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

AbstractO_ST_ABSBackgroundC_ST_ABSSelf-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. MethodsIn 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. FindingsWe 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. InterpretationUnsupervised 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. FundingUK 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. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe conducted a search in the PubMed Central database, with keywords: ("Long-COVID*" OR "post?covid*" OR "post?COVID*" OR postCOVID* OR postCovid*) AND (cluster* OR endotype* OR phenotype* OR sub?type* OR subtype). On 15 June 2022, 161 documents were identified, of which 24 either provided descriptions of sub-types or proposed phenotypes of Long-COVID or post-COVID syndrome(s). These included 16 studies attempting manual sub-grouping of phenotypes, 6 deployments of unsupervised methods for patient clustering and automatic semantic phenotyping (unsupervised k-means=2; random forest classification=1; other=2), and two reports of uncommon presentations of Long-COVID/post-COVID syndrome. Overall, two to eight symptom profiles (clusters) were identified, with three recurring clusters. A cardiopulmonary syndrome was the predominant observation, manifesting with exertional intolerance and dyspnoea (n=10), fatigue (n=8), autonomic dysfunction, tachycardia or palpitations (n=5), lung radiological abnormalities including fibrosis (n=2), and chest pain (n=1). A second common presentation consisted in persistent general autoimmune activation and proinflammatory state (n=2), comprising multi-organ mild sequelae (n=2), gastrointestinal symptoms (n=2), dermatological symptoms (n=2), and/or fever (n=1). A third syndrome was reported, with neurological or neuropsychiatric symptoms: brain fog or dizziness (n=2), poor memory or cognition (n=2), and other mental health issues including mood disorders (n=5), headache (n=2), central sensitization (n=1), paresthesia (n=1), autonomic dysfunction (n=1), fibromyalgia (n=2), and chronic pain or myalgias (n=6). Unsupervised clustering methods identified two to six different post-COVID phenotypes, mapping to the ones described above. 14 further documents focused on possible causes and/or mechanisms of disease underlying one or more manifestations of Long-COVID or post-COVID and identifying immune response dysregulation as a potential common element. All the other documents were beyond the scope of this work. To our knowledge, there are no studies examining the symptom profile of post-COVID syndrome between different variants and vaccination status. Also, no studies reported the modelling of longitudinally collected symptoms, as time-series data, aiming at the characterisation of post-COVID syndrome. Added-value of this studyOur study aimed to identify symptom profiles for post-COVID syndrome across the dominant variants in 2020 and 2021, and across vaccination status at the time of infection, using a large sample with prospectively collected longitudinal self-reports of symptoms. For individuals developing 12 weeks or more of symptoms, we identified three main symptom profiles which were consistent across variants and by vaccination status, differing only in the ratio of individuals affected by each profile and symptom duration overall. Implications of all the available evidenceWe demonstrate the existence of different post-COVID syndromes, which share commonalities across SARS-CoV-2 variant types in both symptoms themselves and how they evolved through the illness. We describe subgroups of patients with specific post-COVID presentations which might reflect different underlying pathophysiological mechanisms. Given the time-series component, our study is relevant for post-COVID prognostication, indicating how long certain symptoms last. These insights could aid in the development of personalised diagnosis and treatment, as well as helping policymakers plan for the delivery of care for people living with post-COVID syndrome.

