On not ‘being there’: Making sense of the potent urge for physical proximity in transnational families at the outbreak of the COVID‐19 pandemic

This paper investigates transnational families’ experiences of the COVID‐19 pandemic outbreak and the accompanying sudden and unexpected travel restrictions. Our data consist of written stories collected in April–June 2020 from migrants with ageing kin living in another country. For many respondents, the situation provoked an acutely felt urge for physical proximity with their families. By analysing their experiences of ‘not being there’, we seek to understand what exactly made the urge to ‘be there’ so forceful. Bringing into dialogue literature on transnational families with Jennifer Mason's recent theoretical work on affinities, we move the focus from families’ transnational caregiving practices to the potent connections between family members. We argue that this approach can open important avenues for future research on families—transnational or otherwise—because it sheds light on the multisensory and often ineffable charges between family members that serve to connect them.

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

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

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

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

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

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

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

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

Disentangling post-vaccination symptoms from early COVID-19 (preprint)

Background Identifying 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. Design We 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. Findings Differentiating 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). Interpretation Post-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. Funding Zoe 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, Alzheimer’s Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR). Research in context Evidence before this study There 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 study This 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 evidence Our 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 (preprint)

Background: Mental health issues have been reported after SARS-CoV-2 infection. However, comparison to prevalence in uninfected individuals and contribution from common risk factors (e.g., obesity, comorbidities) have not been examined. We identified how COVID-19 relates to mental health in the large community-based COVID Symptom Study. Methods: We assessed anxiety and depression symptoms using two validated questionnaires in 413,148 individuals between February and April 2021; 26,998 had tested positive for SARS-CoV-2. We adjusted for physical and mental pre-pandemic comorbidities, BMI, age, and sex. Findings: Overall, 26.4% of participants met screening criteria for general anxiety and depression. Anxiety and depression were slightly more prevalent in previously SARS-CoV-2 positive (30.4%) vs. negative (26.1%) individuals. This association was small compared to the effect of an unhealthy BMI and the presence of other comorbidities, and not evident in younger participants ([≤]40 years). Findings were robust to multiple sensitivity analyses. Association between SARS-CoV-2 infection and anxiety and depression was stronger in individuals with recent (<30 days) vs. more distant (>120 days) infection, suggesting a short-term effect. Interpretation: A small association was identified between SARS-CoV-2 infection and anxiety and depression symptoms. The proportion meeting criteria for self-reported anxiety and depression disorders is only slightly higher than pre-pandemic.

App-based COVID-19 surveillance and prediction: The COVID Symptom Study Sweden (preprint)

Background The response of the Swedish authorities to the COVID-19 pandemic was less restrictive than in most countries during the first year, with infection and death rates substantially higher than in neighbouring Nordic countries. Because access to PCR testing was limited during the first wave (February to June 2020) and regional data were reported with delay, adequate monitoring of community disease spread was hampered. The app-based COVID Symptom Study was launched in Sweden to disseminate real-time estimates of disease spread and to collect prospective data for research. The aim of this study was to describe the research project, develop models for estimation of COVID-19 prevalence and to evaluate it for prediction of hospital admissions for COVID-19. Methods We enrolled 143 531 study participants ([≥]18 years) throughout Sweden, who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Data from 19 161 self-reported PCR tests were used to create a symptom-based algorithm to estimate daily prevalence of symptomatic COVID-19. The prediction model was validated using external datasets. We further utilized the model estimates to forecast subsequent new hospital admissions. Findings A prediction model for symptomatic COVID-19 based on 17 symptoms, age, and sex yielded an area under the ROC curve of 0.78 (95% CI 0.74-0.83) in an external validation dataset of 943 PCR-tested symptomatic individuals. App-based surveillance proved particularly useful for predicting hospital trends in times of insufficient testing capacity and registration delays. During the first wave, our prediction model estimates demonstrated a lower mean error (0.38 average new daily hospitalizations per 100 000 inhabitants per week (95% CI 0.32, 0.45)) for subsequent hospitalizations in the ten most populated counties, than a model based on confirmed case data (0.72 (0.64, 0.81)). The model further correctly identified on average three out of five counties (95% CI 2.3, 3.7) with the highest rates of hospitalizations the following week during the first wave and four out of five (3.0, 4.6) during the second wave. Interpretation The experience of the COVID Symptom Study highlights the important role citizens can play in real-time monitoring of infectious diseases, and how app-based data collection may be used for data-driven rapid responses to public health challenges.

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

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

COVID-19: Assessing the impact of lockdown on recreational athletes.

BACKGROUND AND AIMS: The COVID-19 pandemic has resulted in associated lockdown restrictions for individuals across England, including the postponement of all recreational sporting provisions. The beneficial effects of regular physical activity are well established yet to the authors' knowledge, no research addresses the cancellation of all recreational provisions. Using quantitative and qualitative methods, this study assessed the impact of COVID-19 restrictions on recreational sports players, what alternative exercise methods have been sought and how players feel about returning to their sport. METHOD: An online survey was distributed across England for six-weeks commencing in May 2020. A questionnaire explored differences in the impact of COVID-19 restrictions between sex, winter/summer/year-round sports, team/individual sports, age, and resilience groups. The use of alternative exercise methods, coping strategies and feelings about returning to sport were also investigated. Responses were gathered from 2023 adults whose recreational sport had been cancelled by COVID-19. All completed questionnaires (n = 1213) were taken for analysis (mean age = 49.41 years, SD = 17.165, 55.2% female). RESULTS: Quantitative findings showed the negative impact of COVID-19 restrictions was greater for females, those involved in winter and team sports, those aged 18-39 and low-resilient copers (p < .05). No significant differences were found between individuals that had had COVID-19 or were considered vulnerable by government guidelines. Acceptance was the most common coping strategy. The average number of days per week that participants exercised significantly increased during lockdown, with significant increases also seen in the use of online workouts, fitness apps and home-gym exercise. Qualitative findings suggested that participants are looking forward to the social and physical benefits of recreational activity restarting yet are concerned about the logistics of returning under social distancing restrictions. Other worries included loss of fitness, spreading (younger age groups) and catching (older age groups) COVID-19 and being in a crowd. CONCLUSIONS: Results highlight what is currently accessible to home-based exercisers and inform the reintroduction of recreational sports clubs. As COVID-19 restrictions look to persist, club representatives should provide accessible home-exercise options and be cautious of participant concerns when considering the return of recreational sport.

