism in the UK and USA means that Black people are disadvantaged in myriad ways, including within the Academy. While the disproportionate impact of COVID-19, alongside the Black Lives Matter movement, has increased awareness of the challenges faced by Black communities, these issues remain, both in and beyond higher education. Furthermore, there is still a paucity of research individualising the experiences of Black people, who are often homogenised with other ethnic minority groups. This paper explores the impact of COVID-19 on UK and US Black students and academic staff, utilising a critical race theory (CRT) framework. Analysis revealed that Black students and staff experienced COVID-19 against the backdrop of racism as a "pandemic within a pandemic" (Laurencin and Walker, Cell Systems 11:9-10, 2020), including racial (re)traumatisation, loneliness and isolation. Other themes included precarious employment and exploitation. Recommendations are offered for penetrative interventions that can support Black students and staff in the wake of strained race relations neglecting their adverse experiences and a global pandemic.

Race, ethnicity and mortality in the United States during the first year of the COVID-19 pandemic: an assessment

The fact that a disproportionate share of the disease burden from COVID-19, including mortality, has been borne by racial and ethnic minority communities is well documented. The purpose of this paper is to reassess the "race/ethnicity effect" in COVID-19 mortality in the United States. Using an ecological regression framework and county-level data, the study aims to make two contributions. First, it estimates the race/ethnicity effect for all major racial/ethnic groups at four important junctures during the first year of the pandemic. In doing so, it seeks to provide the fullest possible picture of the nature and evolution of the race/ethnicity effect. Second, it estimates the race/ethnicity effect net of basic socioeconomic factors (SEF). This helps to identify the likely mechanisms through which the race/ethnicity effect operates. Racial/ethnic composition is flexibly measured in two ways-by percentage contributions to county population and by indicators of group plurality. The ecological regressions revealed a positive association between the size of three racial/ethnic groups-non-Hispanic Blacks, non-Hispanic American Indian and Alaskan Natives (AIAN) and Hispanics-and county mortality, although the association was stronger and more consistent for Blacks and AIANs. Furthermore, accounting for basic SEF had different impacts on the race/ethnicity-mortality association for the three groups. For Hispanics, it was almost fully mediated. For Blacks, it decreased but remained statistically significant [62-6% higher mortality associated with a 1-standard deviation increase in Black share of county population; 2.3-1.1 times higher mortality in the average Black plurality county]. For AIANs, it was largely unaffected or even increased [44-10% higher mortality associated with a 1-standard deviation increase in AIAN share; 6.2-1.8 times higher mortality in AIAN plurality county). For all groups, the race/ethnicity effect generally decreased as the pandemic wore on during the first year.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44155-022-00019-9.

Smart Hand Sanitisers in the Workplace: A Survey of Attitudes towards an Internet of Things Technology

An online survey was circulated to employees from a wide range of organisations to gauge attitudes towards the idea of using smart hand sanitisers in the workplace. The sanitisers are capable of real-time monitoring and providing feedback that varies according to the hand hygiene behaviour of users. In certain circumstances, the sanitisers can monitor individuals, making it possible to identify workers whose hand hygiene falls below a certain standard. The survey was circulated between July and August 2021 during the COVID-19 pandemic. Data gathered from 314 respondents indicated support for some features of the technology, but also indicated concern about invasions of privacy and the possibility of coercion. Attitudes towards the possible implementation of the technology varied significantly according to certain characteristics of the sample, but particularly with age. Respondents above the median age were more likely to support the use of data in ways that could facilitate the promotion and enforcement of hand hygiene practices.

SARS-CoV-2 seropositivity and COVID-19 among 5 years-old Amazonian children and their association with poverty and food insecurity

Background

The epidemiology of childhood SARS-CoV-2 infection and COVID-19-related illness remains little studied in high-transmission tropical settings, partly due to the less severe clinical manifestations typically developed by children and the limited availability of diagnostic tests. To address this knowledge gap, we investigate the prevalence and predictors of SARS-CoV-2 infection (either symptomatic or not) and disease in 5 years-old Amazonian children.