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

BackgroundWe aimed to explore the effectiveness of one-dose BNT162b2 vaccination upon SARS-CoV-2 infection, its effect on COVID-19 presentation, and post-vaccination symptoms in children and young people (CYP) in the UK during periods of Delta and Omicron variant predominance. MethodsIn 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, and described the illness profile of CYP with post-vaccination SARS- CoV-2 infection, compared to unvaccinated CYP, and post-vaccination side-effects. FindingsBetween August 5, 2021 and February 14, 2022, 25,971 UK CYP aged 12-17 years received one dose of BNT162b2 vaccine. Vaccination reduced (proxy-reported) infection risk (-80{middle dot}4% and -53{middle dot}7% at 14-30 days with Delta and Omicron variants respectively, and -61{middle dot}5% and -63{middle dot}7% after 61-90 days). The probability of remaining infection-free diverged soon after vaccination, and was greater in CYP with prior SARS-CoV-2 infection. Vaccinated CYP who contracted SARS-CoV-2 during the Delta period had milder disease than unvaccinated CYP; during the Omicron period this was only evident in children aged 12-15 years. 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. InterpretationOne dose of BNT162b2 vaccine reduced risk of SARS-CoV-2 infection for at least 90 days in CYP aged 12-17 years. Vaccine protection varied for 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 was generally milder, although unvaccinated CYP also had generally mild disease. Overall, vaccination was well-tolerated. FundingUK 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. Research in context Evidence before this studyWe searched PubMed database for peer-reviewed articles and medRxiv for preprint papers, published between January 1, 2021 and February 15, 2022 using keywords ("SARS-CoV-2" OR "COVID-19") AND (child* OR p?ediatric* OR teenager*) AND ("vaccin*" OR "immunization campaign") AND ("efficacy" OR "effectiveness" OR "symptoms") AND ("delta" or "omicron" OR "B.1.617.2" OR "B.1.1.529"). The PubMed search retrieved 36 studies, of which fewer than 30% specifically investigated individuals <18 years. Eleven studies explored SARS-CoV-2 viral transmission: seroprevalence in children (n=4), including age-dependency of susceptibility to SARS-CoV-2 infection (n=1), SARS-CoV-2 transmission in schools (n=5), and the effect of school closure on viral transmission (n=1). Eighteen documents reported clinical aspects, including manifestation of infection (n=13), symptomatology, disease duration, and severity in children. Other studies estimated emergency department visits, hospitalization, need for intensive care, and/or deaths in children (n=4), and explored prognostic factors (n=1). Thirteen studies explored vaccination-related aspects, including vaccination of children within specific paediatric co-morbidity groups (e.g., children with Down syndrome, inflammatory bowel disease, and cancer survivors, n=4), mRNA vaccine efficacy in children and adolescents from the general population (n=7), and the relation between vaccination and severity of disease and hospitalization cases (n=2). Four clinical trials were conducted using mRNA vaccines in minors, also exploring side effects. Sixty percent of children were found to have side effects after BNT162b2 vaccination, and especially after the second dose; however, most symptoms were mild and transient apart from rare uncomplicated skin ulcers. Two studies focused on severe adverse effects and safety of SARS-CoV-2 vaccines in children, reporting on myocarditis episodes and two cases of Guillain-Barre syndrome. All other studies were beyond the scope of our research. Added value of this studyWe assessed multiple components of the UK vaccination campaign in a cohort of children and young people (CYP) aged 12-17 years drawn from a large UK community-based citizen-science study, who received a first dose of BNT162b2 vaccine. We describe a variant-dependent protective effect of the first dose against both Delta and Omicron, with additional protective effect of pre-vaccination SARS- CoV-2 infection on post-vaccination re-infection. We compare the illness profile in CYP infected post-vaccination with that of unvaccinated CYP, demonstrating overall milder disease with fewer symptoms for vaccinated CYP. We describe local and systemic side-effects during the first week following first-dose vaccination, confirming that local symptoms are common, systemic symptoms uncommon, and both usually transient. Implications of all the available evidenceOur data confirm that first dose BNT162b2 vaccination in CYP reduces risk of infection by SARS-CoV-2 variants, with generally local and brief side-effects. If infected after vaccination, COVID-19 is milder, if manifest at all. The study aims to contribute quantitative evidence to the risk-benefit evaluation of vaccination in CYP to inform discussion regarding rationale for their vaccination and the designing of national immunisation campaigns for this age group; and applies citizen-science approaches in the conduct of epidemiological surveillance and data collection in the UK community. Importantly, this study was conducted during Delta and Omicron predominance in UK; specificity of vaccine efficacy to variants is also illustrated; and results may not be generalizable to future SARS-CoV-2 strains.

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

BackgroundThe 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. MethodsThis 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. Findings3,581 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{middle dot}47) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly (69-84%) reduced risk of Delta infection. InterpretationCOVID-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. FundingUK 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, Alzheimers Society, and ZOE Limited. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for differences (including illness, transmissibility, and vaccine effectiveness) from SARS-CoV-2 infection due to Alpha (B.1.1.7) and Delta (B.1.617.2) variants, we searched PubMed for peer-reviewed articles and medRxiv for preprint publications between March 1 and November 18, 2021 using keywords ("SARS-CoV-2" OR "COVID-19") AND ("delta variant" OR "B.1.617.2") AND (symptom* OR transmiss* OR "disease duration" OR "illness duration" OR "symptom* duration"). Searches were not restricted by language. Among 169 identified PubMed articles, we found evidence that Delta variant has increased replication capacity (from 4-fold, up to 21-fold, compared with wild-type) and greater transmissibility (estimated between +20% and +97%), compared with previous strains. Currently available vaccines may have 2- to 5-fold lower neutralizing response to Delta vs. previous variants, depending on vaccine formulation, although their protective effect against severe disease and death appears to remain strong. REACT-1 study found that in UK infections were increasing exponentially in the 5-17-year old children in September 2021, coinciding with the start of the autumn school term in England. This was interpreted as an effect of the relatively low rate of vaccinated individuals in this age group. Other studies found that in unvaccinated individuals, Delta variant may be associated with higher odds of pneumonia, oxygen requirement, emergency care requests, ICU admission, and death. In a study of 27 (mainly young) cases, 22 persons were symptomatic, with fever (41%), cough (33%), headache (26%), and sore throat (26%) the commonest symptoms. We found no studies, beyond case series, investigating symptom and/or illness duration due to Delta variant infection otherwise. Added value of this studyUsing data from one of the largest UK citizen science epidemiological initiatives, we describe and compare illness (symptom duration, burden, profile, risk of long illness, and hospital attendance) in symptomatic community-based adults presenting when either the Alpha or Delta variant was the predominant circulating strain of SARS-CoV-2 in the UK. We assess evidence of transmission, reinfection, and vaccine effectiveness. Our data show that the seven most common symptoms with Delta infection were the same as with Alpha infection. Risks of illness duration [≥]7 days and [≥]28 days, and of requiring hospital care, were not increased. In line with previous research, we found increased transmissibility of Delta vs. previous variants; and no evidence of increased re-infection rates. Our data support high vaccine efficacy of BNT162b2 and ChAdOx1 nCoV-19 formulations against Delta variant infection. Overall, our study adds quantitative information regarding meaningful clinical differences in COVID-19 due to Delta vs. other variants. Implications of all the available evidenceOur observational data confirm that COVID-19 disease in UK in adults is generally comparable to infection with the Alpha variant, including in elderly individuals. Our data contribute to epidemiological surveillance from the wider UK population and may capture information from COVID-19 presentation within the community that might be missed in healthcare-based surveillance. Our data may be useful in informing healthcare service planning, vaccination policies, and measures for social protection.

