Publications
240 results found
Riley S, 2022, Steven Riley's discussion contribution to papers in Session 1 of the Royal Statistical Society's Special Topic Meeting on COVID-19 transmission: 9 June 2021, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 185, Pages: S53-S54, ISSN: 0964-1998
Riley S, 2022, Steven Riley's discussion contribution to papers in Session 3 of the Royal Statistical Society's Special Topic Meeting on COVID-19 transmission: 11 June 2021, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 185, Pages: S148-S149, ISSN: 0964-1998
Yang B, Garcia-Carreras B, Lessler J, et al., 2022, Long term intrinsic cycling in human life course antibody responses to influenza A(H3N2): an observational and modeling study, ELIFE, Vol: 11, ISSN: 2050-084X
Kwok KO, Chan EYY, Riley S, et al., 2022, Carriage prevalence of antimicrobial resistance in Hong Kong: a longitudinal study (abridged secondary publication)., Hong Kong Med J, Vol: 28 Suppl 6, Pages: 25-28, ISSN: 1024-2708
Eales O, Haw D, Wang H, et al., 2022, Quantifying changes in the IFR and IHR over 23 months of the SARS-CoV-2 pandemic in England
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>The relationship between prevalence of infection and severe outcomes such as hospitalisation and death changed over the course of the COVID-19 pandemic. The REal-time Assessment of Community Transmission-1 (REACT-1) study estimated swab positivity in England approximately monthly from May 2020 to 31 March 2022. This period covers widespread circulation of the original strain, the emergence of the Alpha, Delta and Omicron variants and the rollout of England’s mass vaccination campaign.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Here, we explore this changing relationship between prevalence of swab positivity and the infection fatality rate (IFR) and infection hospitalisation rate (IHR) over 23 months of the pandemic in England, using publicly available data for the daily number of deaths and hospitalisations, REACT-1 swab positivity data, time-delay models and Bayesian P-spline models. We analyse data for all age groups together, as well as in two sub-groups: those aged 65 and over and those aged 64 and under.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>During 2020, we estimated the IFR to be 0.67% and the IHR to be 2.6%. By late-2021/early-2022 the IFR and IHR had both decreased to 0.097% and 0.76% respectively. Continuous estimates of the IFR and IHR of the virus were observed to increase during the periods of Alpha and Delta’s emergence. During periods of vaccination rollout, and the emergence of the Omicron variant, the IFR and IHR of the virus decreased. During 2020, we estimated a time-lag of 19 days between hospitalisation and swab positivity, and 26 days between deaths and swab positivity. By late-2021/early-2022 these time-lags had decreased to 7 days for hospitalisations, and 18 days for deaths.</jats:
Eales O, Ainslie KEC, Walters CE, et al., 2022, Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number, Epidemics: the journal of infectious disease dynamics, Vol: 40, ISSN: 1755-4365
The time-varying reproduction number () can change rapidly over the course of a pandemic due to changing restrictions, behaviours, and levels of population immunity. Many methods exist that allow the estimation of from case data. However, these are not easily adapted to point prevalence data nor can they infer across periods of missing data. We developed a Bayesian P-spline model suitable for fitting to a wide range of epidemic time-series, including point-prevalence data. We demonstrate the utility of the model by fitting to periodic daily SARS-CoV-2 swab-positivity data in England from the first 7 rounds (May 2020–December 2020) of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Estimates of over the period of two subsequent rounds (6–8 weeks) and single rounds (2–3 weeks) inferred using the Bayesian P-spline model were broadly consistent with estimates from a simple exponential model, with overlapping credible intervals. However, there were sometimes substantial differences in point estimates. The Bayesian P-spline model was further able to infer changes in over shorter periods tracking a temporary increase above one during late-May 2020, a gradual increase in over the summer of 2020 as restrictions were eased, and a reduction in during England’s second national lockdown followed by an increase as the Alpha variant surged. The model is robust against both under-fitting and over-fitting and is able to interpolate between periods of available data; it is a particularly versatile model when growth rate can change over small timescales, as in the current SARS-CoV-2 pandemic. This work highlights the importance of pairing robust methods with representative samples to track pandemics.
