Nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination.

BackgroundMost studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. MethodsPlasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FindingsStrong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months. Nasal and plasma anti-S IgG remained elevated for at least 12 months with high plasma neutralising titres against all variants. Of 180 with complete data, 160 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal. Samples 12 months after admission showed no association between nasal IgA and plasma IgG responses, indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. InterpretationThe decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. Research in contextO_ST_ABSEvidence before the studyC_ST_ABSWhile systemic immunity to SARS-CoV-2 is important in preventing severe disease, mucosal immunity prevents viral replication at the point of entry and reduces onward transmission. We searched PubMed with search terms "mucosal", "nasal", "antibody", "IgA", "COVID-19", "SARS-CoV-2", "convalescent" and "vaccination" for studies published in English before 20th July 2022, identifying three previous studies examining the durability of nasal responses that generally show nasal antibody to persist for 3 to 9 months. However, these studies were small or included individuals with mild COVID-19. One study of 107 care-home residents demonstrated increased salivary IgG (but not IgA) after two doses of mRNA vaccine, and another examined nasal antibody responses after infection and subsequent vaccination in 20 cases, demonstrating rises in both nasal IgA and IgG 7 to 10 days after vaccination. Added value of this studyStudying 446 people hospitalised for COVID-19, we show durable nasal and plasma IgG responses to ancestral (B.1 lineage) SARS-CoV-2, Delta and Omicron (BA.1) variants up to 12 months after infection. Nasal antibody induced by infection with pre-Omicron variants, bind Omicron virus in vitro better than plasma antibody. Although nasal and plasma IgG responses were enhanced by vaccination, Omicron binding responses did not reach levels equivalent to responses for ancestral SARS-CoV-2. Using paired plasma and nasal samples collected approximately 12 months after infection, we show that nasal IgA declines and shows a minimal response to vaccination whilst plasma antibody responses to S antigen are well maintained and boosted by vaccination. Implications of all the available evidenceAfter COVID-19 and subsequent vaccination, Omicron binding plasma and nasal antibody responses are only moderately enhanced, supporting the need for booster vaccinations to maintain immunity against SARS-CoV-2 variants. Notably, there is distinct compartmentalisation between nasal IgA and plasma IgA and IgG responses after vaccination. These findings highlight the need for vaccines that induce robust and durable mucosal immunity.

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a prospective, multicentre study

ObjectivesTo describe physical behaviours following hospital admission for COVID-19 including associations with acute illness severity and ongoing symptoms. Methods1077 patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and type 2 diabetes were comparators. ResultsValid accelerometer data from 253 women and 462 men were included. Women engaged in a mean{+/-}SD of 14.9{+/-}14.7 minutes/day of moderate-to-vigorous physical activity (MVPA), with 725.6{+/-}104.9 minutes/day spent inactive and 7.22{+/-}1.08 hours/day asleep. The values for men were 21.0{+/-}22.3 and 755.5{+/-}102.8 minutes/day and 6.94{+/-}1.14 hours/day, respectively. Over 60% of women and men did not have any days containing a 30-minute bout of MVPA. Variability in sleep timing was approximately 2 hours in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer sleep duration, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. ConclusionsPhysical activity and regulating sleep patterns are potential treatable traits for COVID-19 recovery programmes.

Patient symptoms and experience following COVID-19: results from a UK wide survey