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

BackgroundThe Delta (B.1.617.2) SARS-CoV-2 variant became the predominant UK circulating strain in May 2021. Whether COVID-19 from Delta infection differs to infection with other variants in children is unknown. MethodsThrough 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. Findings694 (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. InterpretationCOVID-19 in UK school-aged children due to SARS-CoV-2 Delta strain B.1.617.2 resembles illness due to the Alpha variant B.1.1.7., with short duration and similar symptom burden. FundingZOE Limited, 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 and Alzheimers Society. EthicsEthics approval was granted by KCL Ethics Committee (reference LRS-19/20-18210). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for differences in COVID-19 due to infection with Alpha (B.1.1.7) or Delta (B.1.617.2) SARS-CoV-2 variants, we searched PubMed for peer-reviewed articles and medRxiv for preprint publications between March 1, and September 17, 2021 using keywords ("SARS-CoV-2" OR "COVID-19") AND (children OR p?ediatric*) AND ("delta variant" OR "B.1.617.2"). We did not restrict our search by language. Of twenty published articles identified in PubMed, we found one case study describing disease presentation associated with Delta variant infection in a child. Another study examining the increase in hospitalization rates of paediatric cases in USA from August 1, 2020 to August 27, 2021 stated that "It is not known whether the B.1.617.2 (Delta) variant [...] causes different clinical outcomes in children and adolescents compared with variants that circulated earlier." Four studies reported cases of transmission of the Delta variant in school and community contexts; and two discussed screening testing in school-aged children (thus not directly relevant to the research question here). Remaining papers did not target paediatric age specifically. We found no studies investigating differences in COVID-19 presentation (e.g., duration, burden, individual symptoms) in school-aged children either in the UK or world-wide. Added value of this studyWe describe and compare illness profiles in symptomatic UK school-aged children (aged 5-17 years) with COVID-19 when either Alpha or Delta strains were the predominant circulating SARS-CoV-2 variant. Our data, collected through one of the largest UK citizen science epidemiological initiatives, show that symptom profile and illness duration of COVID-19 are broadly similar between the strains. Although there were slightly more symptoms with Delta than with Alpha, particularly in older children, this was offset by similar symptom duration (whether considered for symptoms individually or for illness overall). Our study adds quantitative information to the debate on whether there are meaningful clinical differences in COVID-19 due to Alpha vs. Delta variants; and contributes to the discussion regarding rationale for vaccinating children (particularly younger children) against SARS-CoV-2. Implications of all the available evidenceOur data confirm that COVID-19 in UK school-aged children is usually of short duration and similar symptom burden, whether due to Delta or Alpha. Our data contribute to epidemiological surveillance from the wider UK population, and we capture common and generally mild paediatric presentations of COVID-19 that might be missed using clinician-based surveillance alone. Our data will also be useful for the vaccination debate.

Disentangling post-vaccination symptoms from early COVID-19

BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app. DesignWe conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria. FindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue). InterpretationPost-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread. FundingZoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimers Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThere are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: "COVID-19" AND "Vaccination" AND ("mobile application" OR "web tool" OR "digital survey" OR "early detection" OR "Self-reported symptoms" OR "side-effects"). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies ("machine learning") coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services. Added value of this studyThis study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals. Implications of all the available evidenceOur study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated - to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.