Methodology/Principal findings

We retrospectively estimated SARS-CoV-2 attack rates and the proportion of infections leading to COVID-19-related illness among 660 participants in a population-based birth cohort study in the Juruá Valley, Amazonian Brazil. Children were physically examined, tested for SARS-CoV-2 IgG and IgM antibodies, and had a comprehensive health questionnaire administered during a follow-up visit at the age of 5 years carried out in January or June-July 2021. We found serological evidence of past SARS-CoV-2 infection in 297 (45.0%; 95% confidence interval [CI], 41.2–48.9%) of 660 cohort participants, but only 15 (5.1%; 95% CI, 2.9–8.2%) seropositive children had a prior medical diagnosis of COVID-19 reported by their mothers or guardians. The period prevalence of clinically apparent COVID-19, defined as the presence of specific antibodies plus one or more clinical symptoms suggestive of COVID-19 (cough, shortness of breath, and loss of taste or smell) reported by their mothers or guardians since the pandemic onset, was estimated at 7.3% (95% CI, 5.4–9.5%). Importantly, children from the poorest households and those with less educated mothers were significantly more likely to be seropositive, after controlling for potential confounders by mixed-effects multiple Poisson regression analysis. Likewise, the period prevalence of COVID-19 was 1.8-fold (95%, CI 1.2–2.6-fold) higher among cohort participants exposed to food insecurity and 3.0-fold (95% CI, 2.8–3.5-fold) higher among those born to non-White mothers. Finally, children exposed to household and family contacts who had COVID-19 were at an increased risk of being SARS-CoV-2 seropositive and–even more markedly–of having had clinically apparent COVID-19 by the age of 5 years.

Conclusions/Significance

Childhood SARS-CoV-2 infection and COVID-19-associated illness are substantially underdiagnosed and underreported in the Amazon. Children in the most socioeconomically vulnerable households are disproportionately affected by SARS-CoV-2 infection and disease.

The epidemiology of childhood COVID-19 in the tropics remains a relatively neglected research topic, in part because SARS-CoV-2 typically causes fewer severe illnesses, hospitalizations, and deaths in children than in adults. Here we show that 45% of 660 participants in a birth cohort study in the Brazilian Amazon had SARS-CoV-2 antibodies at the age of 5 years, although only 5% of them reported previously diagnosed COVID-19 episodes–implying that as many as 8 in 9 SARS-CoV-2 infections had remained undiagnosed in these young children. Only 16% of the seropositive children had reportedly experienced cough, shortness of breath, and/or loss of taste or smell. The most socioeconomically vulnerable participants were more likely to have experienced SARS-CoV-2 infection and overt COVID-19 by the age of 5 years. Importantly, children exposed to household food insecurity, which affects 54% of our study participants, had their COVID-19 risk increased by 76%.

Social determinants related to COVID-19 infection

This study was aimed at identifying the social determinants related to COVID-19 infection in South Korea. This secondary analysis used data from the 2020 Community Health Survey, a nationwide sample taken to understand the health status of Korean residents. The participants were 220 970 adults 19 years of age or older. COVID-19-related social determinants were age, education level, marital status, household income, hypertension, eating habits, social support, and regional income. The risk of COVID-19 infection increased in those who were under 40 years, were high school graduates or higher, were single, had a household income over US$ 4166.7, ate breakfast 5-7 times a week, had three or more helpers during COVID-19, and lived in a region with above-average income. Hypertension reduced the risk of COVID-19 infection. In conclusion, adults with high socioeconomic activity showed a high risk for COVID-19 infection, which was assumed to include only adults living in residential housing in the community. Further studies are required to include adults living in long-term care or communal living facilities, known to be frequently infected with the corona virus.

Cancers and COVID-19 Risk: A Mendelian Randomization Study

Simple Summary

During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the causal effects of cancers on COVID-19 outcomes using the Mendelian randomization (MR) approach. No strong evidence was observed to support a causal role of cancer in COVID-19 development. Previous observational correlations between cancers and COVID-19 outcomes were likely confounded. Large and well-conducted epidemiological studies are required to determine whether cancers causally contribute to increased risk of COVID-19.