ObjectivesTo investigate the experience of people who continue to be unwell after acute COVID-19, often referred to as long COVID, both in terms of their symptoms and their interactions with healthcare. DesignWe conducted a mixed-methods analysis (quantitative and qualitative) of responses to a survey accessed through a UK online post-COVID support and information hub between April 2020 and December 2020 about peoples experiences after having acute COVID-19. ParticipantsOf 3290 respondents, 78% were female, median age range 45-54 years, 92.1% reported white ethnicity; 12.7% had been hospitalised. 494 respondents (16.5%) completed the survey between 4 and 8 weeks of the onset of their symptoms, 641 (21.4%) between 8 and 12 weeks and 1865 (62.1%) more than 12 weeks after. ResultsThe ongoing symptoms most frequently reported were; breathing problems (92.1%), fatigue (83.3%), muscle weakness or joint stiffness (50.6%), sleep disturbances (46.2%), problems with mental abilities (45.9%) changes in mood, including anxiety and depression (43.1%) and cough (42.3%). Symptoms did not appear to be related to the severity of the acute illness or to the presence of pre-existing medical conditions. Analysis of free text responses revealed three main themes (1) Experience of living with COVID-19 - physical and psychological symptoms that fluctuate unpredictably; (2) Interactions with healthcare; (3) Implications for the future - their own condition, society and the healthcare system and the need for research ConclusionPeople living with persistent problems after the acute phase of COVID-19 report multiple and varying symptoms that are not necessarily associated with initial disease severity or the presence of pre-existing health conditions. Many have substantial unmet needs and experience barriers to accessing healthcare. Consideration of patient perspective and experiences will assist in the planning of services to address this. Ethical approvalEthical approval was granted by Imperial College Research and Integrity Team (IREC; 20IC6625). What we already know on this subjectO_LIMany people who develop COVID-19 will go on to endure persistent symptoms past the acute phase of the disease, commonly termed long-COVID. C_LIO_LIKnowledge gaps exist regarding the lived experience and symptom frequency, in people with long-COVID, particularly in those who were not admitted to hospital during the acute phase of their illness. C_LI What this study addsO_LIThe findings from this large population, many of whom were not hospitalised during the acute phase of their illness, demonstrate the varying patterns and persistence of symptoms of long-COVID, which do not appear to be associated with severity of the acute phase of the disease or pre-existing medical conditions. C_LIO_LIQualitative findings revealing the patient experience of long-COVID symptoms, healthcare, and suggestions for future research and service adaptation. C_LI

Post-acute COVID-19 sequelae in cases managed in the community or hospital in the UK: a population based study

ObjectiveTo compare post-COVID-19 sequelae between hospitalised and non-hospitalised individuals DesignPopulation-based cohort study Setting1,383 general practices in England contributing to Clinical Practice Research Database Aurum Participants46,687 COVID-19 cases diagnosed between 1st August to 17th October 2020 (45.4% male; mean age 40), either hospitalised within two weeks of diagnosis or non-hospitalised, and followed-up for a maximum of three months. Main outcome measuresEvent rates of new symptoms, diseases, prescriptions and healthcare utilisation in hospitalised and non-hospitalised individuals, with between-group comparison using Cox regression. Outcomes compared at 6 and 12 months prior to index date, equating to first UK wave and pre-pandemic. Non-hospitalised group outcomes stratified by age and sex. Results45,272 of 46,687 people were non-hospitalised; 1,415 hospitalised. Hospitalised patients had higher rates of 13/26 symptoms and 11/19 diseases post-COVID-19 than the community group, received more prescriptions and utilised more healthcare. The largest differences were noted for rates per 100,000 person-weeks [95%CI] of breathlessness: 536 [432 to 663] v. 85 [77 to 93]; joint pain: 295 [221 to 392] v. 168 [158 to 179]; diabetes: 303 [225 to 416] v. 36 [32 to 42], hypertension: 244 [178 to 344] v. 47 [41 to 53]. Although low, rates of chest tightness, tinnitus and lung fibrosis were higher in the community group. 4.2% (1882/45,272) of the community group had a post-acute burden, most frequently reporting anxiety, breathlessness, chest pain and fatigue. In those non-hospitalised, age and sex differences existed in outcome rates. Healthcare utilisation in the community group increased 28.5% post-COVID-19 relative to pre-pandemic. ConclusionsPost-COVID-19 sequelae differ between hospitalised and non-hospitalised individuals, with age and sex-specific differences in those non-hospitalised. Most COVID-19 cases managed in the community do not report ongoing issues to healthcare professionals. Post-COVID-19 follow-up and management strategies need to be tailored to specific groups.

