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.

Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies (preprint)

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, 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 week,' 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 (preprint)

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.

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

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 from 25,670 respondents, aged 16 to 66, from nine UK longitudinal studies were analysed. Changes in employment (including being furloughed) were defined by comparing employment status pre-pandemic and during the first lockdown. 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 outcome measures, were pooled using meta-analysis. 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 fair/poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but risk ratios appear less pronounced compared to those no longer employed (e.g., psychological distress, ARR=1.39; 95% CI: 1.21, 1.59) or stable unemployed (e.g., psychological distress, ARR=1.33; 95% CI: 1.09, 1.62). Conclusions: During 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 those who became or remained unemployed, suggesting that furlough partly mitigated poorer outcomes.

Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK (preprint)

The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing. Methods Analysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses. Results Functionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%). Conclusions Long COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.

Individual factors underlie temperature variation in sickness and in health: influence of age, BMI and genetic factors in a multi-cohort study (preprint)

IntroductionAgeing affects immune function resulting in aberrant fever response to infection. We assess the effects of biological variables on basal temperature and temperature in COVID-19 infection, proposing an updated temperature threshold for older adults. MethodsParticipants: O_LIUnaffected twin volunteers: 1089 adult TwinsUK participants. C_LIO_LILondon hospitalised COVID-19+: 520 adults with emergency admission. C_LIO_LIBirmingham hospitalised COVID-19+: 757 adults with emergency admission. C_LIO_LICommunity-based COVID-19+: 3972 adults self-reporting a positive test using the COVID Symptom Study mobile application. C_LI AnalysisHeritability assessed using saturated and univariate ACE models; Linear mixed-effect and multivariable linear regression analysing associations between temperature, age, sex and BMI; multivariable logistic regression analysing associations between fever ([≥]37.8{degrees}C) and age; receiver operating characteristic (ROC) analysis to identify temperature threshold for adults [≥] 65 years. ResultsAmong unaffected volunteers, lower BMI (p=0.001), and older age (p<0.001) associated with lower basal temperature. Basal temperature showed a heritability of 47% (95% Confidence Interval 18-57%). In COVID-19+ participants, increasing age associated with lower temperatures in cohorts (c) and (d) (p<0.001). For each additional year of age, participants were 1% less likely to demonstrate a fever (OR 0.99; p<0.001). Combining healthy and COVID-19+ participants, a temperature of 37.4{degrees}C in adults [≥]65 years had similar sensitivity and specificity to 37.8{degrees}C in adults <65 years for discriminating fever in COVID-19. ConclusionsAgeing affects temperature in health and acute infection. Significant heritability indicates biological factors contribute to temperature regulation. Our observations indicate a lower threshold (37.4{degrees}C) should be considered for assessing fever in older adults. Key PointsO_LIOlder adults, particularly those with lower BMI, have a lower basal temperature and a lower temperature in response to infection C_LIO_LIBasal temperature is heritable, suggesting biological factors underlying temperature regulation C_LIO_LIOur findings support a lower temperature threshold of 37.4{degrees}C for identifying possible COVID-19 infection in older adults C_LIO_LIThis has implications for case detection, surveillance and isolation and could be incorporated into observation assessment C_LI

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.

Diagnostic value of skin manifestation of SARS-CoV-2 infection (preprint)

SARS-CoV-2 causes multiple immune-related reactions at various stages of the disease. The wide variety of skin presentations has delayed linking these to the virus. Previous studies had attempted to look at the prevalence and timing of SARS-COV-2 rashes but were based on mostly hospitalized severe cases and had little follow up. Using data collected on a subset of 336,847 eligible UK users of the COVID Symptom Study app, we observed that 8.8% of the swab positive cases (total: 2,021 subjects) reported either a body rash or an acral rash, compared to 5.4% of those with a negative swab test (total: 25,136). Together, these two skin presentations showed an odds ratio (OR) of 1.67 (95% confidence interval [CI]: 1.41-1.96) for being swab positive. Skin rashes were also predictive in the larger untested group of symptomatic app users (N=54,652), as 8.2% of those who had reported at least one classical COVID-19 symptom, i.e., fever, persistent cough, and/or anosmia, also reported a rash. Data from an independent online survey of 11,546 respondents with a rash showed that in 17% of swab positive cases, the rash was the initial presentation. Furthermore, in 21%, the rash was the only clinical sign. Skin rashes cluster with other COVID-19 symptoms, are predictive of a positive swab test and occur in a significant number of cases, either alone or before other classical symptoms. Recognising rashes is important in identifying new and earlier COVID-19 cases.