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

BackgroundMental 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. MethodsWe 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. FindingsOverall, 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. InterpretationA 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. FundingZoe Limited, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, Medical Research Council UK

Illness duration and symptom profile in a large cohort of symptomatic UK school-aged children tested for SARS-CoV-2

BackgroundIn children, SARS-CoV-2 is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, the largest UK citizen participatory epidemiological study to date. MethodsData from 258,790 children aged 5-17 years were reported by an adult proxy between 24 March 2020 and 22 February 2021. Illness duration and symptom profiles were analysed for all children testing positive for SARS-CoV-2 for whom illness duration could be determined, considered overall and within younger (5-11 years) and older (12-17 years) groups. Data from symptomatic children testing negative for SARS-CoV-2, matched 1:1 for age, gender, and week of testing, were also assessed. Findings1,734 children (588 younger, 1,146 older children) had a positive SARS-CoV-2 test result and calculable illness duration within the study time frame. The commonest symptoms were headache (62.2%) and fatigue (55.0%). Median illness duration was six days (vs. three days in children testing negative), and was positively associated with age (rs 0.19, p<1.e-4) with median duration of seven days in older vs. five days in younger children. Seventy-seven (4.4%) children had illness duration [≥]28 days (LC28), more commonly experienced by older vs. younger children (59 (5.1%) vs. 18 (3.1%), p=0.046). The commonest symptoms experienced by these children were fatigue (84%), headache (80%) and anosmia (80%); however, by day 28 the symptom burden was low (median, two). Only 25 (1.8%) of 1,379 children experienced symptoms for [≥]56 days. Few children (15 children, 0.9%) in the negatively-tested cohort experienced prolonged symptom duration; however, these children experienced greater symptom burden (both throughout their illness and at day 28) than children positive for SARS-CoV-2. InterpretationSome children with COVID-19 experience prolonged illness duration. Reassuringly, symptom burden in these children did not increase with time, and most recovered by day 56. Some children who tested negative for SARS-CoV-2 also had persistent and burdensome illness. A holistic approach for all children with persistent illness during the pandemic is appropriate. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSARS-CoV-2 in children is usually asymptomatic or manifests as a mild illness of short duration. Concerns have been raised regarding prolonged illness in children, with no clear resolution of symptoms several weeks after onset, as is observed in some adults. How common this might be in children, the clinical features of such prolonged illness in children, and how it might compare with illnesses from other respiratory viruses (and with general population prevalence of these symptoms) is unclear. Added value of this studyWe provide systematic description of COVID-19 in UK school-aged children. Our data, collected in a digital surveillance platform through one of the largest UK citizen science initiatives, show that long illness duration after SARS-CoV-2 infection in school-aged children does occur, but is uncommon, with only a small proportion of children experiencing illness duration beyond four weeks; and the symptom burden in these children usually decreases over time. Almost all children have symptom resolution by eight weeks, providing reassurance about long-term outcomes. Additionally, symptom burden in children with long COVID was not greater than symptom burden in children with long illnesses due to causes other than SARS-CoV-2 infection. Implications of all the available evidenceOur data confirm that COVID-19 in UK school-aged children is usually of short duration and of low symptom burden. Some children do experience longer illness duration, validating their experience; however, most of these children usually recover with time. Our findings highlight that appropriate resources will be necessary for any child with prolonged illness, whether due to COVID-19 or other illness. Our study provides timely and critical data to inform discussions around the impact and implications of the pandemic on paediatric healthcare resource allocation.