Increasing but inadequate intention to receive Covid-19 vaccination over the first 50 days of impact of the more infectious variant and roll-out of vaccination in UK: indicators for public health messaging

ObjectivesTo inform critical public health messaging by determining how changes in Covid-19 vaccine hesitancy, attitudes to the priorities for administration, the emergence of new variants and availability of vaccines may affect the trajectory and achievement of herd immunity. Methods>9,000 respondents in an ongoing cross-sectional participatory longitudinal epidemiology study (LoC-19, n=18,581) completed a questionnaire within their personal electronic health record in the week reporting first effective Covid-19 vaccines, and then again after widespread publicity of the increased transmissibility of a new variant (November 13th and December 31st 2020 respectively). Questions covered willingness to receive Covid-19 vaccination and attitudes to prioritisation. Descriptive statistics, unadjusted and adjusted odds ratios (ORs) and natural language processing of free-text responses are reported, and how changes over the first 50 days of both vaccination roll-out and new-variant impact modelling of anticipated transmission rates and the likelihood and time to herd immunity. FindingsCompared with the week reporting the first efficacious vaccine there was a 15% increase in acceptance of Covid-19 vaccination, attributable in one third to the impact of the new variant, with 75% of respondents "shielding" - staying at home and not leaving unless essential - regardless of health status or tier rules. 12.5% of respondents plan to change their behaviour two weeks after completing vaccination compared with 45% intending to do so only when cases have reduced to a low level. Despite the increase from 71% to 86% over this critical 50-day period, modelling of planned uptake of vaccination remains below that required for rapid effective herd immunity - now estimated to be 90 percent in the presence of a new variant escalating R0 to levels requiring further lockdowns. To inform the public messaging essential therefore to improve uptake, age and female gender were, respectively, strongly positively and negatively associated with wanting a vaccine. 22.7% disagreed with the prioritisation list, though 70.3% were against being able to expedite vaccination through payment. Teachers (988, 12.6%) and Black, Asian and Minority Ethnic (BAME) (837, 10.7%) groups were most cited by respondents for prioritisation. InterpretationIn this sample, the growing impact of personal choice among the increasingly informed public highlights a decrease in Covid-19 vaccine hesitancy over time, with news of a new variant motivating increased willingness for vaccination but at levels below what may be required for effective herd immunity. We identify public preferences for next-in-line priorities, headed by teachers and BAME groups, consideration of which will help build trust and community engagement critical for maximising compliance with not only the vaccination programme but also all other public health measures.

Inadequate intention to receive Covid-19 vaccination: indicators for public health messaging needed to improve uptake in UK

Data promising effective Covid-19 vaccines have accelerated the UKs mass vaccination programme. The UK publics attitudes to the governments prioritisation list are unknown, and achieving critical population immunity will require the remaining majority to accept both vaccination and the delay in access of up to a year or more. This cross-sectional observational study sent an online questionnaire to registrants of the UK National Health Services largest personal health record. Question items covered willingness for Covid-19 vaccine uptake and attitudes to prioritisation. Among 9,122 responses, 71.5% indicated wanting a vaccine, below what previous modelling indicated as critical levels for progressing towards herd immunity. 22.7% disagreed with the prioritisation list, though 70.3% were against being able to expedite vaccination through payment. Age and female gender were, respectively, strongly positively and negatively associated with wanting a vaccine. Teachers and Black, Asian and Minority Ethnic (BAME) groups were most cited by respondents for prioritisation. This study identifies factors to inform the public health messaging critical to improving uptake.

The Impact of the Covid-19 Pandemic on Uptake of Influenza Vaccine: A UK-Wide Observational Study