Delirium is a presenting symptom of COVID-19 in frail, older adults: a cohort study of 322 hospitalised and 535 community-based older adults (preprint)

BackgroundFrailty, increased vulnerability to physiological stressors, is associated with adverse outcomes. COVID-19 exhibits a more severe disease course in older, co-morbid adults. Awareness of atypical presentations is critical to facilitate early identification. ObjectiveTo assess how frailty affects presenting COVID-19 symptoms in older adults. DesignObservational cohort study of hospitalised older patients and self-report data for community-based older adults. SettingAdmissions to St Thomas Hospital, London with laboratory-confirmed COVID-19. Community-based data for 535 older adults using the COVID Symptom Study mobile application. SubjectsHospital cohort: patients aged 65 and over (n=322); unscheduled hospital admission between March 1st, 2020-May 5th, 2020; COVID-19 confirmed by RT-PCR of nasopharyngeal swab. Community-based cohort: participants aged 65 and over enrolled in the COVID Symptom Study (n=535); reported test-positive for COVID-19 from March 24th (application launch)-May 8th, 2020. MethodsMultivariate logistic regression analysis performed on age-matched samples from hospital and community-based cohorts to ascertain association of frailty with symptoms of confirmed COVID-19. ResultsHospital cohort: significantly higher prevalence of delirium in the frail sample, with no difference in fever or cough. Community-based cohort :significantly higher prevalence of probable delirium in frailer, older adults, and fatigue and shortness of breath. ConclusionsThis is the first study demonstrating higher prevalence of delirium as a COVID-19 symptom in older adults with frailty compared to other older adults. This emphasises need for systematic frailty assessment and screening for delirium in acutely ill older patients in hospital and community settings. Clinicians should suspect COVID-19 in frail adults with delirium.

Symptom clusters in Covid19: A potential clinical prediction tool from the COVID Symptom study app (preprint)

As no one symptom can predict disease severity or the need for dedicated medical support in COVID-19, we asked if documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between May 1- May 28th, 2020. Using the first 5 days of symptom logging, the ROC-AUC of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

Key predictors of attending hospital with COVID19: An association study from the COVID Symptom Tracker App in 2,618,948 individuals (preprint)

Objectives: We aimed to identify key demographic risk factors for hospital attendance with COVID-19 infection. Design: Community survey Setting: The COVID Symptom Tracker mobile application co-developed by physicians and scientists at Kings College London, Massachusetts General Hospital, Boston and Zoe Global Limited was launched in the UK and US on 24th and 29th March 2020 respectively. It captured self-reported information related to COVID-19 symptoms and testing. Participants: 2,618,948 users of the COVID Symptom Tracker App. UK (95.7%) and US (4.3%) population. Data cut-off for this analysis was 21st April 2020. Main outcome measures: Visit to hospital and for those who attended hospital, the need for respiratory support in three subgroups (i) self-reported COVID-19 infection with classical symptoms (SR-COVID-19), (ii) self-reported positive COVID-19 test results (T-COVID-19), and (iii) imputed/predicted COVID-19 infection based on symptomatology (I-COVID-19). Multivariate logistic regressions for each outcome and each subgroup were adjusted for age and gender, with sensitivity analyses adjusted for comorbidities. Classical symptoms were defined as high fever and persistent cough for several days. Results: Older age and all comorbidities tested were found to be associated with increased odds of requiring hospital care for COVID-19. Obesity (BMI >30) predicted hospital care in all models, with odds ratios (OR) varying from 1.20 [1.11; 1.31] to 1.40 [1.23; 1.60] across population groups. Pre-existing lung disease and diabetes were consistently found to be associated with hospital visit with a maximum OR of 1.79 [1.64,1.95] and 1.72 [1.27; 2.31]) respectively. Findings were similar when assessing the need for respiratory support, for which age and male gender played an additional role. Conclusions: Being older, obese, diabetic or suffering from pre-existing lung, heart or renal disease placed participants at increased risk of visiting hospital with COVID-19. It is of utmost importance for governments and the scientific and medical communities to work together to find evidence-based means of protecting those deemed most vulnerable from COVID-19. Trial registration: The App Ethics have been approved by KCL ethics Committee REMAS ID 18210, review reference LRS-19/20-18210