Tildesley MJ, Vassall A, Riley S, et al., 2022, Optimal health and economic impact of non-pharmaceutical intervention measures prior and post vaccination in England: a mathematical modelling study, ROYAL SOCIETY OPEN SCIENCE, Vol: 9, ISSN: 2054-5703
- Author Web Link
- Cite
- Citations: 1
Ben-Nun M, Riley P, Turtle J, et al., 2022, Consistent pattern of epidemic slowing across many geographies led to longer, flatter initial waves of the COVID-19 pandemic, PLOS COMPUTATIONAL BIOLOGY, Vol: 18, ISSN: 1553-734X
Eales O, Martins LDO, Page AJ, et al., 2022, Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England, Nature Communications, Vol: 13, ISSN: 2041-1723
The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’.
Eales O, Wang H, Haw D, et al., 2022, Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Following rapidly rising COVID-19 case numbers, England entered a national lockdown on 6 January 2021, with staged relaxations of restrictions from 8 March 2021 onwards.</jats:p></jats:sec><jats:sec><jats:title>Aim</jats:title><jats:p>We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>On average, risk of infection is proportional to infection prevalence. The REal-time Assessment of Community Transmission-1 (REACT-1) study is a repeat cross-sectional study of over 98,000 people every round (rounds approximately monthly) that estimates infection prevalence in England. We used Bayesian P-splines to estimate prevalence and the time-varying reproduction number (<jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>) nationally, regionally and by age group from round 8 (beginning 6 January 2021) to round 13 (ending 12 July 2021) of REACT-1. As a comparator, a separate segmented-exponential model was used to quantify the impact on <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> of each relaxation of restrictions.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Following an initial plateau of 1.54% until mid-January, infection prevalence decreased until 13 May when it reached a minimum of 0.09%, before increasing until the end of the study to 0.76%. Following the first easing of restrictions, which included schools reopening, the reproduction number <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> incre
Cann A, Clarke C, Brown J, et al., 2022, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody lateral flow assay for antibody prevalence studies following vaccination: a diagnostic accuracy study [version 2; peer review: 2 approved], Wellcome Open Research, Vol: 6, ISSN: 2398-502X
Background: Lateral flow immunoassays (LFIAs) are able to achieve affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. Methods: This was a prospective diagnostic accuracy study. Sampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Two cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following two doses of SARS-CoV-2 vaccine, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination and subsequent follow up. During the participants visit, finger-prick blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG was detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA. A total of 186 paired samples were collected. The accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay Results: The LFIA had an estimated sensitivity of 92.0% (114/124; 95% confidence interval [CI] 85.7% to 96.1%) and specificity of 93.6% (58/62; 95% CI 84.3% to 98.2%) using the Abbott assay as reference standard (using the threshold for positivity of 7.10 BAU/ml) Conclusions: Fortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveillance but does not meet criteria for individual testing.
Ainslie KEC, Riley S, 2022, Is annual vaccination best? A modelling study of influenza vaccination strategies in children, VACCINE, Vol: 40, Pages: 2940-2948, ISSN: 0264-410X
- Author Web Link
- Cite
- Citations: 1
Cramer EY, Ray EL, Lopez VK, et al., 2022, Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 119, ISSN: 0027-8424
- Author Web Link
- Cite
- Citations: 4
Whitaker M, Elliott J, Chadeau M, et al., 2022, Persistent COVID-19 symptoms in a community study of 606,434 people in England, Nature Communications, Vol: 13, ISSN: 2041-1723
Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (n=508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 (n=97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.