ObjectivesThe objective of this study was to measure the impact of the Covid-19 pandemic on acceptance of flu vaccination in the 2020-21 season, including for those newly eligible for the UK National Health Service (NHS) free vaccination programme, extended this year to include an estimated 32.4 million (48.8%) of the UK population. Knowing intended uptake is essential to inform supply and steer public health messaging to maximise vaccination given the combined threats of both flu and Covid-19 -- the unknown impact of which on both attitudes and the need for mass uptake yet again create the threat of ill-informed planning resulting in failure to meet necessary public health demand. MethodsAn online questionnaire posing question items on influenza vaccination was administered to registrants of the Care Information Exchange (CIE), the NHSs largest patient electronic personal health record. This was part of a longitudinal study initiated during the Covid-19 pandemic lockdown. This analysis was limited to those who, in line with established NHS criteria, were previously or newly eligible but had not routinely received seasonal influenza vaccination in the past. Groups were stratified by response (yes/no) to intending to receive flu vaccination in 2020-21: Group 1.) Previously eligible now responding yes, 2.) Previously eligible still responding no, 3.) Newly eligible responding yes, and 4.) Newly eligible responding no. Within these groups, response by health worker status and each groups inclination to vaccinate school age children was also measured. Summary statistics were reported alongside univariate and multivariable regression. Lastly, a network analysis visualised the frequency and co-occurrence of reasons qualifying response for or against influenza vaccination in 2020/21. FindingsAmong 6,641 respondents, 4,040 (61.1%) had previously routinely received the flu vaccination. 1,624 (24.5%) had been either previously eligible but not vaccinated (945, 58.2%) or newly eligible (679, 41.8%). Among the previously eligible participants who had not routinely received influenza vaccination 536 (56.7%) responded they would in 2020-21, increasing the vaccination rate in the entire previously eligible cohort from 79.6% to 91.2%, and 466 (68.6%) in the newly eligible. Multivariable logistic regression resulted in few substantial changes to effect estimates, with the exception of age, for which all estimates showed a stronger association with intention to receive the flu vaccine. In those who became newly eligible to receive the flu vaccine, there was an association between intention to receive the flu vaccine and increased age (OR = 1.07, 95% CI 1.03 to 1.12), IMD quintile, and considering oneself at high risk from Covid-19 (OR = 1.80, 95% CI 1.22 to 2.70). Network analysis showed the most frequent themes for previously eligible unvaccinated and newly eligible participants accepting vaccination in 2020/21 were: precaution for myself (41.2% and 46.1%) and Covid-19 (27.4% and 27.1%), where the former was qualified by the latter in 36% and 29.1% of responses. Among the previously and newly eligible not intending to receive vaccination in 2020/21, misinformed themes of makes me unwell, gives me flu and vaccine doesnt work were present across 37.4% and 21.9% of responses, respectively. Among participants with school age children, of those previously eligible who now intend to be vaccinated themselves, 82.5% also intend to vaccinate their children in 2020/21 compared to 25.8% of those who would not accept the influenza vaccine for themselves. Among the newly eligible respondents this was 82.1% and 43.5%, respectively. 49.9% of the previously unvaccinated healthcare workers would continue to decline the vaccine in 2020/21. InterpretationIn this UK-wide observational study, Covid-19 has increased acceptance of flu vaccination in 2020/21 from 79.6% to 91.2% in those previously eligible, and for the 69% of those newly eligible. This high anticipated vaccination rate (to 26 million (80%) of the UK population) requires appropriate planning, but can be further increased with effective messaging campaigns to address negative misconceptions about flu vaccination, which may also help in preparation for future Covid-19 vaccination. It remains of concern that 50% of healthcare professionals who refused it previously still do not intend to have the flu vaccine.

UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records

BackgroundThis study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom in 2019. MethodsWe used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to describe the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. FindingsOn 5 March 2019, 24{middle dot}4% of the UK population were at risk due to a record of at least one underlying health condition, including 8{middle dot}3% of school-aged children, 19{middle dot}6% of working-aged adults, and 66{middle dot}2% of individuals aged 70 years or more. 7{middle dot}1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1{middle dot}6% of the population had a new diagnosis of cancer in the past five years. InterpretationThe population at risk of severe COVID-19 (aged [≥]70 years, or with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. FundingNIHR HPRU in Immunisation Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Pubmed for peer-reviewed articles, preprints, and research reports on the size and distribution of the population at risk of severe COVID. We used the terms (1) risk factor or co-morbidity or similar (2) COVID or SARS or similar and (3) prevalence to search for studies aiming to quantify the COVID-19 at-risk UK population published in the previous year to 19 July 2020, with no language restrictions. We found one study which modelled prevalence of risk factors based on the Global Burden of Disease (which included the UK) and one study which estimated that 8.4 million individuals aged [≥]30 years in the UK were at risk based on prevalence of a subset of relevant conditions in England. There were no studies which described the complete COVID-19 at-risk population across the UK. Added value of this studyWe used a large, nationally-representative dataset based on electronic health records to estimate prevalence of increased risk of severe COVID-19 across the United Kingdom, including all conditions in national guidance. We stratified by age, sex and region to enable regionally-tailored prediction of COVID-19-related healthcare burden and interventions to reduce transmission of infection, and planning and modelling of vaccination of the at-risk population. We also quantified the value of linked secondary care records to supplement primary care records. Implications of all the available evidenceIndividuals at moderate or high risk of severe COVID-19 according to current national guidance (aged [≥]70 years, or with a specified underlying health condition) comprise 18{middle dot}5 million individuals in the United Kingdom, rather than the 8.43 million previously estimated. The 8{middle dot}3% of school-aged children and 19{middle dot}6% of working-aged adults considered at-risk according to national guidance emphasises the need to consider younger at-risk individuals in shielding policies and when re-opening schools and workplaces, but also supports prioritising vaccination based on age and condition-specific mortality risk, rather than targeting all individuals with underlying conditions, who form a large population even among younger age groups. Among individuals aged [≥]70 years, 66{middle dot}2% had at least one underlying health condition, suggesting an age-targeted approach to vaccination may efficiently target individuals at risk of severe COVID-19. These national estimates broadly support the use of Global Burden of Disease modelled estimates and age-targeted vaccination strategies in other countries.

