Social determinants of recovery from ongoing symptoms following COVID-19 in two UK longitudinal studies: a prospective cohort study (preprint)

BackgroundSocial gradients in COVID-19 exposure, illness severity, and mortality have been observed in multiple international contexts. Whether pre-existing social factors affect recovery from ongoing symptoms following COVID-19 and long COVID is less well understood. MethodsWe analysed data on self-perceived recovery following self-reported COVID-19 illness in two United Kingdom community-based cohorts, COVID Symptom Study Biobank (CSSB) (N = 2548) and TwinsUK (N = 1334). Composite variables quantifying socio-demographic advantage and disadvantage prior to the COVID-19 pandemic were generated from sex, ethnic group, education, local area deprivation and employment status. Associations between self-perceived recovery and composite variables were tested with multivariable logistic regression models weighted for inverse probability of study participation, adjusting for potential confounding by age, region and pre- pandemic health factors, and potential mediation by COVID-19 illness characteristics and adverse experiences during the pandemic. Further analyses tested associations between recovery and individual socio-demographic variables reflecting status prior to and during the COVID-19 pandemic. FindingsSocio-demographic gradients in recovery were observed, with unadjusted recovery rate varying between 50% and 80% in CSSB and 70% and 90% in TwinsUK based on composite socio-demographic variables. Likelihood of recovery was lower for individuals with more indicators of pre-pandemic social disadvantage in both cohorts (CSSB: odds ratio, OR = 0.74, 95% confidence interval, CI: 0.62-0.88, TwinsUK: OR = 0.79, 95% CI: 0.64-0.98 per disadvantage) and higher with more social advantages (CSSB: OR = 1.26, 95% CI: 1.08-1.47, TwinsUK: OR = 1.36, 95% CI: 1.09-1.70 per advantage). Associations were neither explained by differences in COVID-19 illness severity or timing, nor adverse social experiences during the pandemic, which were themselves inversely associated with recovery. InterpretationStrong social inequalities in the likelihood of recovery from COVID-19 were observed, with ongoing symptoms several months after coronavirus infection more likely for individuals with multiple indicators of social disadvantage. Work is needed to identify modifiable biopsychosocial factors to enable interventions that address inequalities. FundingChronic Disease Research Foundation, National Institute for Health and Care Research, Medical Research Council, Wellcome LEAP, Wellcome Trust, Engineering & Physical Sciences Research Council, Biotechnology and Biological Sciences Research Council, Versus Arthritis, European Commission, Zoe Ltd. Plain language summaryAcross the world acute COVID-19 illness has affected the most disadvantaged in society the most. However, we have not looked in detail whether peoples social circumstances affect their recovery from COVID-19. In our study, we asked people from two UK-based health studies if they still had symptoms after having COVID-19. We looked at how advantaged or disadvantaged they were at the start of the pandemic, based on information about their sex, ethnic group, education level, local area, and employment. In both studies, people who were more disadvantaged were more likely to still have symptoms long after having COVID-19. In contrast, more advantaged people were more likely to have fully recovered. We also saw that people who had negative experiences during the pandemic such as losing their job, being unable to afford their bills or not being able to access health & social care services were less likely to recover. More work is needed to understand how and why recovery was so different for people with different circumstances. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo search for previous reports on associations between recovery from COVID-19 and socio-demographic factors, we screened abstracts identified from the PubMed search query on December 21, 2023: "((COVID-19) AND ((recovery) OR (convalescence) OR (" ongoing symptoms")) AND ((socioeconomic) OR (sociodemographic) OR (social) OR (gradient))) AND LitCLONGCOVID[filter]", where LitCLONGCOVID is a filter for articles relating to long COVID (https://pubmed.ncbi.nlm.nih.gov/help/#covid19-article-filters), which returned 210 results published between July, 2020 and December, 2023. A small number (N = 11) of studies contained direct measures of recovery from COVID-19 in terms of presence/absence of ongoing symptoms relating to COVID-19 illness, either as perceived by the individual or inferred from current symptom reports. Of these, most focused on associations with COVID-19 illness factors such as severity and symptomatology, and prior health indicators. Socio-demographics were mostly used for sample description and adjustments in models rather than as exposures of interest. Of the few studies (N = 8) that tested associations with socio-demographic variables, the range of socio-demographics tested was limited and/or follow-up time typically restricted to 6-12 months since symptom onset. In these studies, associations with recovery were reported for age (N = 4), sex (N = 7), race/ethnicity (N = 2), local area deprivation (N = 1), and education level (N = 1). Associations between long-term symptoms and education or income have been reported in single separate studies. Monthly bulletins up to March 2023 from the UK Coronavirus Infection Survey highlighted prevalence of individuals reporting current effects on daily activities due to long COVID was associated with age, sex, race/ethnicity, local area deprivation and economic activity. No studies were identified that tested for associations of multiple socio-demographics in combination with the likelihood of recovery following COVID-19. Added value of this studyThis is the first study to testing the effects of multiple socio-demographics on self-perceived recovery in combination. Measures that attempt to quantify social advantage and disadvantage were generated from multiple known social determinants of health. We tested a wider range of socio-demographic factors than previous studies, including UK geographic region, educational qualification level, employment status and income. Our study has a longer follow-up time than previous comparable reports, with most participants assessed more than one year after infection onset. Detailed data on health before the coronavirus pandemic and COVID-19 illness allowed models to be adjusted extensively and mediation effects to be tested. Implications of all the available evidenceThe likelihood of full recovery following COVID-19 appears to follow a social gradient, higher for individuals with multiple indicators of social advantages and fewer disadvantages, and lower for those with multiple social disadvantages and fewer advantages prior to the coronavirus pandemic. This reflects and reaffirms the established cycle of social inequalities in health, between individuals status within social hierarchies and ill-health. More work is needed to understand the pathways through which this inequality operates so that interventions can be made.

Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data. (preprint)

Background: Some individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration. Methods Survival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([≥]8 weeks, 906 [67.1%] with illness [≥]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms. Findings: Individuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly. Interpretation: Individuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.

Profiling post-COVID syndrome across different variants of SARS-CoV-2 (preprint)

Background: Self-reported symptom studies rapidly increased our understanding of SARS-CoV-2 during the pandemic and enabled the monitoring of long-term effects of COVID-19 outside the hospital setting. It is now evident that post-COVID syndrome presents with heterogeneous profiles, which need characterisation to enable personalised care among the most affected survivors. This study describes post-COVID profiles, and how they relate to different viral variants and vaccination status. Methods: In this prospective longitudinal cohort study, we analysed data from 336,652 subjects, with regular health reports through the Covid Symptom Study (CSS) smartphone application. These subjects had reported feeling physically normal for at least 30 days before testing positive for SARS-CoV-2. 9,323 individuals subsequently developed Long-COVID, defined as symptoms lasting longer than 28 days. 1,459 had post-COVID syndrome, defined as more than 12 weeks of symptoms. Clustering analysis of the time-series data was performed to identify distinct symptom profiles for post-COVID patients, across variants of SARS-CoV-2 and vaccination status at the time of infection. Clusters were then characterised based on symptom prevalence, duration, demography, and prior conditions (comorbidities). Using an independent testing sample with additional data (n=140), we investigated the impact of post-COVID symptom clusters on the lives of affected individuals. Findings: We identified distinct profiles of symptoms for post-COVID syndrome within and across variants: four endotypes were identified for infections due to the wild-type variant; seven for the alpha variant; and five for delta. Across all variants, a cardiorespiratory cluster of symptoms was identified. A second cluster related to central neurological, and a third to cases with the most severe and debilitating multi-organ symptoms. Gastrointestinal symptoms clustered in no more than two specific phenotypes per viral variant. The three main clusters were confirmed in an independent testing sample, and their functional impact was assessed. Interpretation: Unsupervised analysis identified different post-COVID profiles, characterised by differing symptom combinations, durations, and functional outcomes. Phenotypes were at least partially concordant with individuals reported experiences. Our classification may be useful to understand distinct mechanisms of the post-COVID syndrome, as well as subgroups of individuals at risk of prolonged debilitation. Funding: UK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation and Alzheimers Society, and ZOE Limited, UK.

Vaccination against SARS-CoV-2 in UK school-aged children and young people decreases infection rates and reduces COVID-19 symptoms (preprint)