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

BackgroundCOVID-19 vaccines show excellent efficacy in clinical trials and real-world data, but some people still contract SARS-CoV-2 despite vaccination. This study sought to identify risk factors associated with SARS-CoV-2 infection post-vaccination and describe characteristics of post-vaccination illness. MethodsAmongst 1,102,192 vaccinated UK adults from the COVID Symptom Study, 2394 (0.2%) cases of post-vaccination SARS-CoV-2 infection were identified between 8th December 2020 and 1st May 2021. Using a control group of vaccinated individuals testing negative, we assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection. Illness profile post-vaccination was assessed using a second control group of unvaccinated cases. FindingsOlder adults with frailty (OR=2.78, 95% CI=[1.98-3.89], p-value<0.0001) and individuals living in most deprived areas (OR=1.22 vs. intermediate group, CI[1.04-1.43], p-value=0.01) had increased odds of post-vaccination infection. Risk was lower in individuals without obesity (OR=0.6, CI[0.44-0.82], p-value=0.001) and those reporting healthier diet (OR=0.73, CI[0.62-0.86], p-value<0.0001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, CI[0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, CI[0.42-0.61], p-value<0.0001). In older adults, risk of [≥]28 days illness was lower following vaccination (OR=0.72, CI[0.51-1.00], p-value=0.05). Symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, CI[1.05-1.46], p-value=0.01). InterpretationOur findings suggest that older individuals with frailty and those living in most deprived areas are at increased risk of infection post-vaccination. We also showed reduced symptom burden and duration in those infected post-vaccination. Efforts to boost vaccine effectiveness in at-risk populations, and to targeted infection control measures, may still be appropriate to minimise SARS-CoV-2 infection. FundingThis work is supported by UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre (BRC) award to Guys & St Thomas NHS Foundation Trust in partnership with Kings College London and Kings College Hospital NHS Foundation Trust and via a grant to ZOE Global; the Wellcome Engineering and Physical Sciences Research Council (EPSRC) Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). Investigators also received support from the Chronic Disease Research Foundation, the Medical Research Council (MRC), British Heart Foundation, the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, the Wellcome Flagship Programme (WT213038/Z/18/Z and Alzheimers Society (AS-JF-17-011), and the Massachusetts Consortium on Pathogen Readiness (MassCPR). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for risk factors and characteristics of SARS-CoV-2 infection post-vaccination, we searched PubMed for peer-reviewed articles published between December 1, 2020 and May 18, 2021 using keywords ("COVID-19" OR "SARS-CoV-2") AND ("Vaccine" OR "vaccination") AND ("infection") AND ("risk factor*" OR "characteristic*"). We did not restrict our search by language or type of publication. Of 202 articles identified, we found no original studies on individual risk and protective factors for COVID-19 infection following vaccination nor on nature and duration of symptoms in vaccinated, community-based individuals. Previous studies in unvaccinated populations have shown that social and occupational factors influence risk of SARS-CoV-2infection, and that personal factors (age, male sex, multiple morbidities and frailty) increased risk for adverse outcomes in COVID-19. Phase III clinical trials have demonstrated good efficacy of BNT162b2 and ChAdOx1 vaccines against SARS-CoV-2 infection, confirmed in published real-world data, which additionally showed reduced risk of adverse outcomes including hospitalisation and death. Added value of this studyThis is the first observational study investigating characteristics of and factors associated with SARS-CoV-2 infection after COVID-19 vaccination. We found that vaccinated individuals with frailty had higher rates of infection after vaccination than those without. Adverse determinants of health such as increased social deprivation, obesity, or a less healthy diet were associated with higher likelihood of infection after vaccination. In comparison with unvaccinated individuals, those with post-vaccination infection had fewer symptoms of COVID-19, and more were entirely asymptomatic. Fewer vaccinated individuals experienced five or more symptoms, required hospitalisation, and, in the older adult group, fewer had prolonged illness duration (symptoms lasting longer than 28 days). Implications of all the available evidenceSome individuals still contract COVID-19 after vaccination and our data suggest that frail older adults and those living in more deprived areas are at higher risk. However, in most individuals illness appears less severe, with reduced need for hospitalisation and lower risk of prolonged illness duration. Our results are relevant for health policy post-vaccination and highlight the need to prioritise those most at risk, whilst also emphasising the balance between the importance of personal protective measures versus adverse effects from ongoing social restrictions. Strategies such as timely prioritisation of booster vaccination and optimised infection control could be considered for at-risk groups. Research is also needed on how to enhance the immune response to vaccination in those at higher risk.

Knowledge barriers in the symptomatic-COVID-19 testing programme in the UK: an observational study

BackgroundSymptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. MethodsWe analysed a cohort of untested symptomatic app users (N=1,237), nested in the Zoe COVID Symptom Study (Zoe, N= 4,394,948); and symptomatic survey respondents who wanted, but did not have a test (N=1,956), drawn from the University of Maryland-Facebook Covid-19 Symptom Survey (UMD-Facebook, N=775,746). FindingsThe proportion tested among individuals with incident test-qualifying symptoms rose from [~]20% to [~]75% from April to December 2020 in Zoe. Testing was lower with one vs more symptoms (73.0% vs 85.0%), or short vs long symptom duration (72.6% vs 87.8%). 40.4% of survey respondents did not identify all three test-qualifying symptoms. Symptom identification decreased for every decade older (OR=0.908 [95% CI 0.883-0.933]). Amongst symptomatic UMD-Facebook respondents who wanted but did not have a test, not knowing where to go was the most cited factor (32.4%); this increased for each decade older (OR=1.207 [1.129-1.292]) and for every 4-years fewer in education (OR=0.685 [0.599-0.783]). InterpretationDespite current UK messaging on COVID-19 testing, there is a knowledge gap about when and where to test, and this may be contributing to the [~]25% testing gap. Risk factors, including older age and less education, highlight potential opportunities to tailor public health messages. FundingZoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimers Society, Facebook Sponsored Research Agreement. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo assess current evidence on test uptake in symptomatic testing programmes, and the reasons for not testing, we searched PubMed from database inception for research using the keywords (COVID-19) AND (testing) AND ((access) OR (uptake)). We did not find any work reporting on levels of test uptake amongst symptomatic individuals. We found three papers investigating geographic barriers to testing. We found one US based survey reporting on knowledge barriers to testing, and one UK based survey reporting on barriers in the period March - August 2020. Neither of these studies were able to combine testing behaviour with prospectively collected symptom reports from the users surveyed. Added value of this studyThrough prospective collection of symptom and test reports, we were able to estimate testing uptake amongst individuals with test-qualifying symptoms in the UK. Our results indicate that whilst testing has improved since the start of the pandemic, there remains a considerable testing gap. Investigating this gap we find that individuals with just one test-qualifying symptom or short symptom duration are less likely to get tested. We also find knowledge barriers to testing: a substantial proportion of individuals do not know which symptoms qualify them for a COVID-19 test, and do not know where to seek testing. We find a larger knowledge gap in individuals with older age and fewer years of education. Implications of all the available evidenceDespite the UK having a simple set of symptom-based testing criteria, with tests made freely available through nationalised healthcare, a quarter of individuals with qualifying symptoms do not get tested. Our findings suggest testing uptake may be limited by individuals not acting on mild or transient symptoms, not recognising the testing criteria, and not knowing where to get tested. Improved messaging may help address this testing gap, with opportunities to target individuals of older age or fewer years of education. Messaging may prove even more valuable in countries with more fragmented testing infrastructure or more nuanced testing criteria, where knowledge barriers are likely to be greater.