Eales O, de Oliveira Martins L, Page AJ, et al., 2022, The new normal? Dynamics and scale of the SARS-CoV-2 variant Omicron epidemic in England
<jats:title>Summary</jats:title><jats:p>The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants which have led to substantial changes in the epidemiology of the virus. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant was first detected in late November 2021 and exhibited a high degree of immune evasion, leading to increased infection rates in many countries. However, estimates of the magnitude of the Omicron wave have relied mainly on routine testing data, which are prone to several biases. Here we infer the dynamics of the Omicron wave in England using PCR testing and genomic sequencing obtained by the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys testing random samples of the population of England. We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections in England during February-March 2022 as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct genomic variants, intermittent epidemics of similar magnitude as the Omicron wave may become the ‘new normal’.</jats:p>
Chadeau-Hyam M, Wang H, Eales O, et al., 2022, SARS-CoV-2 infection and vaccine effectiveness in England (REACT-1): a series of cross-sectional random community surveys, The Lancet Respiratory Medicine, Vol: 10, Pages: 355-366, ISSN: 2213-2600
SummaryBackground England has experienced a third wave of the COVID-19 epidemic since the end of May, 2021, coincidingwith the rapid spread of the delta (B.1.617.2) variant, despite high levels of vaccination among adults. Vaccinationrates (single dose) in England are lower among children aged 16–17 years and 12–15 years, whose vaccination inEngland commenced in August and September, 2021, respectively. We aimed to analyse the underlying dynamicsdriving patterns in SARS-CoV-2 prevalence during September, 2021, in England.Methods The REal-time Assessment of Community Transmission-1 (REACT-1) study, which commenced datacollection in May, 2020, involves a series of random cross-sectional surveys in the general population of Englandaged 5 years and older. Using RT-PCR swab positivity data from 100 527 participants with valid throat and noseswabs in round 14 of REACT-1 (Sept 9–27, 2021), we estimated community-based prevalence of SARS-CoV-2 andvaccine effectiveness against infection by combining round 14 data with data from round 13 (June 24 to July 12, 2021;n=172 862).Findings During September, 2021, we estimated a mean RT-PCR positivity rate of 0·83% (95% CrI 0·76–0·89), with areproduction number (R) overall of 1·03 (95% CrI 0·94–1·14). Among the 475 (62·2%) of 764 sequenced positiveswabs, all were of the delta variant; 22 (4·63%; 95% CI 3·07–6·91) included the Tyr145His mutation in the spikeprotein associated with the AY.4 sublineage, and there was one Glu484Lys mutation. Age, region, key worker status,and household size jointly contributed to the risk of swab positivity. The highest weighted prevalence was observedamong children aged 5–12 years, at 2·32% (95% CrI 1·96–2·73) and those aged 13–17 years, at 2·55% (2·11–3·08).The SARS-CoV-2 epidemic grew in those aged 5–11 years, with an R of 1&m
Eales O, Ainslie KEC, Walters CE, et al., 2022, Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number
<jats:title>Abstract</jats:title><jats:p>The time-varying reproduction number (<jats:bold><jats:italic>R</jats:italic></jats:bold><jats:sub><jats:bold><jats:italic>t</jats:italic></jats:bold></jats:sub>) can change rapidly over the course of a pandemic due to changing restrictions, behaviours, and levels of population immunity. Many methods exist that allow the estimation of <jats:bold><jats:italic>R</jats:italic></jats:bold><jats:sub><jats:bold><jats:italic>t</jats:italic></jats:bold></jats:sub> from case data. However, these are not easily adapted to point prevalence data nor can they infer <jats:bold><jats:italic>R</jats:italic></jats:bold><jats:sub><jats:bold><jats:italic>t</jats:italic></jats:bold></jats:sub> across periods of missing data. We developed a Bayesian P-spline model suitable for fitting to a wide range of epidemic time-series, including point-prevalence data. We demonstrate the utility of the model by fitting to periodic daily SARS-CoV-2 swab-positivity data in England from the first 7 rounds (May 2020 – December 2020) of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Estimates of <jats:bold><jats:italic>R</jats:italic></jats:bold><jats:sub><jats:bold><jats:italic>t</jats:italic></jats:bold></jats:sub> over the period of two subsequent rounds (6-8 weeks) and single rounds (2-3 weeks) inferred using the Bayesian P-spline model were broadly consistent with estimates from a simple exponential model, with overlapping credible intervals. However, there were sometimes substantial differences in point estimates. The Bayesian P-spline model was further able to infer changes in <jats:bold><jats:italic>R</jats:italic></jats:bold><jats:sub><jats
