Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors in two UK longitudinal studies.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. Higher levels of SARS-CoV-2 anti-Spike antibodies are known to be associated with increased protection against future SARS-CoV-2 infection. However, variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination have not been explored across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors within population-based cohorts. Methods: Samples were collected from 9361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies and tested for SARS-CoV-2 antibodies. Cross-sectional sampling was undertaken jointly in April-May 2021 (TwinsUK, N=4256; ALSPAC, N=4622), and in TwinsUK only in November 2021-January 2022 (N=3575). Variation in antibody levels after first, second, and third SARS-CoV-2 vaccination with health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables were analysed. Using multivariable logistic regression models, we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables. Results: Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had threefold greater odds of SARS-CoV-2 infection over the next 6-9 months (OR = 2.9, 95% CI: 1.4, 6.0), compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK 'Shielded Patient List' had consistently greater odds (two- to fourfold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. Conclusions: These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies. Funding: Antibody testing was funded by UK Health Security Agency. The National Core Studies program is funded by COVID-19 Longitudinal Health and Wellbeing - National Core Study (LHW-NCS) HMT/UKRI/MRC ([MC_PC_20030] and [MC_PC_20059]). Related funding was also provided by the NIHR 606 (CONVALESCENCE grant [COV-LT-0009]). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. The UK Medical Research Council and Wellcome (Grant ref: [217065/Z/19/Z]) and the University of Bristol provide core support for ALSPAC.

Vaccination against the virus that causes COVID-19 triggers the body to produce antibodies that help fight future infections. But some people generate more antibodies after vaccination than others. People with lower levels of antibodies are more likely to get COVID-19 in the future. Identifying people with low antibody levels after COVID-19 vaccination is important. It could help decide who receives priority for future vaccination. Previous studies show that people with certain health conditions produce fewer antibodies after one or two doses of a COVID-19 vaccine. For example, people with weakened immune systems. Now that third booster doses are available, it is vital to determine if they increase antibody levels for those most at risk of severe COVID-19. Cheetham et al. show that a third booster dose of a COVID-19 vaccine boosts antibodies to high levels in 90% of individuals, including those at increased risk. In the experiments, Cheetham et al. measured antibodies against the virus that causes COVID-19 in 9,361 individuals participating in two large long-term health studies in the United Kingdom. The experiments found that UK individuals advised to shield from the virus because they were at increased risk of complications had lower levels of antibodies after one or two vaccine doses than individuals without such risk factors. This difference was also seen after a third booster dose, but overall antibody levels had large increases. People who received the Oxford/AstraZeneca vaccine as their first dose also had lower antibody levels after one or two doses than those who received the Pfizer/BioNTech vaccine first. Positively, this difference in antibody levels was no longer seen after a third booster dose. Individuals with lower antibody levels after their first dose were also more likely to have a case of COVID-19 in the following months. Antibody levels were high in most individuals after the third dose. The results may help governments and public health officials identify individuals who may need extra protection after the first two vaccine doses. They also support current policies promoting booster doses of the vaccine and may support prioritizing booster doses for those at the highest risk from COVID-19 in future vaccination campaigns.

Characterising patterns of COVID-19 and long COVID symptoms: evidence from nine UK longitudinal studies.

Multiple studies across global populations have established the primary symptoms characterising Coronavirus Disease 2019 (COVID-19) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID, and the extent and length of time for which they are elevated after COVID-19, could not be examined. We analysed individual symptom prevalences and characterised patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ('no COVID-19', 'COVID-19 in last 12 weeks', 'COVID-19 > 12 weeks ago'), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the 'COVID-19 in last 12 weeks' and 'no COVID-19' groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the 'COVID-19 > 12 weeks ago' and 'no COVID-19' groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.

Psychological distress, depression, anxiety, and life satisfaction following COVID-19 infection: evidence from 11 UK longitudinal population studies.

BACKGROUND: Evidence on associations between COVID-19 illness and mental health is mixed. We aimed to examine whether COVID-19 is associated with deterioration in mental health while considering pre-pandemic mental health, time since infection, subgroup differences, and confirmation of infection via self-reported test and serology data. METHODS: We obtained data from 11 UK longitudinal studies with repeated measures of mental health (psychological distress, depression, anxiety, and life satisfaction; mental health scales were standardised within each study across time) and COVID-19 status between April, 2020, and April, 2021. We included participants with information available on at least one mental health outcome measure and self-reported COVID-19 status (suspected or test-confirmed) during the pandemic, and a subset with serology-confirmed COVID-19. Furthermore, only participants who had available data on a minimum set of covariates, including age, sex, and pre-pandemic mental health were included. We investigated associations between having ever had COVID-19 and mental health outcomes using generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education, and pre-pandemic mental health, whether the strength of the association varied according to time since infection, and whether associations differed between self-reported versus confirmed (by test or serology) infection. FINDINGS: Between 21 Dec, 2021, and July 11, 2022, we analysed data from 54 442 participants (ranging from a minimum age of 16 years in one study to a maximum category of 90 years and older in another; including 33 200 [61·0%] women and 21 242 [39·0%] men) from 11 longitudinal UK studies. Of 40 819 participants with available ethnicity data, 36 802 (90·2%) were White. Pooled estimates of standardised differences in outcomes suggested associations between COVID-19 and subsequent psychological distress (0·10 [95% CI 0·06 to 0·13], I2=42·8%), depression (0·08 [0·05 to 0·10], I2=20·8%), anxiety (0·08 [0·05 to 0·10], I2=0·0%), and lower life satisfaction (-0·06 [-0·08 to -0·04], I2=29·2%). We found no evidence of interactions between COVID-19 and sex, education, ethnicity, or pre-pandemic mental health. Associations did not vary substantially between time since infection of less than 4 weeks, 4-12 weeks, and more than 12 weeks, and were present in all age groups, with some evidence of stronger effects in those aged 50 years and older. Participants who self-reported COVID-19 but had negative serology had worse mental health outcomes for all measures than those without COVID-19 based on serology and self-report. Participants who had positive serology but did not self-report COVID-19 did not show association with mental health outcomes. INTERPRETATION: Self-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings emphasise the need for greater post-infection mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide. FUNDING: UK Medical Research Council and UK National Institute for Health and Care Research.