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

Background Symptomatic 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. Methods We 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). Findings The 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]). Interpretation Despite 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.

Vaccine after Effects and Post-Vaccine Infection in a Real World Setting: Results from the COVID Symptom Study App (preprint)

Background: The Pfizer-BioNTech (BNT162b2) and the Oxford/AstraZeneca (ChAdOx1 nCoV-19) COVID-19 vaccines have shown excellent safety and efficacy in Phase III trials. Here we report results from a real world setting on the two most administered vaccines in the UK.Methods: We investigated self-reported systemic and local effects within eight days of vaccination in 387,471 individuals from the COVID Symptom Study app who received one (n=209,251) or two (n=13,478) doses of the BNT162b2 vaccine, or one dose of ChAdOx1 nCoV-19 vaccine (n=178,220) between December 8 and February 15 2021. A subset of individuals subsequently tested for SARS-CoV-2 were studied for infection rates from PCR or lateral flow test results post-vaccination (59,639 vaccinated vs 277,599 controls).Findings: Systemic side effects were reported in 11.8% of participants after the first BNT162b2 dose, 20.3% after the second BNT162b2 dose, and 29.4% after the first ChAdOx1 nCoV-19 dose. Systemic effects were more prevalent among individuals with pre-existing COVID-19 infection (BNT162b2:34.1%; ChAdOx1 nCoV-19:51.6%) than among individuals without known prior infection (BNT162b2:10.6%; ChAdOx1 nCoV-19:28.6%) and among those aged <55 years (BNT162b2:19.9%; ChAdOx1 nCoV-19:45.3%) compared to those aged >55 years (BNT162b2:9.2%, ChAdOx1 nCoV-19: 26.9%). We observed significant reduction in infection risk 12-21 days after the first dose (BNT162b2:-57% [-71%, -38%], ChAdOx1 nCoV-19:-42% [-71%, -17%]). Interpretation: This phase IV-type study assessing both BNT162b2 and ChAdOx1 nCoV-19 vaccines identifies mild systemic side effects affecting 11-30% of individuals post-vaccination, lower than in published Phase III trials. Our data on infection post-vaccine were also reassuring.Funding: Zoe, NIHR, CDRF, NIH, MRCDeclaration of Interests: TDS and AMV are consultants to Zoe Global Ltd (“Zoe”). JW, AM, LP and JC are employees of Zoe Global Limited. ALG is a regional PI on the COV002 trial and the Novavax COVID-19 vaccine trial and as such her organisation has received grants from Novavax. Other authors have no conflict of interest to declare.Ethics Approval Statement: Ethical approval for use of the app for research purposes in the UK was obtained from King’s College London Ethics Committee (review reference LRS-19/20-18210), and all users provided consent for non-commercial use.

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

The new SARS-CoV-2 variant B.1.1.7 was identified in December 2020 in the South-East of England, and rapidly increased in frequency and geographic spread. While there is some evidence for increased transmissibility of this variant, it is not known if the new variant presents with variation in symptoms or disease course, or if previously infected individuals may become reinfected with the new variant. Using longitudinal symptom and test reports of 36,920 users of the Covid Symptom Study app testing positive for COVID-19 between 28 September and 27 December 2020, we examined the association between the regional proportion of B.1.1.7 and reported symptoms, disease course, rates of reinfection, and transmissibility. We found no evidence for changes in reported symptoms, disease severity and disease duration associated with B.1.1.7. We found a likely reinfection rate of around 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 regional and national lockdowns have reduced R(t) below 1 in regions with very high proportions of B.1.1.7.

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 (preprint)

Background: Several COVID-19 vaccine efficacy trials are ongoing with others predicted to start soon. Diagnostic work-up of trial participants following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify an efficient symptom combination to capture most cases using the lowest possible number of tests. Methods: UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms between March-September 2020 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 RT-PCR positive case were calculated for individual symptoms and symptom combinations. A multi-objective evolutionary algorithm was applied to generate symptom combinations with good trade-offs between sensitivity and specificity. Findings: The UK dataset included 122,305 individuals (1,202 RT-PCR positive). Findings were replicated in a US dataset including 3,162 individuals (79 RT-PCR positive). Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 RT-PCR tests per positive case. The symptom combination with the highest sensitivity was fatigue, anosmia, cough, diarrhoea, headache, and sore throat, identifying 96% of cases and requiring 96 tests. Interpretation: We confirm the significance of COVID-19 specific symptoms widely recommended for triggering RT-PCR. By using the data-driven optimization technique we identified additional symptoms (fatigue, sore throat, headache, diarrhoea) that enabled many more positive cases to be captured efficiently. By providing a set of solutions with optimal trade-offs between sensitivity and specificity, we produced a selection of symptom subsets that maximise the capture of cases given different laboratory capacities. The methodology may be of particular use for COVID-19 vaccine developers across a range of resource settings and have more far-reaching public health implications for detection of symptomatic SARS CoV2 infection.

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.