Liang J-B, Yuan H-Y, Li K-K, et al., 2022, Path to normality: Assessing the level of social-distancing measures relaxation against antibody-resistant SARS-CoV-2 variants in a partially- vaccinated population, COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, Vol: 20, Pages: 4052-4059, ISSN: 2001-0370
Eales O, Page AJ, de Oliveira Martins L, et al., 2021, SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2
<jats:title>Abstract</jats:title><jats:p>Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Here we present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. From 9 to 27 September 2021 (round 14) and 19 October to 5 November 2021 (round 15), all lineages sequenced within REACT-1 were Delta or a Delta sub-lineage with 44 unique lineages identified. The proportion of the original Delta variant (B.1.617.2) was found to be increasing between September and November 2021, which may reflect an increasing number of sub-lineages which have yet to be identified. The proportion of B.1.617.2 was greatest in London, which was further identified as a region with an increased level of genetic diversity. The Delta sub-lineage AY.4.2 was found to be robustly increasing in proportion, with a reproduction number 15% (8%, 23%) greater than its parent and most prevalent lineage, AY.4. Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Though no difference in the viral load based on cycle threshold (Ct) values was identified, a lower proportion of those infected with AY.4.2 had symptoms for which testing is usually recommend (loss or change of sense of taste, loss or change of sense of smell, new persistent cough, fever), compared to AY.4 (p = 0.026). The evolutionary rate of SARS-CoV-2, as measured by the mutation rate, was fou
Elliott P, Haw D, Wang H, et al., 2021, Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant, Science, Vol: 374, Pages: 1-11, ISSN: 0036-8075
SARS-CoV-2 infections were rising during early summer 2021 in many countries associated with the Delta variant. We assessed RT-PCR swab-positivity in the REal-time Assessment of Community Transmission-1 (REACT-1) study in England. We observed sustained exponential growth with average doubling time (June-July 2021) of 25 days driven by complete replacement of Alpha variant by Delta, and by high prevalence at younger less-vaccinated ages. Unvaccinated people were three times more likely than double-vaccinated people to test positive. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination.
Davies B, Araghi M, Moshe M, et al., 2021, Acceptability, usability and performance of lateral flow immunoassay tests for SARS-CoV-2 antibodies: REACT-2 study of self-testing in non-healthcare key workers, Open Forum Infectious Diseases, Vol: 8, ISSN: 2328-8957
Background Seroprevalence studies are essential to understand the epidemiology of SARS-CoV-2. Various technologies, including laboratory assays and point-of-care self-tests, are available for antibody testing. The interpretation of seroprevalence studies requires comparative data on the performance of antibody tests. Methods In June 2020, current and former members of the UK Police forces and Fire service performed a self-test lateral flow immunoassay (LFIA), had a nurse-performed LFIA and provided a venous blood sample for ELISA . We present the prevalence of antibodies to SARS-CoV-2; the acceptability and usability of self-test LFIAs; and determine the sensitivity and specificity of LFIAs compared to laboratory ELISA. Results In this cohort of 5189 current and former members of the Police service and 263 members of the Fire service, 7.4% (396/5,348; 95% CI, 6.7-8.1) were antibody positive. Seroprevalence was 8.9% (6.9-11.4) in those under 40 years, 11.5% (8.8-15.0) in those of non-white ethnicity and 7.8% (7.1-8.7) in those currently working. Self-test LFIA had an acceptability of 97.7% and a usability of 90.0%. There was substantial agreement between within-participant LFIA results (kappa 0.80; 0.77-0.83). The LFIAs had a similar performance: compared to ELISA, sensitivity was 82.1% (77.7-86.0) self-test and 76.4% (71.9-80.5) nurse-performed with specificity of 97.8% (97.3-98.2) and 98.5% (98.1-98.8) respectively. Conclusion A greater proportion of this non-healthcare key worker cohort showed evidence of previous infection with SARS-CoV-2 than the general population at 6.0% (5.8-6.1) following the first wave in England. The high acceptability and usability reported by participants and similar performance of self-test and nurse-performed LFIAs indicate that the self-test LFIA is fit for purpose for home-testing in occupational and community prevalence studies.