Background We aim to explore the effectiveness of one-dose BNT162b2 vaccination upon SARS-CoV-2 infection rates in children and young people (CYP) during Delta and Omicron variant predominance in the UK, and study its effect on COVID-19 presentation and post-vaccination symptoms. Methods In this prospective longitudinal cohort study, we analysed data from 115,775 CYP aged 12-17 years, proxy-reported through the Covid Symptom Study (CSS) smartphone application. We calculated post-vaccination infection risk after one dose of BNT162b2. We described the illness profile of CYP with post-vaccination SARS-CoV-2 infection, compared to unvaccinated CYP. Findings Between August 5, 2021 and February 14, 2022, 25,971 UK CYP aged 12-17 years received one dose of BNT162b2 vaccine. Vaccination reduced infection (reporting) risk (-80.4% and -53.7% at 14-30 days with Delta and Omicron variants respectively, and -61.5% and -63.7% after 61-90 days). The probability of remaining infection-free diverged after vaccination, and was more robust with prior infection. Vaccinated CYP who contracted SARS-CoV-2 during the Delta period had milder disease than unvaccinated CYP; however, during the Omicron period this was only evident in children aged 12-15 years, and overall disease profile was similar in both vaccinated and unvaccinated CYP. Post-vaccination local side-effects were common, systemic side-effects were uncommon, and both resolved quickly. Interpretation One dose of BNT162b2 vaccine reduced risk of SARS-CoV-2 infection for at least 90 days in CYP aged 12-17 years. Vaccine protection was modulated by SARS-CoV-2 variant type (lower for Omicron than Delta variant), and was enhanced by pre-vaccination SARS-CoV-2 infection. Severity of COVID-19 presentation after vaccination is generally milder, although unvaccinated CYP also have an uncomplicated course. Overall, vaccination was well-tolerated.

COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: two prospective observational cohort studies (preprint)

Background The Delta (B.1.617.2) variant became the predominant UK circulating SARS-CoV-2 strain in May 2021. How Delta infection compares with previous variants is unknown. Methods This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. Findings 3,581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta vs. Alpha infection (including fever, sore throat and headache) and vice versa (dyspnoea). Symptom burden in the first week was higher with Delta vs. Alpha infection; however, the odds of any given symptom lasting [≥]7 days was either lower or unchanged. Illness duration [≥]28 days was lower with Delta vs. Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.47) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly (69-84%) reduced risk of Delta infection. Interpretation COVID-19 from Delta or Alpha infections is clinically similar. The Delta variant is more transmissible than Alpha; however, current vaccines show good efficacy against disease. Funding UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, Alzheimer's Society, and ZOE Limited.

Illness characteristics of COVID-19 in children infected with the SARS-CoV-2 Delta variant (preprint)

Background The Delta (B.1.617.2) SARSCoV2 variant became the predominant UK circulating strain in May 2021. Whether COVID19 from Delta infection differs to infection with other variants in children is unknown. Methods Through the prospective COVID Symptom Study, 109,626 UK school-aged children were proxy-reported between December 28, 2020 and July 8, 2021. We selected all symptomatic children who tested positive for SARS-CoV-2 and were proxy-reported at least weekly, within two timeframes: December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the main UK circulating variant); and May 26 to July 8, 2021 (Delta the main UK circulating variant). We assessed illness profiles (symptom prevalence, duration, and burden), hospital presentation, and presence of long (>28 day) illness; and calculated odds ratios for symptoms presenting within the first 28 days of illness. Findings 694 (276 younger [5 11 years], 418 older [12 17 years]) symptomatic children tested positive for SARS-CoV-2 with Alpha infection and 706 (227 younger and 479 older) children with Delta infection. Median illness duration was short with either variant (overall cohort: 5 days (IQR 2 9.75) with Alpha, 5 days (IQR 2 9) with Delta). The seven most prevalent symptoms were common to both variants. Symptom burden over the first 28 days was slightly greater with Delta compared with Alpha infection (in younger children, 3 (IQR 2 5) with Alpha, 4 (IQR 2 7) with Delta; in older children 5 (IQR 3 8) with Alpha and 6 (IQR 3 9) with Delta infection in older children). The odds of several symptoms were higher with Delta than Alpha infection, including headache and fever. Few children presented to hospital, and long illness duration was uncommon, with either variant. Interpretation COVID-19 in UK school-aged children due to SARSCoV2 Delta strain B.1.617.2 resembles illness due to the Alpha variant B.1.1.7., with short duration and similar symptom burden.

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

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 (e.g., obesity, 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 413,148 individuals between February and April 2021; 26,998 had tested positive for SARS-CoV-2. We adjusted for physical and mental pre-pandemic comorbidities, 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. negative (26.1%) individuals. This association was small compared to 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) vs. 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 pre-pandemic.