Loss of smell and taste in combination with other symptoms is a strong predictor of COVID-19 infection (preprint)

ImportanceA strategy for preventing further spread of the ongoing COVID-19 epidemic is to detect infections and isolate infected individuals without the need of extensive bio-specimen testing. ObjectivesHere we investigate the prevalence of loss of smell and taste among COVID-19 diagnosed individuals and we identify the combination of symptoms, besides loss of smell and taste, most likely to correspond to a positive COVID-19 diagnosis in non-severe cases. DesignCommunity survey. Setting and ParticipantsSubscribers of RADAR COVID-19, an app that was launched for use among the UK general population asking about COVID-19 symptoms. Main ExposureLoss of smell and taste. Main Outcome MeasuresCOVID-19. ResultsBetween 24 and 29 March 2020, 1,573,103 individuals reported their symptoms via the app; 26% reported suffering from one or more symptoms of COVID-19. Of those, n=1702 reported having had a RT-PCR COVID-19 test and gave full report on symptoms including loss of smell and taste; 579 were positive and 1123 negative. In this subset, we find that loss of smell and taste were present in 59% of COVID-19 positive individuals compared to 18% of those negative to the test, yielding an odds ratio (OR) of COVID-19 diagnosis of OR[95%CI]=6.59[5.25; 8.27], P= 1.90x10-59. We also find that a combination of loss of smell and taste, fever, persistent cough, fatigue, diarrhoea, abdominal pain and loss of appetite is predictive of COVID-19 positive test with sensitivity 0.54[0.44; 0.63], specificity 0.86[0.80; 0.90], ROC-AUC 0.77[0.72; 0.82] in the test set, and cross-validation ROC-AUC 0.75[0.72; 0.77]. When applied to the 410,598 individuals reporting symptoms but not formally tested, our model predicted that 13.06%[12.97%;13.15] of these might have been already infected by the virus. Conclusions and RelevanceOur study suggests that loss of taste and smell is a strong predictor of having been infected by the COVID-19 virus. Also, the combination of symptoms that could be used to identify and isolate individuals includes anosmia, fever, persistent cough, diarrhoea, fatigue, abdominal pain and loss of appetite. This is particularly relevant to healthcare and other key workers in constant contact with the public who have not yet been tested for COVID-19. Key pointsO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe spread of COVID-19 can be reduced by identifying and isolating infected individuals but it is not possible to test everyone and priority has been given in most countries to individuals presenting symptoms of the disease. C_LIO_LICOVID-19 symptoms, such as fever, cough, aches, fatigue are common in many other viral infections C_LIO_LIThere is therefore a need to identify symptom combinations that can rightly pinpoint to infected individuals C_LI What this study addsO_LIAmong individuals showing symptoms severe enough to be given a COVID-19 RT-PCR test in the UK the prevalence of loss of smell (anosmia) was 3-fold higher (59%) in those positive to the test than among those negative to the test (18%). C_LIO_LIWe developed a mathematical model combining symptoms to predict individuals likely to be COVID-19 positive and applied this to over 400,000 individuals in the general population presenting some of the COVID-19 symptoms. C_LIO_LIWe find that [~]13% of those presenting symptoms are likely to have or have had a COVID-19 infection. The proportion was slightly higher in women than in men but is comparable in all age groups, and corresponds to 3.4% of those who filled the app report. C_LI