Pollett S, Johansson MA, Reich NG, et al., 2021, Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines, PLOS MEDICINE, Vol: 18, ISSN: 1549-1277
- Author Web Link
- Cite
- Citations: 6
Elliott J, Whitaker M, Bodinier B, et al., 2021, Predictive symptoms for COVID-19 in the community: REACT-1 study of over one million people, PLoS Medicine, Vol: 18, Pages: 1-14, ISSN: 1549-1277
Background:Rapid detection, isolation and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and whether predictive symptoms differ between B.1.1.7 (Alpha) lineage (predominating as of April 2021in the USA, UK and elsewhere) and wild type.Methods and Findings:We obtained throat and nose swabs with valid SARS-CoV-2 polymerase chain reaction (PCR) test results from 1,147,370 volunteers aged 5 years and above (6,450 positives) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%-27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least one symptom identified seven symptoms as jointly and positively predictive of PCR positivity in rounds 2–7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss and muscle aches. The resulting model (rounds 2–7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same seven symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. Main
Eales O, Walters C, Wang H, et al., 2021, Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2
BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administeredthroat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community.MethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines.ResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportionof positive individuals detected on first swab, was found to be higher 𝑃 for those with an 0 initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in socialdistancing measures.DiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has hig
Ward H, Atchison C, Whitaker M, et al., 2021, Increasing SARS-CoV-2 antibody prevalence in England at the start of the second wave: REACT-2 Round 4 cross-sectional study in 160,000 adults
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>REACT-2 Study 5 is a population survey of the prevalence of SARS-CoV-2 antibodies in the community in England.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We contacted a random sample of the population by sending a letter to named individuals aged 18 or over from the NHS GP registrations list. We then sent respondents a lateral flow immunoassay (LFIA) kit for SARS-CoV-2 antibody self-testing and asked them to perform the test at home and complete a questionnaire, including reporting of their test result. Overall, 161,537 adults completed questionnaires and self-administered LFIA tests for IgG against SARS-CoV-2 between 27 October and 10 November 2020.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The overall adjusted and weighted prevalence was 5.6% (95% CI 5.4-5.7). This was an increase from 4.4% (4.3-4.5) in round 3 (September), a relative increase of 26.9% (24.0-29.9).The largest increase by age was in the 18 to 24 year old age group, which increased (adjusted and weighted) from 6.7% (6.3-7.2) to 9.9% (9.3-10.4), and in students, (adjusted, unweighted) from 5.9% (4.8-7.1) to 12.1% (10.8-13.5). Prevalence increased most in Yorkshire and The Humber, from 3.4% (3.0-3.8) to 6.3% (5.9-6.8) and the North West from 4.5% (4.2-4.9) to 7.7% (7.2-8.1). In contrast, the prevalence in London was stable, at 9.5% (9.0-9.9) and 9.5% (9.1-10.0) in rounds 3 and 4 respectively. We found the highest prevalence in people of Bangladeshi 15.1% (10.9-20.5), Pakistani 13.9% (11.2-17.2) and African 13.5% (10.7-16.8) ethnicity, and lowest in those of white British ethnicity at 4.2% (4.0-4.3).</jats:p></jats:sec><jats:sec><jats:title>Interpretation</jats:title><jats:p>The second wave of infection in England is apparen
Ward H, Whitaker M, Tang SN, et al., 2021, Vaccine uptake and SARS-CoV-2 antibody prevalence among 207,337 adults during May 2021 in England: REACT-2 study