Post-vaccination SARS-CoV-2 infection: risk factors and illness profile in a prospective, observational community-based case-control study (preprint)

Background: Both BNT162b2 and ChAdOx1 vaccines show good efficacy in clinical trials and real-world data. However, some still contract SARS-CoV-2 post-vaccination. This study identifies risk factors associated with SARS-CoV-2 infection at least 14 days after first vaccination and describes characteristics of post-vaccination illness. Methods: Cases were UK adults reporting post-vaccination SARS-CoV-2 infection between 8th December 2020 and 1st May 2021, reporting on the COVID Symptom Study app. We assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection (vaccinated cases vs. negative-vaccinated controls); and vaccination with illness profile (vaccinated cases vs positive-unvaccinated controls). Findings: Post-vaccination infection risk was substantially higher in older adults with frailty (OR= 2.78, 95% CI [1.98-3.89], p-value<0.0001) and in individuals living in most deprived areas (OR vs. intermediate group=1.22, 95%CI [1.04-1.43], p-value=0.01). Risk was lower in individuals with a healthier diet (OR=0.73, 95%CI [0.62-0.86], p-value<0.0001) and without obesity (OR=0.6, 95% CI [0.44-0.82], p-value=0.001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, 95%CI [0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, 95%CI [0.42-0.61], p-value<0.0001). In the 60+ age group, risk of >28 days illness was lower following vaccination (OR=0.72 , 95%CI [0.51-1.00], p-value=0.05). Most symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, 95%CI [1.05-1.46], p-value=0.01). Interpretation: Our findings highlight reduced symptom burden and duration in those infected post-vaccination. Whilst reassuring, our data should prompt efforts to boost vaccine effectiveness in at-risk populations; moreover, targeted infection control measures will still be appropriate to minimise SARS-CoV-2 infection.

Anosmia and other SARS-CoV-2 positive test-associated symptoms, across three national, digital surveillance platforms as the COVID-19 pandemic and response unfolded: an observation study (preprint)

Background: Multiple participatory surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of community-wide COVID-19 epidemiology. During this time, testing criteria broadened and healthcare policies matured. We sought to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three national surveillance platforms, during periods of testing and policy changes, and whether inconsistencies could better inform our understanding and future studies as the COVID-19 pandemic progresses. Methods: Four months (1st April 2020 to 31st July 2020) of observation through three volunteer COVID-19 digital surveillance platforms targeting communities in three countries (Israel, United Kingdom, and United States). Logistic regression of self-reported symptom on self-reported SARS-CoV-2 test status (or test access), adjusted for age and sex, in each of the study cohorts. Odds ratios over time were compared to known changes in testing policies and fluctuations in COVID-19 incidence. Findings: Anosmia/ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test, based on 658325 tests (5% positive) from over 10 million respondents in three digital surveillance platforms using longitudinal and cross-sectional survey methodologies. During higher-incidence periods with broader testing criteria, core COVID-19 symptoms were more strongly associated with test status. Lower incidence periods had, overall, larger confidence intervals. Interpretation: The strong association of anosmia/ageusia with self-reported SARS-CoV-2 test positivity is omnipresent, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform or testing policy. This analysis highlights that precise effect estimates, as well as an understanding of test access patterns to interpret differences, are best done only when incidence is high. These findings strongly support the need for testing access to be as open as possible both for real-time epidemiologic investigation and public health utility.

Accessible Data Curation and Analytics for International-Scale Citizen Science Datasets (preprint)

The Covid Symptom Study, a smartphone-based surveillance study on COVID-19 symptoms in the population, is an exemplar of big data citizen science. Over 4.7 million participants and 189 million unique assessments have been logged since its introduction in March 2020. The success of the Covid Symptom Study creates technical challenges around effective data curation for two reasons. Firstly, the scale of the dataset means that it can no longer be easily processed using standard software on commodity hardware. Secondly, the size of the research group means that replicability and consistency of key analytics used across multiple publications becomes an issue. We present ExeTera, an open source data curation software designed to address scalability challenges and to enable reproducible research across an international research group for datasets such as the Covid Symptom Study dataset.

Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application (preprint)

Background As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. Methods We performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence and effective reproduction number. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots. Findings More than 2.6 million app users in England provided 115 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence showed similar sensitivity to changes as two national community surveys: the ONS and REACT studies. On a geographically granular level, our estimates were able to highlight regions before they were subject to local government lockdowns. Between 12 May and 29 September we were able to flag between 35-80% of regions appearing in the Government's hotspot list. Interpretation Self-reported data from mobile applications can provide a cost-effective and agile resource to inform a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance.

Attributes and predictors of Long-COVID: analysis of COVID cases and their symptoms collected by the Covid Symptoms Study App (preprint)

Reports of "Long-COVID", are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >28 days, 189 (4.5%) for >8 weeks and 95 (2.3%) for >12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increasing age, BMI and female sex. Experiencing more than five symptoms during the first week of illness was associated with Long-COVID, OR=3.53 [2.76;4.50]. Our model to predict long-COVID at 7 days, which gained a ROC-AUC of 76%, was replicated in an independent sample of 2472 antibody positive individuals. This model could be used to identify individuals for clinical trials to reduce long-term symptoms and target education and rehabilitation services.