Belief of Previous COVID-19 Infection and Unclear Government Policy are Associated with Reduced Willingness to Participate in App-Based Contact Tracing: A UK-Wide Observational Study of 13,000 Patients

BackgroundContact tracing and lockdown are health policies being used worldwide to combat the coronavirus (COVID-19). While easing lockdown, the UK National Health Service (NHS) launched its Track and Trace Service at the end of May 2020, and aims by end of June 2020 also to include app-based notification and advice to self-isolate for those who have been in contact with a person known to have COVID-19. To be successful, such an app will require high uptake, the determinants and willingness for which are unclear but essential to understand for effective public health benefit. ObjectivesTo measure the determinants of willingness to participate in an NHS app-based contact tracing programme using a questionnaire within the Care Information Exchange (CIE) - the largest patient-facing electronic health record in the NHS. MethodsObservational study of 47,708 registered NHS users of the CIE, 27% of whom completed a novel questionnaire asking about willingness to participate in app-based contact tracing, understanding of government advice, mental and physical wellbeing and their healthcare utilisation -- related or not to COVID-19. Descriptive statistics are reported alongside univariate and multivariable logistic regression models, with positive or negative responses to a question on app-based contact tracing as the dependent variable. Results26.1% of all CIE participants were included in the analysis (N = 12,434, 43.0% male, mean age 55.2). 60.3% of respondents were willing to participate in app-based contact tracing. Out of those who responded no, 67.2% stated that this was due to privacy concerns. In univariate analysis, worsening mood, fear and anxiety in relation to changes in government rules around lockdown were associated with lower willingness to participate. Multivariable analysis showed that difficulty understanding government rules was associated with a decreased inclination to download the app, with those scoring 1-2 and 3-4 in their understanding of the new government rules being 45% and 27% less inclined to download the contact tracing app, respectively; when compared to those who rated their understanding as 5-6/10 (OR for 1-2/10 = 0.57 [CI 0.48 - 0.67]; OR for 3-4/10 = 0.744 [CI 0.64 - 0.87]), whereas scores of 7-8 and 9-10 showed a 43% and 31% respective increase. Those reporting an unconfirmed belief of having previously had and recovered from COVID-19 were 27% less likely to be willing to download the app; belief of previous recovery from COVID-19 infection OR 0.727 [0.585 - 0.908]). ConclusionsIn this large UK-wide questionnaire of wellbeing in lockdown, a willingness for app-based contact tracing is 60% - close to the estimated 56% population uptake, and substantially less than the smartphone-user uptake considered necessary for an app-based contact-tracing to be an effective intervention to help suppress an epidemic. Given this marginal level of support over an appropriate age range, the impacts of difficulty comprehending government advice and a policy of not testing to confirm self-reported COVID-19 infection during lockdown indicate that uncertainty in communication and diagnosis in adopted public health policies will negatively impact the effectiveness of a government contact tracing app.

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.