The effect of SARS-CoV-2 variant B.1.1.7 on symptomatology, re-infection and transmissibility

BackgroundSARS-CoV-2 variant B.1.1.7 was first identified in December 2020 in England. It is not known if the new variant presents with variation in symptoms or disease course, if previously infected individuals may become reinfected with the new variant, or how the variants increased transmissibility affects measures to reduce its spread. MethodsUsing longitudinal symptom reports from 36,920 users of the COVID Symptom Study app testing positive for Covid-19 between 28 September and 27 December 2020, we performed an ecological study to examine the association between the regional proportion of B.1.1.7 and reported symptoms, disease course, rates of reinfection, and transmissibility. FindingsWe found no evidence for changes in reported symptoms or disease duration associated with B.1.1.7. We found a likely reinfection rate of 0.7% (95% CI 0.6-0.8), but no evidence that this was higher compared to older strains. We found an increase in R(t) by a factor of 1.35 (95% CI 1.02-1.69). Despite this, we found that R(t) fell below 1 during regional and national lockdowns, even in regions with high proportions of B.1.1.7. InterpretationThe lack of change in symptoms indicates existing testing and surveillance infrastructure do not need to change specifically for the new variant, and the reinfection findings suggest that vaccines are likely to remain effective against the new variant. FundingZoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimers Society. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence on SARS-CoV-2 variant B.1.1.7 we searched PubMed and Google Scholar for articles between 1 December 2020 and 1 February 2021 using the keywords Covid-19 AND B.1.1.7, finding 281 results. We did not find any studies that investigated B.1.1.7-associated changes in the symptoms experienced, their severity and duration, but found one study showing B.1.1.7 did not change the ratio of symptomatic to asymptomatic infections. We found six articles describing laboratory-based investigations of the responses of B.1.1.7 to vaccine-induced immunity to B.1.1.7, but no work investigating what this means for natural immunity and the likelihood of reinfection outside of the lab. We found five articles demonstrating the increased transmissibility of B.1.1.7. Added value of this studyTo our knowledge, this is the first study to explore changes in symptom type and duration, as well as community reinfection rates, associated with B.1.1.7. The work uses self-reported symptom logs from 36,920 users of the COVID Symptom Study app reporting positive test results between 28 September and 27 December 2020. We find that B.1.1.7 is not associated with changes in the symptoms experienced in Covid-19, nor their duration. Building on existing lab studies, our work suggests that natural immunity developed from previous infection provides similar levels of protection to B.1.1.7. We add to the emerging consensus that B.1.1.7 exhibits increased transmissibility. Implications of all the available evidenceOur findings suggest that existing criteria for obtaining a Covid-19 test in the community need not change for the rise of B.1.1.7. The fact that immunity developed from infection by wild type variants protects against B.1.1.7 provides an indication that vaccines will remain effective against B.1.1.7. R(t) fell below 1 during the UKs national lockdown, even in regions with high levels of B.1.1.7, but further investigation is required to establish the factors that enabled this, to facilitate countries seeking to control the spread of B.1.1.7.