Abstract

Observational studies have shown increased COVID-19 risk among cancer patients, but the causality has not been proven yet. Mendelian randomization analysis can use the genetic variants, independently of confounders, to obtain causal estimates which are considerably less confounded. We aimed to investigate the causal associations of cancers with COVID-19 outcomes using the MR analysis. The inverse-variance weighted (IVW) method was employed as the primary analysis. Sensitivity analyses and multivariable MR analyses were conducted. Notably, IVW analysis of univariable MR revealed that overall cancer and twelve site-specific cancers had no causal association with COVID-19 severity, hospitalization or susceptibility. The corresponding p-values for the casual associations were all statistically insignificant: overall cancer (p = 0.34; p = 0.42; p = 0.69), lung cancer (p = 0.60; p = 0.37; p = 0.96), breast cancer (p = 0.43; p = 0.74; p = 0.43), endometrial cancer (p = 0.79; p = 0.24; p = 0.83), prostate cancer (p = 0.54; p = 0.17; p = 0.58), thyroid cancer (p = 0.70; p = 0.80; p = 0.28), ovarian cancer (p = 0.62; p = 0.96; p = 0.93), melanoma (p = 0.79; p = 0.45; p = 0.82), small bowel cancer (p = 0.09; p = 0.08; p = 0.19), colorectal cancer (p = 0.85; p = 0.79; p = 0.30), oropharyngeal cancer (p = 0.31; not applicable, NA; p = 0.80), lymphoma (p = 0.51; NA; p = 0.37) and cervical cancer (p = 0.25; p = 0.32; p = 0.68). Sensitivity analyses and multivariable MR analyses yielded similar results. In conclusion, cancers might have no causal effect on increasing COVID-19 risk. Further large-scale population studies are needed to validate our findings.

Associations between predicted vitamin D status, vitamin D intake, and risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity

BACKGROUND

Vitamin D may have a role in immune responses to viral infections. However, data on the association between vitamin D and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity have been limited and inconsistent.

OBJECTIVE

We examined the associations of predicted vitamin D status and intake with risk of SARS-CoV-2 infection and COVID-19 severity.

METHODS

We used data from periodic surveys (May 2020 to March 2021) within the Nurses' Health Study II. Among 39,315 participants, 1768 reported a positive test for SARS-CoV-2 infection. Usual vitamin D intake from foods and supplements were measured using a semiquantitative, pre-pandemic food-frequency questionnaire in 2015. Predicted 25-hydroxyvitamin D [25(OH)D] concentration were calculated based on a previously validated model including dietary and supplementary vitamin D intake, UV-B, and other behavioral predictors of vitamin D status.

RESULTS

Higher predicted 25(OH)D concentrations, but not vitamin D intake, were associated with a lower risk of SARS-CoV-2 infection. Comparing participants in the highest quintile of predicted 25(OH)D concentrations with the lowest, the multivariable-adjusted OR was 0.76 (95% CI: 0.58, 0.99; P-trend = 0.04). Participants in the highest quartile of UV-B (OR: 0.76; 95% CI: 0.66, 0.87; P-trend = 0.002) and UV-A (OR: 0.76; 95% CI: 0.66, 0.88; P-trend < 0.001) also had a lower risk of SARS-CoV-2 infection compared with the lowest. High intake of vitamin D from supplements (≥400 IU/d) was associated with a lower risk of hospitalization (OR: 0.51; 95% CI: 0.29, 0.91; P-trend = 0.04).

CONCLUSIONS

Our study provides suggestive evidence on the association between higher predicted circulating 25(OH)D concentrations and a lower risk of SARS-CoV-2 infection. Greater intake of vitamin D supplements was associated with a lower risk of hospitalization. Our data also support an association between exposure to UV-B or UV-A, independently of vitamin D and SARS-CoV-2 infection, so results for predicted 25(OH)D need to be interpreted cautiously.

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

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

A Narrative Review of the Evidence for Variations in Serum 25-Hydroxyvitamin D Concentration Thresholds for Optimal Health

Vitamin D3 has many important health benefits. Unfortunately, these benefits are not widely known among health care personnel and the general public. As a result, most of the world's population has serum 25-hydroxyvitamin D (25(OH)D) concentrations far below optimal values. This narrative review examines the evidence for the major causes of death including cardiovascular disease, hypertension, cancer, type 2 diabetes mellitus, and COVID-19 with regard to sub-optimal 25(OH)D concentrations. Evidence for the beneficial effects comes from a variety of approaches including ecological and observational studies, studies of mechanisms, and Mendelian randomization studies. Although randomized controlled trials (RCTs) are generally considered the strongest form of evidence for pharmaceutical drugs, the study designs and the conduct of RCTs performed for vitamin D have mostly been flawed for the following reasons: they have been based on vitamin D dose rather than on baseline and achieved 25(OH)D concentrations; they have involved participants with 25(OH)D concentrations above the population mean; they have given low vitamin D doses; and they have permitted other sources of vitamin D. Thus, the strongest evidence generally comes from the other types of studies. The general finding is that optimal 25(OH)D concentrations to support health and wellbeing are above 30 ng/mL (75 nmol/L) for cardiovascular disease and all-cause mortality rate, whereas the thresholds for several other outcomes appear to range up to 40 or 50 ng/mL. The most efficient way to achieve these concentrations is through vitamin D supplementation. Although additional studies are warranted, raising serum 25(OH)D concentrations to optimal concentrations will result in a significant reduction in preventable illness and death.

Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom

Worldwide, racial and ethnic minorities have been disproportionately impacted by COVID-19 with increased risk of infection, its related complications, and death. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy may result in differences in uptake. We performed a cohort study among U.S. and U.K. participants who volunteered to take part in the smartphone-based COVID Symptom Study (March 2020-February 2021) and used logistic regression to estimate odds ratios of vaccine hesitancy and uptake. In the U.S. (n = 87,388), compared to white participants, vaccine hesitancy was greater for Black and Hispanic participants and those reporting more than one or other race. In the U.K. (n = 1,254,294), racial and ethnic minority participants showed similar levels of vaccine hesitancy to the U.S. However, associations between participant race and ethnicity and levels of vaccine uptake were observed to be different in the U.S. and the U.K. studies. Among U.S. participants, vaccine uptake was significantly lower among Black participants, which persisted among participants that self-reported being vaccine-willing. In contrast, statistically significant racial and ethnic disparities in vaccine uptake were not observed in the U.K sample. In this study of self-reported vaccine hesitancy and uptake, lower levels of vaccine uptake in Black participants in the U.S. during the initial vaccine rollout may be attributable to both hesitancy and disparities in access.

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.

Knowledge barriers in a national symptomatic-COVID-19 testing programme

Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a University of Maryland survey administered to Facebook users (The Global COVID-19 Trends and Impact Survey [CTIS], N = 775,746). The proportion tested among individuals with incident test-qualifying symptoms rose from ~20% to ~75% from April to December 2020 in Zoe. Testing was lower with one vs more symptoms (72.9% vs 84.6% p<0.001), or short vs long symptom duration (69.9% vs 85.4% p<0.001). 40.4% of survey respondents did not identify all three test-qualifying symptoms. Symptom identification decreased for every decade older (OR = 0.908 [95% CI 0.883-0.933]). Amongst symptomatic UMD-CTIS respondents who wanted but did not have a test, not knowing where to go was the most cited factor (32.4%); this increased for each decade older (OR = 1.207 [1.129-1.292]) and for every 4-years fewer in education (OR = 0.685 [0.599-0.783]). Despite current UK messaging on COVID-19 testing, there is a knowledge gap about when and where to test, and this may be contributing to the ~25% testing gap. Risk factors, including older age and less education, highlight potential opportunities to tailor public health messages. The testing gap may be ever larger in countries that do not have extensive, free testing, as the UK does.

Perceived vulnerability to immigration policies among postpartum Hispanic/Latina women in the MADRES pregnancy cohort before and during the COVID-19 pandemic

INTRODUCTION AND OBJECTIVES

Research suggests that perceived immigration policy vulnerability has important health implications. Coupled with the mental and physical stressors accompanying the postpartum period and a growing awareness of the discrimination and structural racism experienced by marginalized communities globally, the coronavirus disease 2019 period may have exacerbated stress among vulnerable populations, specifically postpartum Hispanic/Latina women. This study evaluated perceived immigration policy vulnerability (i.e. discrimination, social isolation, and family threats) in early postpartum Hispanic/Latina women in Los Angeles before and during the coronavirus disease 2019 pandemic.

METHODS

The Perceived Immigration Policy Effects Scale (PIPES) was administered cross-sectionally at 1 month postpartum to 187 Hispanic/Latina women in the MADRES cohort. Respondents between September 2018 and March 2020 were classified as "pre-pandemic" (N = 128), between March 2020 and July 2020 as "early pandemic" (N = 38), and between August 2020 and November 2021 as "later pandemic" (N = 21). Average PIPES subscale scores were dichotomized into "higher" and "lower" groups (⩽median, >median) and logistic regression models were performed.

