ABSTRACT
Determining the protection an individual has to SARS-CoV-2 variants of concern (VoC) will be crucial for future immune surveillance and understanding the changing immune response. As further variants emerge, current serology tests are becoming less effective in reflecting neutralising capability of the immune system. A better measure of an evolving antigen-antibody immune response is needed. We describe a multiplexed, baited, targeted-proteomic assay for direct detection of multiple proteins in the SARS-CoV-2 anti-spike antibody immunocomplex. This enables a more sophisticated and informative characterisation of the antibody response to vaccination and infection against VoC. Using this assay, we detail different and specific responses to each variant by measuring several antibody classes, isotypes and associated complement binding. Furthermore, we describe how these proteins change using serum from individuals collected after infection, first and second dose vaccination. We show complete IgG1 test concordance with gold standard ELISA (r>0.8) and live virus neutralisation against Wuhan Hu-1, Alpha B.1.1.7, Beta B.1.351, and Delta B.1.617.1 variants (r>0.79). We also describe a wide degree of heterogeneity in the immunocomplex of individuals and a greater IgA response in those patients who had a previous infection. Significantly, our test points to an important role the complement system may play particularly against VoC. Where we observe altered Complement C1q association to the Delta VoC response and a stronger overall association with neutralising antibodies than IgG1. A detailed understanding of an individuals antibody response could benefit public health immunosurveillance, vaccine design and inform vaccination dosing using a personalised medicine approach.
ABSTRACT
Background: Health systems worldwide have faced major disruptions due to COVID-19 which could exacerbate health inequalities. The UK National Health Service (NHS) provides free healthcare and prioritises equity of delivery, but the pandemic may be hindering the achievement of these goals. We investigated associations between multiple social characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions in over 65,000 participants across twelve UK longitudinal studies. Methods: Participants reported disruptions from March 2020 up to late January 2021. Associations between social characteristics and three types of self-reported healthcare disruption (medication access, procedures, appointments) and a composite of any of these were assessed in logistic regression models, adjusting for age, sex and ethnicity where relevant. Random-effects meta-analysis was conducted to obtain pooled estimates. Results: Prevalence of disruption varied across studies; between 6.4% (TwinsUK) and 31.8 % (Understanding Society) of study participants reported any disruption. Females (Odd Ratio (OR): 1.27 [95%CI: 1.15,1.40]; I2=53%), older persons (e.g. OR: 1.39 [1.13,1.72]; I2=77% for 65-75y vs 45-54y), and Ethnic minorities (excluding White minorities) (OR: 1.19 [1.05,1.35]; I2=0% vs White) were more likely to report healthcare disruptions. Those in a more disadvantaged social class (e.g. OR: 1.17 [1.08, 1.27]; I2=0% for manual/routine vs managerial/professional) were also more likely to report healthcare disruptions, but no clear differences were observed by education levels. Conclusion: The COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.
Subject(s)
COVID-19ABSTRACT
Background: Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. Methods: Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study-design, non-response weights, psychological distress, presence of children or adolescents in the household, keyworker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts and meta-regression evaluated the effect of age as a moderator. Findings: 14891 participants were included. Females (OR 1.40, 95% confidence interval [1.27,1.55]) and those with a chronic illness (OR 1.84 [1.65-2.05]) experienced significantly more cancellations during lockdown (all p<0.0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR approx. 2.00, all p<0.002). Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. Interpretation: The UK government's lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly females, ethnic-minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a second wave.