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

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

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

BackgroundMultiple 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. MethodsFour 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. FindingsAnosmia/ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test, based on 658,325 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. InterpretationThe 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. FundingNIH, NIHR, Alzheimers Society, Wellcome Trust Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAs the COVID-19 pandemic has evolved, testing capacity expanded and governmental guidelines adapted, generally encouraging testing with a broader set of symptoms, not just fever with respiratory symptoms. In parallel, multiple large-scale citizen science digital surveillance platforms launched to complement knowledge from laboratory and somewhat smaller clinical studies. Symptoms such as loss of sense of smell have been identified as strongly predictive of COVID-19 infection in both clinical and syndromic surveillance analyses, and have therefore been used to inform these testing policy changes and access expansion. Added value of this studyThis study identifies symptoms that are or are not consistently associated with SARS-CoV-2 test positivity over time and across three country-based COVID-19 surveillance platforms in the United States, United Kingdom and Israel. These platforms are website and smartphone based, as well as cross-sectional and longitudinal. The study period of 4 months covers fluctuating COVID-19 prevalence during the fall of the first wave and, in some areas, rise of the second wave. In addition, the study period overlaps expansion of test access and test seeking. Importantly, these analyses track and highlight the value of individual symptoms to predict SARS-CoV-2 test positivity under a range of conditions. Implications of all the available evidenceDespite differences in surveillance methodology, access to SARS-CoV-2 testing and disease prevalence, loss of sense of smell or taste was consistently the strongest predictor of COVID-19 infection across all platforms over time. As access to testing broadened, the relevance of COVID-like symptoms and consistency of their predictive ability became apparent. However, confidence bounds generally widened with a fall in COVID-19 incidence. Therefore, for the most robust symptom-based COVID-19 prediction models should consider surveillance data during periods of higher incidence and improved test access, and effect estimates that replicate across different epidemiologic conditions and platforms.

Identifying optimal combinations of symptoms to trigger diagnostic work-up of suspected COVID-19 cases in vaccine trials: analysis from a community-based, prospective, observational cohort

ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. MethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. FindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. InterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings. HighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases C_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled C_LIO_LIOptimal symptom combinations maximise case capture considering available resources C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health C_LI

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

BackgroundAs 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. MethodsWe 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. FindingsMore than 2.8 million app users in England provided 120 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-1 studies. On 28 September 2020 we estimated 15,841 (95% CI 14,023-17,885) daily cases, a prevalence of 0.53% (95% CI 0.45-0.60), and R(t) of 1.17 (95% credible interval 1.15-1.19) in England. On a geographically granular level, on 28 September 2020 we detected 15 of the 20 regions with highest incidence according to Government test data, with indications that our method may be able to detect rapid case increases in regions where Government testing provision is more limited. InterpretationSelf-reported data from mobile applications can provide an agile resource to inform policymakers during a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance. FundingZoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimers Society. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify instances of the use of digital tools to perform COVID-19 surveillance, we searched PubMed for peer-reviewed articles between 1 January and 14 October 2020, using the keywords COVID-19 AND ((mobile application) OR (web tool) OR (digital survey)). Of the 382 results, we found eight that utilised user-reported data to ascertain a users COVID-19 status. Of these, none sought to provide disease surveillance on a national level, or to compare these predictions to other tools to ascertain their accuracy. Furthermore, none of these papers sought to use their data to highlight geographical areas of concern. Added value of this studyTo our knowledge, we provide the first demonstration of mobile technology to provide national-level disease surveillance. Using over 120 million reports from more than 2.8 million users across England, we estimate incidence, prevalence, and the effective reproduction number. We compare these estimates to those from national community surveys to understand the effectiveness of these digital tools. Furthermore, we demonstrate the large number of users can be used to provide disease surveillance with high geographical granularity, potentially providing a valuable source of information for policymakers seeking to understand the spread of the disease. Implications of all the available evidenceOur findings suggest that mobile technology can be used to provide real-time data on the national and local state of the pandemic, enabling policymakers to make informed decisions in a fast-moving pandemic.

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

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]. A simple model to distinguish between short and 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.

SARS-CoV-2 (COVID-19) infection in pregnant women: characterization of symptoms and syndromes predictive of disease and severity through real-time, remote participatory epidemiology.