RESULTS

Approximately half of participants had incomes of <$50,000 (50.3%) and were Latin American born (54.6%). After adjusting for age, nativity, education, income, postpartum distress, and employment status, early pandemic respondents had 5.05 times the odds of a higher score on the perceived discrimination subscale (95% CI: 1.81, 14.11), 6.47 times the odds of a higher score on the social isolation subscale (95% CI: 2.23, 18.74), 2.66 times the odds of a higher score on the family threats subscale (95% CI: 0.97, 7.32), and 3.36 times the odds of a higher total score (95% CI: 1.19, 9.51) when compared to pre-pandemic respondents. There were no significant subscale score differences between later pandemic and pre-pandemic periods.

CONCLUSION

Higher perceived immigration policy vulnerability was reported among postpartum women during the early coronavirus disease 2019 pandemic versus pre-pandemic periods. This suggests greater social inequities during the early pandemic period.

Clinical Characteristics of Hospital Follow-up for Patients Hospitalized from SARS CoV-2 (COVID 19) in an Academic Outpatient Internal Medicine Clinic

BACKGROUND

As of July 2022, there have been more than 91.3 million cases of COVID-19 and nearly 1.03 million deaths in the United States alone. In addition, many people who survived COVID-19 had long-term symptoms, such as fatigue, dyspnea, loss of smell and taste, depression, and anxiety.

OBJECTIVES

The purpose of our study is to evaluate the status of COVID-19 patients who were previously hospitalized.

METHODS

We conducted a single-center retrospective cohort study at Texas Tech University Health Sciences Center and its affiliated University Medical Center under IRB of L21-144. We included all patients hospitalized for COVID-19 and followed up in our Internal Medicine Clinic at any time between April 1, 2020, and April 1, 2021, and reviewed follow-up data for these patients after discharge.

RESULTS

A total of 128 patients were included; 59 (46%) were men, and 69 (54%) were women with an average age of 59.7 ± 14.8 years. Most of the patients (n = 78, 60.9%) identified their race as Hispanic or Latino origin; the next largest group was Caucasian (n = 29, 22.65%). The average number of days until post-hospitalization follow-up was 36 ± 38 days. The 50% of the patients (n = 64) used telemedicine for follow-up visits. Important comorbidities in these patients included diabetes (n = 84, 65.6%) and hypertension (n = 94, 73.4%). Thirty-four patients (26.6%) reported respiratory symptoms at their follow-up appointments, 24 patients (18.8%) reported constitutional symptoms, 12 patients (9.4%) reported GI symptoms, and 25 patients (19.5%) reported other symptoms, such as paresthesia, lower extremity edema, or psychological symptoms. After hospital discharge, 54 patients had follow-up chest x-rays, and 41 (75.9%) still had abnormal findings consistent with COVID-19 imaging characteristics. Follow-up laboratory tests identified 44 patients (77.2%, 57 tested) with elevated D-dimer levels, 44 patients (78.6%, 56 tested) with high ferritin levels, and 21patients (35.6%, 59 tested) with elevated troponin T HS levels.

CONCLUSION

Long-lasting COVID-19 symptoms in these patients included respiratory symptoms (26.6%), constitutional symptoms (18.8%), GI symptoms (9.4%), and other symptoms, such as paresthesia, lower extremity edema, or psychological symptoms (19.5%). The rate of telehealth follow-up was 50%. Many patients had elevated inflammatory markers that will need follow up to determine the clinical implications.

Integrated neuroimmune processing of threat, injury, and illness: An ecological framework mapping social alienation onto lifetime health vulnerability

Social alienation is a pre-eminent ecological threat for humans. In clinical and social care settings its impact is acknowledged in conditions as diverse as severe mood disturbance, chronic pain, and metabolic non-communicable diseases. An integrated psychoneuroimmune perspective shows how threat, injury, healing, and recovery follow through as a continuous process, but accepted cultural and clinical paradigms separating mental from physical illness provide little common ground on which to analyse and apply this continuum in practice. By reviewing the ecological relationships between emotional threat, tissue dyshomeostasis and injury, infection, pain, and mood this article explores not only how primeval somatic responses underpin the evolutionary foundations of depression and somatisation, but also links them to escalating physical non-communicable disease through archived socioeconomic adversity (allostatic load). Social alienation (in the absence of trauma) may prime and activate this ancient repertoire in which sensitised responses lay the foundation for persistent maladaptive states of aversive sensory misinterpretation, behavioural avoidance, anhedonia, and neuroinflammation presenting as widespread non-nociceptive pain, non-pain somatisation, and severe depression. The ecological perspective illuminates perverse clinical presentations, shows how some approaches to care may facilitate self-reinforcement in maladaptive syndromes, and offers pointers for inclusive rehabilitative clinical and social care.

Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: a space-time study

BACKGROUND

Ethnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK.

METHOD

Using a multilevel regression model we assess the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity. We separately consider weekly test positivity rate (number of positive tests over the total number of tests) and estimated unbiased prevalence (proportion of individuals in the population who would test positive) at the Lower Tier Local Authority (LTLA) level. The model also adjusts for age, urbanicity, vaccine uptake and spatio-temporal correlation structure.

FINDINGS

Comparing the least deprived and predominantly White areas with most deprived and predominantly non-White areas over the whole study period, the weekly positivity rate increases by 13% from 297% to 335%. Similarly, prevalence increases by 10% from 037% to 041%. Deprivation has a stronger effect until October 2020, while the effect of ethnicity becomes slightly more pronounced at the peak of the second wave and then again in May-June 2021. Not all BAME groups were equally affected: in the second wave of the pandemic, LTLAs with large South Asian populations were the most affected, whereas areas with large Black populations did not show increased values for either outcome during the entire period under analysis.

INTERPRETATION

At the area level, IMD and BAME% are both associated with an increased COVID-19 burden in terms of prevalence (disease spread) and test positivity (disease monitoring), and the strength of association varies over the course of the pandemic. The consistency of results across the two outcome measures suggests that community level characteristics such as deprivation and ethnicity have a differential impact on disease exposure or susceptibility rather than testing access and habits.

FUNDINGS

EPSRC, MRC, The Alan Turing Institute, NIH, UKHSA, DHSC, NIHR.

Magnifying the importance of collecting race, ethnicity, industry and occupation data during covid-19 pandemic

The contagiousness of coronavirus disease-2019 (COVID-19) led to the imposition of historical lockdowns in various countries. No scientific mind could have made accurate projections of the tremendous impact that COVID-19 would have on nations, communities, and the global-wide economy. Meanwhile, millions of workers have lost their jobs, while healthcare workers are overwhelmed and are reaching a state of mental and physical exhaustion. With the uncontrollable spread, researchers have been working to identify factors associated with COVID-19. In this regard, race, ethnicity, industry, and occupation have been found to be predominant factors of interest. However, unfortunately, the unavailability of such information has been a difficult reality. Since race, ethnicity, and employment are essential social determinants of health and could serve as potential risk-factors for COVID-19, collecting such information may offer important context for prioritising vulnerable groups. Thus, this perspective aims to highlight the importance and need for collecting race, ethnicity, and occupation-related data to track and treat the racial/ethnic groups that have been most strongly affected by the COVID-19 pandemic. Collecting such data will provide valuable insights and help public health officials recognise workplace-related outbreaks and evaluate the odds of various ethnic groups and professions contracting COVID-19.

Antirheumatic Drug Intake Influence on Occurrence of COVID-19 Infection in Ambulatory Patients with Immune-Mediated Inflammatory Diseases: A Cohort Study

Introduction

We aimed to study the prevalence of a history of COVID-19 infection among patients suffering from systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Sjögren’s syndrome (SjS) or psoriatic arthritis (PsA), and the potential influence of long-term hydroxychloroquine (HCQ) intake.

Methods

We performed an observational monocentric cohort study at the Adolphe de Rothschild Foundation Hospital ophthalmology division (Paris, France). Electronic medical records (EMR) data were searched for keywords associated with SLE, RA, SjS, or PsA. Patients were contacted by phone and were interviewed using a standardized questionnaire. The primary outcome was the occurrence of a positive COVID-19 test result during the study period. We determined the adjusted association between various antirheumatic drugs intake, COVID-19 risk factors, and occurrence of COVID-19 using a logistic regression model. This study is registered on ClinicalTrials.gov (Identifier: NCT04345159).

Results

Patients were recruited between Apr 17, 2020, and Apr 30, 2020 and were recontacted between Oct 6, 2020, and Nov 2, 2020. A total of 569 patients were included, of whom 459 patients were eligible for data analysis. One hundred and eighty-one patients were treated with long-term HCQ and 18 patients had tested positive for COVID-19. No antirheumatic drug intake, including HCQ intake, was significantly associated with an increased or decreased risk of developing COVID-19 infection.

Conclusions

No antirheumatic drug intake was associated with an increased or decreased risk of developing COVID-19 infection in our cohort of patients suffering from immune-mediated inflammatory diseases.