Background The programme to vaccinate adults in England has been rapidly implementedsince it began in December 2020. The community prevalence of SARS-CoV-2 anti-spikeprotein antibodies provides an estimate of total cumulative response to natural infection andvaccination. We describe the distribution of SARS-CoV-2 IgG antibodies in adults inEngland in May 2021 at a time when approximately 7 in 10 adults had received at least onedose of vaccine.Methods Sixth round of REACT-2 (REal-time Assessment of Community Transmission-2),a cross-sectional random community survey of adults in England, from 12 to 25 May 2021;207,337 participants completed questionnaires and self-administered a lateral flowimmunoassay test producing a positive or negative result.Results Vaccine coverage with one or more doses, weighted to the adult population inEngland, was 72.9% (95% confidence interval 72.7-73.0), varying by age from 25.1% (24.5-25.6) of those aged 18 to 24 years, to 99.2% (99.1-99.3) of those 75 years and older. Inadjusted models, odds of vaccination were lower in men (odds ratio [OR] 0.89 [0.85-0.94])than women, and in people of Black (0.41 [0.34-0.49]) compared to white ethnicity. Therewas higher vaccine coverage in the least deprived and highest income households. Peoplewho reported a history of COVID-19 were less likely to be vaccinated (OR 0.61 [0.55-0.67]).There was high coverage among health workers (OR 9.84 [8.79-11.02] and care workers (OR4.17 [3.20-5.43]) compared to non-key workers, but lower in hospitality and retail workers(OR 0.73 [0.64-0.82] and 0.77 [0.70-0.85] respectively) after adjusting for age and keycovariates.
Riley S, Eales O, Haw D, et al., 2021, REACT-1 round 13 interim report: acceleration of SARS-CoV-2 Delta epidemic in the community in England during late June and early July 2021
BackgroundDespite high levels of vaccination in the adult population, cases of COVID-19 have risenexponentially in England since the start of May 2021 driven by the Delta variant. However,with far fewer hospitalisations and deaths per case during the recent growth in casescompared with 2020, it is intended that all remaining social distancing legislation in Englandwill be removed from 19 July 2021.MethodsWe report interim results from round 13 of the REal-time Assessment of CommunityTransmission-1 (REACT-1) study in which a cross-sectional sample of the population ofEngland was asked to provide a throat and nose swab for RT-PCR and to answer aquestionnaire. Data collection for this report (round 13 interim) was from 24 June to 5 July2021.ResultsIn round 13 interim, we found 237 positives from 47,729 swabs giving a weighted prevalenceof 0.59% (0.51%, 0.68%) which was approximately four-fold higher compared with round 12at 0.15% (0.12%, 0.18%). This resulted from continued exponential growth in prevalencewith an average doubling time of 15 (13, 17) days between round 12 and round 13.However, during the recent period of round 13 interim only, we observed a shorter doublingtime of 6.1 (4.0, 12) days with a corresponding R number of 1.87 (1.40, 2.45). There weresubstantial increases in all age groups under the age of 75 years, and especially at youngerages, with the highest prevalence in 13 to 17 year olds at 1.33% (0.97%, 1.82%) and in 18 to24 years olds at 1.40% (0.89%, 2.18%). Infections have increased in all regions with thelargest increase in London where prevalence increased more than eight-fold from 0.13%(0.08%, 0.20%) in round 12 to 1.08% (0.79%, 1.47%) in round 13 interim. Overall,prevalence was over 3 times higher in the unvaccinated compared with those reporting twodoses of vaccine in both round 12 and round 13 interim, although there was a similarproportional increase in prevalence in vaccinated and unvaccinated individuals between thetwo rounds.DiscussionWe
Gaythorpe K, Bhatia S, Mangal T, et al., 2021, Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility, Scientific Reports, Vol: 11, Pages: 1-14, ISSN: 2045-2322
Background: SARS-CoV-2 infections have been reported in all age groups including infants, children, and adolescents. However, the role of children in the COVID-19 pandemic is still uncertain. This systematic review of early studies synthesises evidence on the susceptibility of children to SARS-CoV-2 infection, the severity and clinical outcomes in children with SARS-CoV-2 infection, and the transmissibility of SARS-CoV-2 by children in the early phases of the COVID-19 pandemic. Methods and findings: A systematic literature review was conducted in PubMed. Reviewers extracted data from relevant, peer-reviewed studies published up to July 4th 2020 during the first wave of the SARS-CoV-2 outbreak using a standardised form and assessed quality using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. For studies included in the meta-analysis, we used a random effects model to calculate pooled estimates of the proportion of children considered asymptomatic or in a severe or critical state. We identified 2,775 potential studies of which 128 studies met our inclusion criteria; data were extracted from 99, which were then quality assessed. Finally, 29 studies were considered for the meta-analysis that included information of symptoms and/or severity, these were further assessed based on patient recruitment. Our pooled estimate of the proportion of test positive children who were asymptomatic was 21.1% (95% CI: 14.0 - 28.1%), based on 13 included studies, and the proportion of children with severe or critical symptoms was 3.8% (95% CI: 1.5 - 6.0%), based on 14 included studies. We did not identify any studies designed to assess transmissibility in children and found that susceptibility to infection in children was highly variable across studies.Conclusions: Children’s susceptibility to infection and onward transmissibility relative to adults is still unclear and varied widely between studies. However, it is evident that most children e
Turtle J, Riley P, Ben-Nun M, et al., 2021, Accurate influenza forecasts using type-specific incidence data for small geographic units, PLOS COMPUTATIONAL BIOLOGY, Vol: 17, ISSN: 1553-734X
Whitaker M, Elliott J, Chadeau-Hyam M, et al., 2021, Persistent symptoms following SARS-CoV-2 infection in a random community sample of 508,707 people
IntroductionLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorlydefined syndrome. There is uncertainty about its predisposing factors and the extent of theresultant public health burden, with estimates of prevalence and duration varying widely.MethodsWithin rounds 3–5 of the REACT-2 study, 508,707 people in the community in England wereasked about a prior history of COVID-19 and the presence and duration of 29 differentsymptoms. We used uni- and multivariable models to identify predictors of persistence ofsymptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12weeks, and used unsupervised learning to cluster individuals by symptoms experienced.ResultsAmong the 508,707 participants, the weighted prevalence of self-reported COVID-19 was 19.2%(95% CI: 19.1,19.3). 37.7% of 76,155 symptomatic people post COVID-19 experienced at leastone symptom, while 14.8% experienced three or more symptoms, lasting 12 weeks or more. Thisgives a weighted population prevalence of persistent symptoms of 5.75% (5.68, 5.81) for one and2.22% (2.1, 2.26) for three or more symptoms. Almost a third of people 8,771/28,713 (30.5%)with at least one symptom lasting 12 weeks or more reported having had severe COVID-19symptoms (“significant effect on my daily life”) at the time of their illness, giving a weightedprevalence overall for this group of 1.72% (1.69,1.76). The prevalence of persistent symptomswas higher in women than men (OR: 1.51 [1.46,1.55]) and, conditional on reporting symptoms,risk of persistent symptoms increased linearly with age by 3.5 percentage points per decade oflife. Obesity, smoking or vaping, hospitalisation , and deprivation were also associated with ahigher probability of persistent symptoms, while Asian ethnicity was associated with a lowerprobability. Two stable clusters were identified based on symptoms that persisted for 12 weeks ormore: in the largest cluster, tiredness predominated
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.