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 COVID-19 (Coronavirus Disease 2019) 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 could not be examined. We aimed to characterise 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.

Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors

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. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), 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. Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, 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 (2 to 4-fold) 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. 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. Lay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK "Shielded Patient List". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK "Shielded Patient List", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.

Mental health outcomes following COVID-19 infection: Evidence from 11 UK longitudinal population studies

BackgroundEvidence on associations between COVID-19 illness and mental health is mixed. We examined longitudinal associations between COVID-19 and mental health while considering: 1) pre-pandemic mental health, 2) time since infection; 3) subgroup differences; and 4) confirmation of infection via self-reported test, and serology data. MethodsUsing data from 11 UK longitudinal studies, involving 54,442 participants, with 2 to 8 repeated measures of mental health and COVID-19 between April 2020 and April 2021, we standardised continuous mental health scales within each study across time. We investigated associations between COVID-19 (self-report, test-confirmed, serology-confirmed) and mental health using multilevel generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education and pre-pandemic mental health. Effect-sizes were pooled in random-effects meta-analyses. OutcomesPooled estimates of the standardized difference in outcome between those with and without self-reported COVID-19 suggested associations with subsequent psychological distress (0.10 [95%CI: 0.06; 0.13], I2=42.8%), depression (0.08 [0.05; 0.10], I2=20.8%), anxiety (0.08 [0.05; 0.10], I2=0%), and lower life satisfaction (-0.06 [-0.08; -0.04], I2=29.2%). Associations did not vary by time since infection until 3+ months and were present in all age groups, with some evidence of stronger effects in those aged 50+. Self-reported COVID-19, whether suspected or test-confirmed and irrespective of serology status, was associated with poorer mental health. InterpretationSelf-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings have important implications for mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide. FundingMRC and NIHR

Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies

BackgroundThe 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. MethodsData were from 25,670 respondents, aged 17 to 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 measures, were pooled using meta-analysis. ResultsCompared 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), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62). ConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.

The UK COVID-19 furlough scheme and associations with smoking, alcohol consumption and vaping: evidence from 8 UK longitudinal population surveys.

BackgroundDisruptions to employment status can impact smoking and alcohol consumption. During the COVID-19 pandemic, the UK implemented a furlough scheme to prevent job loss. We examine how furlough was associated with participants smoking, vaping and alcohol consumption behaviours in the early stages of the pandemic. MethodsData were from 27,841 participants in eight UK adult longitudinal surveys. Participants self-reported employment status and current smoking, current vaping and drinking alcohol (>4 days/week or 5+ drinks per typical occasion) both before and during the pandemic (April-July 2020). Risk ratios were estimated within each study using modified Poisson regression, adjusting for a range of potential confounders, including pre-pandemic behaviour. Findings were synthesised using random effects meta-analysis. Sub-group analyses were used to identify whether associations differed by gender, age or education. ResultsCompared to stable employment, neither furlough, no longer being employed, nor stable unemployment were associated with smoking, vaping or drinking, following adjustment for pre-pandemic characteristics. However, some sex differences in these associations were observed, with stable unemployment associated with smoking for women (ARR=1.35; 95% CI: 1.00-1.82; I2: 47%) but not men (0.84; 95% CI: 0.67-1.05; I2: 0%). No longer being employed was associated with vaping among women (ARR=2.74; 95% CI: 1.59-4.72; I2: 0%) but not men (ARR=1.25; 95% CI: 0.83-1.87; I2: 0%). There was little indication of associations with drinking differing by age, gender or education. ConclusionsWe found no clear evidence of furlough or unemployment having adverse impacts on smoking, vaping or drinking behaviours during the early stages of the COVID-19 pandemic in the UK, with differences in risk compared to those who remained employed largely explained by pre-pandemic characteristics.

Inequalities in healthcare disruptions during the Covid-19 pandemic: Evidence from 12 UK population-based longitudinal studies

BackgroundHealth 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. MethodsParticipants 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. ResultsPrevalence 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. ConclusionThe COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.

The UK Coronavirus Job Retention Scheme and changes in diet, physical activity and sleep during the COVID-19 pandemic: Evidence from eight longitudinal studies

BackgroundIn March 2020 the UK implemented the Coronavirus Job Retention Scheme (furlough) to minimize job losses. Our aim was to investigate associations between furlough and diet, physical activity, and sleep during the early stages of the COVID-19 pandemic. MethodsWe analysed data from 25,092 participants aged 16 to 66 years from eight UK longitudinal studies. Changes in employment (including being furloughed) were defined by comparing employment status pre- and during the first lockdown. Health behaviours included fruit and vegetable consumption, physical activity, and sleeping patterns. Study-specific estimates obtained using modified Poisson regression, adjusting for socio-demographic characteristics and pre-pandemic health and health behaviours, were statistically pooled using random effects meta-analysis. Associations were also stratified by sex, age, and education. ResultsAcross studies, between 8 and 25% of participants were furloughed. Compared to those who remained working, furloughed workers were slightly less likely to be physically inactive (RR:0.85, [0.75-0.97], I2=59%) and did not differ in diet and sleep behaviours, although findings for sleep were heterogenous (I2=85%). In stratified analyses, furlough was associated with low fruit and vegetable consumption among males (RR=1.11; 95%CI: 1.01-1.22; I2: 0%) but not females (RR=0.84; 95%CI: 0.68-1.04; I2: 65%). Considering change in these health behaviours, furloughed workers were more likely than those who remained working to report increased fruit and vegetable consumption, exercise, and hours of sleep. ConclusionsThose furloughed exhibited broadly similar levels of health behaviours to those who remained in employment during the initial stages of the pandemic. There was little evidence to suggest that such social protection policies if used in the post-pandemic recovery period and during future economic crises would have adverse impacts on population health behaviours.

Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies

BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable. AimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing. Method59,482 participants in 12 UK longitudinal adult population studies with data collected prior to 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 three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies. ResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption. ConclusionPeople experiencing psychological distress pre-pandemic have been 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 the existing inequalities in mental health.