BackgroundFrom the beginning of COVID-19 pandemic, pregnant women have been considered at greater risk of severe morbidity and mortality. However, data on hospitalized pregnant women show that the symptom profile and risk factors for severe disease are similar to those among women who are not pregnant, although preterm birth, Cesarean delivery, and stillbirth may be more frequent and vertical transmission is possible. Limited data are available for the cohort of pregnant women that gave rise to these hospitalized cases, hindering our ability to quantify risk of COVID-19 sequelae for pregnant women in the community. ObjectiveTo test the hypothesis that pregnant women in community differ in their COVID-19 symptoms profile and disease severity compared to non-pregnant women. This was assessed in two community-based cohorts of women aged 18-44 years in the United Kingdom, Sweden and the United States of America. Study designThis observational study used prospectively collected longitudinal (smartphone application interface) and cross-sectional (web-based survey) data. Participants in the discovery cohort were drawn from 400,750 UK, Sweden and US women (79 pregnant who tested positive) who self-reported symptoms and events longitudinally via their smartphone, and a replication cohort drawn from 1,344,966 USA women (162 pregnant who tested positive) cross-sectional self-reports samples from the social media active user base. The study compared frequencies of symptoms and events, including self-reported SARS-CoV-2 testing and differences between pregnant and non-pregnant women who were hospitalized and those who recovered in the community. Multivariable regression was used to investigate disease severity and comorbidity effects. ResultsPregnant and non-pregnant women positive for SARS-CoV-2 infection drawn from these community cohorts were not different with respect to COVID-19-related severity. Pregnant women were more likely to have received SARS-CoV-2 testing than non-pregnant, despite reporting fewer clinical symptoms. Pre-existing lung disease was most closely associated with the severity of symptoms in pregnant hospitalized women. Heart and kidney diseases and diabetes were additional factors of increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% in pregnant, 92% in non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized. Gastrointestinal symptoms, including nausea and vomiting, were different among pregnant and non-pregnant women who developed severe outcomes. ConclusionsAlthough pregnancy is widely considered a risk factor for SARS-CoV-2 infection and outcomes, and was associated with higher propensity for testing, the profile of symptom characteristics and severity in our community-based cohorts were comparable to those observed among non-pregnant women, except for the gastrointestinal symptoms. Consistent with observations in non-pregnant populations, comorbidities such as lung disease and diabetes were associated with an increased risk of more severe SARS-CoV-2 infection during pregnancy. Pregnant women with pre-existing conditions require careful monitoring for the evolution of their symptoms during SARS-CoV-2 infection.

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

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

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. One sentence summaryLongitudinal clustering of symptoms can predict the need for respiratory support in severe COVID-19.

Current tobacco smoking and risk from COVID-19: results from a population symptom app in over 2.4 million people

BackgroundThe association between current tobacco smoking, the risk of developing COVID-19 and the severity of illness is an important information gap. MethodsUK users of the COVID Symptom Study app provided baseline data including demographics, anthropometrics, smoking status and medical conditions, were asked to log symptoms daily from 24th March 2020 to 23rd April 2020. Participants reporting that they did not feel physically normal were taken through a series of questions, including 14 potential COVID-19 symptoms and any hospital attendance. The main study outcome was the association between current smoking and the development of "classic" symptoms of COVID-19 during the pandemic defined as fever, new persistent cough and breathlessness. The number of concurrent COVID-19 symptoms was used as a proxy for severity. In addition, association of subcutaneous adipose tissue expression of ACE2, both the receptor for SARS-CoV-2 and a potential mediator of disease severity, with smoking status was assessed in a subset of 541 twins from the TwinsUK cohort. ResultsData were available on 2,401,982 participants, mean(SD) age 43.6(15.1) years, 63.3% female, overall smoking prevalence 11.0%. 834,437 (35%) participants reported being unwell and entered one or more symptoms. Current smokers were more likely to develop symptoms suggesting a diagnosis of COVID-19; classic symptoms adjusted OR[95%CI] 1.14[1.10 to 1.18]; >5 symptoms 1.29[1.26 to 1.31]; >10 symptoms 1.50[1.42 to 1.58]. Smoking was associated with reduced ACE2 expression in adipose tissue (Beta(SE)=-0.395(0.149); p=7.01x10-3). InterpretationThese data are consistent with smokers having an increased risk from COVID-19. FundingZoe provided in kind support for all aspects of building, running and supporting the app and service to all users worldwide. The study was also supported by grants from the Wellcome Trust, UK Research and Innovation and British Heart Foundation. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe interaction between current smoking and COVID-19 is unclear. Smoking is known to increase susceptibility to viral infections and appears to be associated with worse outcomes in people admitted to hospital with COVID-19. However, case series have reported relatively low levels of current smoking among individuals admitted to hospital with the condition, raising the possibility that smoking has a protective effect against the disease. Added value of this studyData from a large UK population who are users of a symptom reporting app during the pandemic supports the hypothesis that smokers are more likely to develop symptoms consistent with COVID-19 and that they have an increased symptom burden. Implications of all the available evidenceThese population data, combined with evidence of a worse outcome in smokers hospitalised with the condition, support the contention that smoking increases individual risk from COVID-19. Support to help people to quit smoking should therefore form part of efforts to deal with the pandemic.

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

ObjectivesWe aimed to identify key demographic risk factors for hospital attendance with COVID-19 infection. DesignCommunity survey SettingThe 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. Participants2,618,948 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 measuresVisit 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) selfreported 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. ResultsOlder 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. ConclusionsBeing 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 registrationThe App Ethics have been approved by KCL ethics Committee REMAS ID 18210, review reference LRS-19/20-18210