Inequalities in healthcare disruptions during the COVID-19 pandemic: evidence from 12 UK population-based longitudinal studies.

OBJECTIVES: We investigated associations between multiple sociodemographic characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions during the early stages of the COVID-19 pandemic. DESIGN: Coordinated analysis of prospective population surveys. SETTING: Community-dwelling participants in the UK between April 2020 and January 2021. PARTICIPANTS: Over 68 000 participants from 12 longitudinal studies. OUTCOMES: Self-reported healthcare disruption to medication access, procedures and appointments. RESULTS: Prevalence of healthcare disruption varied substantially across studies: between 6% and 32% reported any disruption, with 1%-10% experiencing disruptions in medication, 1%-17% experiencing disruption in procedures and 4%-28% experiencing disruption in clinical appointments. Females (OR 1.27; 95% CI 1.15 to 1.40; I2=54%), older persons (eg, OR 1.39; 95% CI 1.13 to 1.72; I2=77% for 65-75 years vs 45-54 years) and ethnic minorities (excluding white minorities) (OR 1.19; 95% CI 1.05 to 1.35; I2=0% vs white) were more likely to report healthcare disruptions. Those in a more disadvantaged social class were also more likely to report healthcare disruptions (eg, OR 1.17; 95% CI 1.08 to 1.27; I2=0% for manual/routine vs managerial/professional), but no clear differences were observed by education. We did not find evidence that these associations differed by shielding status. CONCLUSIONS: Healthcare disruptions during the COVID-19 pandemic could contribute to the maintenance or widening of existing health inequalities.

The mental health burden of racial and ethnic minorities during the COVID-19 pandemic.

Racial/ethnic minorities have been disproportionately impacted by COVID-19. The effects of COVID-19 on the long-term mental health of minorities remains unclear. To evaluate differences in odds of screening positive for depression and anxiety among various racial and ethnic groups during the latter phase of the COVID-19 pandemic, we performed a cross-sectional analysis of 691,473 participants nested within the prospective smartphone-based COVID Symptom Study in the United States (U.S.) and United Kingdom (U.K). from February 23, 2021 to June 9, 2021. In the U.S. (n=57,187), compared to White participants, the multivariable odds ratios (ORs) for screening positive for depression were 1·16 (95% CI: 1·02 to 1·31) for Black, 1·23 (1·11 to 1·36) for Hispanic, and 1·15 (1·02 to 1·30) for Asian participants, and 1·34 (1·13 to 1·59) for participants reporting more than one race/other even after accounting for personal factors such as prior history of a mental health disorder, COVID-19 infection status, and surrounding lockdown stringency. Rates of screening positive for anxiety were comparable. In the U.K. (n=643,286), racial/ethnic minorities had similarly elevated rates of positive screening for depression and anxiety. These disparities were not fully explained by changes in leisure time activities. Racial/ethnic minorities bore a disproportionate mental health burden during the COVID-19 pandemic. These differences will need to be considered as health care systems transition from prioritizing infection control to mitigating long-term consequences.

Mental and social wellbeing and the UK coronavirus job retention scheme: Evidence from nine longitudinal studies.

BACKGROUND: The COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic. METHODS: Data were from 25,670 respondents, aged 17-66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing, were pooled using meta-analysis. Associations were also stratified by sex, age, education, and household composition. RESULTS: Compared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR = 1.12; 95%CI: 0.97, 1.29), low life satisfaction (ARR = 1.14; 95%CI: 1.07, 1.22), loneliness (ARR = 1.12; 95%CI: 1.01, 1.23), and poor self-rated health (ARR = 1.26; 95%CI: 1.05, 1.50). Nevertheless, compared to furloughed workers, those who became unemployed had greater risk of psychological distress (ARR = 1.30; 95%CI: 1.12, 1.52), low life satisfaction (ARR = 1.16; 95%CI: 0.98, 1.38), and loneliness (ARR = 1.67; 95%CI: 1.08, 2.59). Effects were not uniform across all sub-groups. CONCLUSIONS: During the early stages of the pandemic, those furloughed had increased risk of poor mental and social wellbeing, but furloughed workers fared better than those who became unemployed, suggesting that furlough may have partly mitigated poorer outcomes.

Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records.

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive.

Psychological Distress Before and During the COVID-19 Pandemic Among Adults in the United Kingdom Based on Coordinated Analyses of 11 Longitudinal Studies.

Importance: How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, and the consequences for health inequalities are unclear. Objective: To investigate changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies. Design, Setting, and Participants: This cohort study included adult participants from 11 UK longitudinal population-based studies with prepandemic measures of psychological distress. Analyses were coordinated across these studies, and estimates were pooled. Data were collected from 2006 to 2021. Exposures: Trends in the prevalence of poor mental health were assessed in the prepandemic period (time period 0 [TP 0]) and at 3 pandemic TPs: 1, initial lockdown (March to June 2020); 2, easing of restrictions (July to October 2020); and 3, a subsequent lockdown (November 2020 to March 2021). Analyses were stratified by sex, race and ethnicity, education, age, and UK country. Main Outcomes and Measures: Multilevel regression was used to examine changes in psychological distress from the prepandemic period across the first year of the COVID-19 pandemic. Psychological distress was assessed using the 12-item General Health Questionnaire, the Kessler 6, the 9-item Malaise Inventory, the Short Mood and Feelings Questionnaire, the 8-item or 9-item Patient Health Questionnaire, the Hospital Anxiety and Depression Scale, and the Centre for Epidemiological Studies-Depression across different studies. Results: In total, 49 993 adult participants (12 323 [24.6%] aged 55-64 years; 32 741 [61.2%] women; 4960 [8.7%] racial and ethnic minority) were analyzed. Across the 11 studies, mental health deteriorated from prepandemic scores across all 3 pandemic periods, but there was considerable heterogeneity across the study-specific estimated effect sizes (pooled estimate for TP 1: standardized mean difference [SMD], 0.15; 95% CI, 0.06-0.25; TP 2: SMD, 0.18; 95% CI, 0.09-0.27; TP 3: SMD, 0.21; 95% CI, 0.10-0.32). Changes in psychological distress across the pandemic were higher in women (TP 3: SMD, 0.23; 95% CI, 0.11, 0.35) than men (TP 3: SMD, 0.16; 95% CI, 0.06-0.26) and lower in individuals with below-degree level education at TP 3 (SMD, 0.18; 95% CI, 0.06-0.30) compared with those who held degrees (SMD, 0.26; 95% CI, 0.14-0.38). Increased psychological distress was most prominent among adults aged 25 to 34 years (SMD, 0.49; 95% CI, 0.14-0.84) and 35 to 44 years (SMD, 0.35; 95% CI, 0.10-0.60) compared with other age groups. No evidence of changes in distress differing by race and ethnicity or UK country were observed. Conclusions and Relevance: In this study, the substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic period. Mental health declines have been unequal across the population, with women, those with higher degrees, and those aged 25 to 44 years more affected than other groups.

Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies.

BACKGROUND: The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable. AIMS: Quantify mental health inequalities in disruptions to healthcare, economic activity and housing. METHOD: We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies. RESULTS: Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20-1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09-1.41) for disruption to procedures to 1.33 (95% CI 1.20-1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06-1.21) and income (OR 1.12, 95% CI 1.06 -1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00-1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18-1.32) or in one domain (OR 1.11, 95% CI 1.07-1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97-1.03). CONCLUSIONS: People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.

Anxiety and depression symptoms after COVID-19 infection: results from the COVID Symptom Study app.

BACKGROUND: Mental health issues have been reported after SARS-CoV-2 infection. However, comparison to prevalence in uninfected individuals and contribution from common risk factors (eg, obesity and comorbidities) have not been examined. We identified how COVID-19 relates to mental health in the large community-based COVID Symptom Study. METHODS: We assessed anxiety and depression symptoms using two validated questionnaires in 413148 individuals between February and April 2021; 26998 had tested positive for SARS-CoV-2. We adjusted for physical and mental prepandemic comorbidities, body mass index (BMI), age and sex. FINDINGS: Overall, 26.4% of participants met screening criteria for general anxiety and depression. Anxiety and depression were slightly more prevalent in previously SARS-CoV-2-positive (30.4%) vs SARS-CoV-2-negative (26.1%) individuals. This association was small compared with the effect of an unhealthy BMI and the presence of other comorbidities, and not evident in younger participants (≤40 years). Findings were robust to multiple sensitivity analyses. Association between SARS-CoV-2 infection and anxiety and depression was stronger in individuals with recent (<30 days) versus more distant (>120 days) infection, suggesting a short-term effect. INTERPRETATION: A small association was identified between SARS-CoV-2 infection and anxiety and depression symptoms. The proportion meeting criteria for self-reported anxiety and depression disorders is only slightly higher than prepandemic.

Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app.

Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of 'urban hotspots'. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors.