Asymptotic Analysis of Optimal Vaccination Policies

Targeted vaccination policies can have a significant impact on the number of infections and deaths in an epidemic. However, optimising such policies is complicated and the resultant solution may be difficult to explain to policy-makers and to the public. The key novelty of this paper is a derivation of the leading order optimal vaccination policy under multi-group SIR (Susceptible-Infected-Recovered) dynamics in two different cases. Firstly, it considers the case of a small vulnerable subgroup in a population and shows that (in the asymptotic limit) it is optimal to vaccinate this group first, regardless of the properties of the other groups. Then, it considers the case of a small vaccine supply and transforms the optimal vaccination problem into a simple knapsack problem by linearising the final size equations. Both of these cases are then explored further through numerical examples which show that these solutions are also directly useful for realistic parameter values. Moreover, the findings of this paper give some general principles for optimal vaccination policies which will help policy-makers and the public to understand the reasoning behind optimal vaccination programs in more generic cases. Author summaryThe COVID-19 pandemic has illustrated the importance of vaccination programs in preventing infections and deaths from an epidemic. A common feature of vaccination programs across the world has been a prioritisation of different groups within each countrys population, particularly those who are more vulnerable to the disease. Finding the best priority order is crucial, but may be complicated and difficult to justify to policy-makers and the public. In this paper, we consider two extreme cases where the best prioritisation order can be mathematically derived. Firstly, we consider the case of a population with a very small, very vulnerable group and show that this group should always be vaccinated first. Then, we consider the case of a small supply of vaccines and derive an equation which gives the best prioritisation order. Understanding these extreme cases is important, as it highlights general principles of optimal policies which will be useful when understanding the solution in more complicated settings.

Optimality of Maximal-Effort Vaccination

It is widely acknowledged that vaccinating at maximal effort in the face of an ongoing epidemic is the best strategy to minimise infections and deaths from the disease. Despite this, no one has proved that this is guaranteed to be true if the disease follows multi-group SIR (Susceptible-Infected-Recovered) dynamics. This paper provides a novel proof of this principle for the existing SIR framework, showing that the total number of deaths or infections from an epidemic is decreasing in vaccination effort. Furthermore, it presents a novel model for vaccination which assumes that vaccines are distributed randomly to the unvaccinated population and suggests, using COVID-19 data, that this more accurately captures vaccination dynamics than the model commonly found in the literature. However, as the novel model provides a strictly larger set of possible vaccination policies, the results presented in this paper hold for both models. HighlightsO_LIIt is proved that it is optimal to vaccinate at maximal effort C_LIO_LIA novel model of vaccination is explored with COVID-19 vaccine data C_LIO_LIResults are presented which hold for both the novel and classical vaccination models. C_LI

Novel early-warning system for evaluating control and elimination of SARS-CoV-2 reveals alignment of policy with local transmission in New Zealand

Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur, can separate decisive from ineffective policy. By generalising and fusing recent approaches, we propose a novel early-warning framework that maximises the information extracted from low-incidence data to robustly infer the chances of sustained local-transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions.

Quantifying the information in noisy epidemic curves

Reliably estimating the dynamics of transmissible diseases from noisy surveillance data is an enduring problem in modern epidemiology. Key parameters, such as the instantaneous reproduction number, Rt at time t, are often inferred from incident time series, with the aim of informing policymakers on the growth rate of outbreaks or testing hypotheses about the effectiveness of public health interventions. However, the reliability of these inferences depends critically on reporting errors and latencies innate to those time series. While studies have proposed corrections for these issues, methodology for formally assessing how these sources of noise degrade Rt estimate quality is lacking. By adapting Fisher information and experimental design theory, we develop an analytical framework to quantify the uncertainty induced by under-reporting and delays in reporting infections. This yields a novel metric, defined by the geometric means of reporting and cumulative delay probabilities, for ranking surveillance data informativeness. We apply this metric to two primary data sources for inferring Rt: epidemic case and death curves. We find that the assumption of death curves as more reliable, commonly made for acute infectious diseases such as COVID-19 and influenza, is not obvious and possibly untrue in many settings. Our framework clarifies and quantifies how actionable information about pathogen transmissibility is lost due to surveillance limitations.

Prevalence and associated factors with mental health outcomes among interns and residents physicians during COVID-19 epidemic in Panama: a cross-sectional study

BackgroundA new coronavirus SARS-CoV-2 was associated with a newly identified respiratory syndrome, COVID-19 in Wuhan, China, in early December 2019. SARS-CoV-2 rapidly spread across the globe resulting in 117 million cases and 2.59 million deaths by March 2021. Rapidly increased numbers of COVID-19 cases overwhelmed public health systems across the world, imposing increased working hours and workloads for health care workers. Here, we have evaluated the prevalence of health outcomes and associated factors of interns and resident physicians in Panama. MethodsA cross-sectional study was undertaken during July 23, 2020, to August 13, 2020, to evaluate the prevalence of health outcomes and associated factors in interns and residents across Panama. Snowball sampling was used to recruit participants. Then an electronic questionnaire with scales to evaluate anxiety disorders (GAD-7), depression (PHQ-9) and post-traumatic stress (IES-R) was evaluated. In addition, socio-demographic variables, clinical history of mental disorders and COVID-19 exposure were evaluated. Independent analyses for each mental health outcome were undertaken using a logistic regression analysis. ResultsA total of 517/1205 (42.9%) interns and residents were nationwide recruited. Of these 274 (53.0%) were interns and 243 (47.0%) residents. The overall prevalence of depression symptoms was 25.3%, 13.7% anxiety and 12.2% post-traumatic stress. At least, 9.3% participants reported having suicidal ideation. The most parsimonious model showed females had a higher prevalence of mental health disorders, in all results and the married participants were more likely to present depression (OR, 1.73; 95% CI, 1.03-2.91; P = 0.039) or at least one alteration to mental health (OR, 1.66; 95% CI, 1.03-2.68; P = 0.039). Resident physicians in surgical specialties were less likely to have post-traumatic stress (OR, 0.20; 95% CI, 0.06-0.63; P = 0.006) or at least one mental health disturbance (OR, 0.46; 95% CI, 0.26-0.83; P = 0.010). A history of psychological trauma and psychiatric pathology were risk factors for most of the disorders investigated. ConclusionsA high prevalence of mental health disorders was found, showing the need to mitigate this emotional burden among healthcare workers in the current context of the COVID-19 pandemic.

Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates

BackgroundPhase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. MethodsWe developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS-CoV-2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. ResultsVE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively. ConclusionMultiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.

A comparative analysis of statistical methods to estimate the reproduction number in emerging epidemics with implications for the current COVID-19 pandemic

As the SARS-CoV-2 pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. Using simulated epidemic data we assess the performance of 6 commonly-used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario - fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. We find that all methods considered here frequently over-estimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision, particularly for data with significant over-dispersion. As localised epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts. Significance StatementIn line with a real-time outbreak analysis we use simulated epidemic data to assess the performance of 6 commonly-used statistical methods to estimate the reproduction number, R0, at different time points during the epidemic growth phase. We find that estimates of R0 are frequently overestimated by these methods in the early stages of epidemic growth, with decreasing bias when fitting to an increasing number of time points. Reductions in R0 estimates obtained at sequential time points during early epidemic growth may reflect increased methodological accuracy rather than reductions in pathogen transmissibility or effectiveness of interventions. As SARS-CoV-2 continues its geographic spread, awareness of this bias will be important for appropriate interpretation of results and subsequent guidance for control efforts.

Quantifying changes in the IFR and IHR over 23 months of the SARS-CoV-2 pandemic in England

BackgroundThe 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 Englands mass vaccination campaign. MethodsHere, 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. ResultsDuring 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 Deltas 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. ConclusionEven though many populations have high levels of immunity to SARS-CoV-2 from vaccination and natural infection, waning of immunity and variant emergence will continue to be an upwards pressure on IHR and IFR. As investments in community surveillance are scaled back, alternative methods should be developed to accurately track the ever changing relationship between infection, hospitalisation and death.

Transmission dynamics of SARS-CoV-2 in the hospital setting

BackgroundSARS-CoV-2 can spread efficiently in hospitals, but the transmission pathways amongst patients and healthcare workers are unclear. MethodsWe analysed data from four teaching hospitals in Oxfordshire, UK, from January to October 2020. Associations between infectious SARS-CoV-2 individuals and infection risk were quantified using logistic, generalised additive and linear mixed models. Cases were classified as community- or hospital-acquired using likely incubation periods. ResultsNine-hundred and twenty of 66184 patients who were hospitalised during the study period had a positive SARS-CoV-2 PCR test within the same period (1%). Out of these, 571 patients had their first positive PCR tests while hospitalised (62%), and 97 of these occurred at least seven days after admission (11%). Amongst the 5596 healthcare workers, 615 (11%) tested positive during the study period using PCR or serological tests. For susceptible patients, one day in the same ward with another patient with hospital-acquired SARS-CoV-2 was associated with an additional eight infections per 1000 susceptible patients (95%CrI 6-10). Exposure to an infectious patient with community-acquired COVID-19 or to an infectious healthcare worker was associated with substantially lower infection risks (2/1000 susceptible patients/day, 95%CrI 1-2). As for healthcare worker infections, exposure to an infectious patient with hospital-acquired SARS-CoV-2 or to an infectious healthcare worker were both associated with an additional one infection per 1000 susceptible healthcare workers per day (95%CrI 1-2). Exposure to an infectious patient with community-acquired SARS-CoV-2 was associated with half this risk (0.5/1000 susceptible healthcare workers/day, 95%CrI 0.3-0.7). InterpretationExposure to patients with hospital-acquired SARS-CoV-2 poses a substantial infection risk. Infection control measures to limit nosocomial transmission must be optimised to protect both staff and patients from SARS-CoV-2 infection. FundingNational Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with Public Health England (PHE) (NIHR200915). Medical Research Council, Nosocomial transmission of SARS-CoV-2 (MR/V028456/1). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched the PubMed database using the search terms ("COVID-19" OR "SARS-CoV-2") AND ("nosocomial" OR "hospital") AND ("transmission") in either the abstracts or titles, for English-language articles published up to March 31, 2021. This returned 748 results, out of which ten reported transmission events in the hospital setting quantitatively. These publications can be broadly categorised to epidemiological descriptions of isolated outbreaks (5) or contact tracing of patients exposed to infected healthcare workers (1), retrospective cohort studies involving a particular group of patients, e.g., patients who underwent surgical procedures (2), and using genomic sequencing to identify transmission clusters (2). None of the studies reported the comparative transmission rates of SARS-CoV-2 amongst patients and staff. Added value of this studyThis study reports the analysis of a large observational dataset collected from a group of hospitals in the UK over eight months, consisting of both hospitalised patients and healthcare workers. Based on these detailed individual-level data, we quantified the associations between patient and healthcare worker characteristics and risks for acquiring nosocomial SARS-CoV-2 infection after adjusting for their exposures to SARS-CoV-2. Over the study period, we describe how risk of acquisition changes both with calendar time and over a patients hospital stay. By linking the presence of infected and susceptible patients and healthcare workers by time and ward locations, we quantify the relative importance of the transmission pathways for both the susceptible patients and healthcare workers. Implications of all the available evidenceNosocomial transmission of SARS-CoV-2 is common. Identifying the drivers of SARS-CoV-2 transmissions in the hospital setting is essential for designing infection prevention and control policies to minimise the added pressure from such events on our health systems. We found that newly infected patients who acquired SARS-CoV-2 in the hospital pose the highest risk of onward transmission to other patients and healthcare workers. Infection control and prevention efforts need to be enhanced around these patients to prevent further transmissions and studies assessing the effectiveness of these policies are needed.

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

BackgroundREACT-2 Study 5 is a population survey of the prevalence of SARS-CoV-2 antibodies in the community in England. MethodsWe 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. ResultsThe 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). InterpretationThe second wave of infection in England is apparent in increasing antibody prevalence, particularly in younger people, students, and in the Northern Regions. By late October a large proportion of the population remained susceptible to SARS-CoV-2 infection in England based on naturally acquired immunity from the first and early second wave.

Inference of COVID-19 epidemiological distributions from Brazilian hospital data

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalised with COVID-19 using a large dataset (N = 21,000 - 157,000) from the Brazilian Sistema de Informacao de Vigilancia Epidemiologica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2-17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalised lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.

Variant-specific symptoms of COVID-19 among 1,542,510 people in England

Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission -1 (REACT-1) study has been monitoring the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the different variants over that period, with lower reporting of loss of sense of smell and taste for Omicron compared to previous variants, and higher reporting of cold-like and influenza-like symptoms, controlling for vaccination status. Contrary to the perception that recent variants have become successively milder, Omicron BA.2 was associated with reporting more symptoms, with greater disruption to daily activities, than BA.1. With restrictions lifted and routine testing limited in many countries, monitoring the changing symptom profiles associated with SARS-CoV-2 infection and induced changes in daily activities will become increasingly important.

REACT-1 round 7 updated report: regional heterogeneity in changes in prevalence of SARS-CoV-2 infection during the second national COVID-19 lockdown in England

BackgroundEngland exited a four-week second national lockdown on 2nd December 2020 initiated in response to the COVID-19 pandemic. Prior results showed that prevalence dropped during the first half of lockdown, with greater reductions in higher-prevalence northern regions. MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positivity in England, designed to monitor the spread of the epidemic and thus increase situational awareness. Round 7 of REACT-1 commenced swab-collection on 13th November 2020. A prior interim report included data from 13th to 24th November 2020 for 105,122 participants. Here, we report data for the entire round with swab results obtained up to 3rd December 2020. ResultsBetween 13th November and 3rd December (round 7) there were 1,299 positive swabs out of 168,181 giving a weighted prevalence of 0.94% (95% CI 0.87%, 1.01%) or 94 per 10,000 people infected in the community in England. This compares with a prevalence of 1.30% (1.21%, 1.39%) from 16th October to 2nd November 2020 (round 6), a decline of 28%. Prevalence during the latter half of round 7 was 0.91% (95% CI, 0.81%, 1.03%) compared with 0.96% (0.87%, 1.05%) in the first half. The national R number in round 7 was estimated at 0.96 (0.88, 1.03) with a decline in prevalence observed during the first half of this period no longer apparent during the second half at the end of lockdown. During round 7 there was a marked fall in prevalence in West Midlands, a levelling off in some regions and a rise in London. R numbers at regional level ranged from 0.60 (0.41, 0.80) in West Midlands up to 1.27 (1.04, 1.54) in London, where prevalence was highest in the east and south-east of the city. Nationally, between 13th November and 3rd December, the highest prevalence was in school-aged children especially at ages 13-17 years at 2.04% (1.69%, 2.46%), or approximately 1 in 50. ConclusionBetween the previous round and round 7 (during lockdown), there was a fall in prevalence of SARS-CoV-2 swab-positivity nationally, but it did not fall uniformly over time or by geography. Continued vigilance is required to reduce rates of infection until effective immunity at the population level can be achieved through the vaccination programme.

REACT-1 round 6 updated report: high prevalence of SARS-CoV-2 swab positivity with reduced rate of growth in England at the start of November 2020

BackgroundEngland is now in the midst of its second wave of the COVID-19 pandemic. Multiple regions of the country are at high infection prevalence and all areas experienced rapid recent growth of the epidemic during October 2020. MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positivity in England designed to monitor the spread of the epidemic and thus increase situational awareness. Round 6 of REACT-1 commenced swab-collection on 16th October. A prior interim report included data from 16th to 25th October for 85,971 participants. Here, we report data for the entire round on 160,175 participants with swab results obtained up to 2nd November 2020. ResultsOverall weighted prevalence of infection in the community in England was 1.3% or 130 people per 10,000 infected, up from 60 people per 10,000 in the round 5 report (18th September to 5th October 2020), doubling every 24 days on average since the prior round. The corresponding R number was estimated to be 1.2. Prevalence of infection was highest in North West (2.4%, up from 1.2%), followed by Yorkshire and The Humber (2.3% up from 0.84%), West Midlands (1.6% up from 0.60%), North East (1.5% up from 1.1%), East Midlands (1.3% up from 0.56%), London (0.97%, up from 0.54%), South West (0.80% up from 0.33%), South East (0.69% up from 0.29%), and East of England (0.69% up from 0.30%). Rapid growth in the South observed in the first half of round 6 was no longer apparent in the second half of round 6. We also observed a decline in prevalence in Yorkshire and The Humber during this period. Comparing the first and second halves of round 6, there was a suggestion of decline in weighted prevalence in participants aged 5 to 12 years and in those aged 25 to 44 years. While prevalence remained high, in the second half of round 6 there was suggestion of a slight fall then rise that was seen nationally and also separately in both the North and the South. ConclusionThe impact of the second national lockdown in England is not yet known. We provide here a detailed description of swab-positivity patterns at national, regional and local scales for the period immediately preceding lockdown, against which future trends in prevalence can be evaluated.

High prevalence of SARS-CoV-2 swab positivity and increasing R number in England during October 2020: REACT-1 round 6 interim report

BackgroundREACT-1 measures prevalence of SARS-CoV-2 infection in representative samples of the population in England using PCR testing from self-administered nose and throat swabs. Here we report interim results for round 6 of observations for swabs collected from the 16th to 25th October 2020 inclusive. MethodsREACT-1 round 6 aims to collect data and swab results from 160,000 people aged 5 and above. Here we report results from the first 86,000 individuals. We estimate prevalence of PCR-confirmed SARS-CoV-2 infection, reproduction numbers (R) and temporal trends using exponential growth or decay models. Prevalence estimates are presented both unweighted and weighted to be representative of the population of England, accounting for response rate, region, deprivation and ethnicity. We compare these interim results with data from round 5, based on swabs collected from 18th September to 5th October 2020 inclusive. ResultsOverall prevalence of infection in the community in England was 1.28% or 128 people per 10,000, up from 60 per 10,000 in the previous round. Infections were doubling every 9.0 (6.1, 18) days with a national reproduction number (R) estimated at 1.56 (1.27, 1.88) compared to 1.16 (1.05, 1.27) in the previous round. Prevalence of infection was highest in Yorkshire and The Humber at 2.72% (2.12%, 3.50%), up from 0.84% (0.60%, 1.17%), and the North West at 2.27% (1.90%, 2.72%), up from 1.21% (1.01%, 1.46%), and lowest in South East at 0.55% (0.45%, 0.68%), up from 0.29% (0.23%, 0.37%). Clustering of cases was more prevalent in Lancashire, Manchester, Liverpool and West Yorkshire, West Midlands and East Midlands. Interim estimates of R were above 2 in the South East, East of England, London and South West, but with wide confidence intervals. Nationally, prevalence increased across all age groups with the greatest increase in those aged 55-64 at 1.20% (0.99%, 1.46%), up 3-fold from 0.37% (0.30%, 0.46%). In those aged over 65, prevalence was 0.81% (0.58%, 0.96%) up 2-fold from 0.35% (0.28%, 0.43%). Prevalence remained highest in 18 to 24-year olds at 2.25% (1.47%, 3.42%). ConclusionThe co-occurrence of high prevalence and rapid growth means that the second wave of the epidemic in England has now reached a critical stage. Whether via regional or national measures, it is now time-critical to control the virus and turn R below one if further hospital admissions and deaths from COVID-19 are to be avoided.

Declining prevalence of antibody positivity to SARS-CoV-2: a community study of 365,000 adults

BackgroundThe prevalence and persistence of antibodies following a peak SARS-CoV-2 infection provides insights into its spread in the community, the likelihood of reinfection and potential for some level of population immunity. MethodsPrevalence of antibody positivity in England, UK (REACT2) with three cross-sectional surveys between late June and September 2020. 365104 adults used a self-administered lateral flow immunoassay (LFIA) test for IgG. A laboratory comparison of LFIA results to neutralization activity in panel of sera was performed. ResultsThere were 17,576 positive tests over the three rounds. Antibody prevalence, adjusted for test characteristics and weighted to the adult population of England, declined from 6.0% [5.8, 6.1], to 4.8% [4.7, 5.0] and 4.4% [4.3, 4.5], a fall of 26.5% [-29.0, -23.8] over the three months of the study. There was a decline between rounds 1 and 3 in all age groups, with the highest prevalence of a positive result and smallest overall decline in positivity in the youngest age group (18-24 years: -14.9% [-21.6, -8.1]), and lowest prevalence and largest decline in the oldest group (75+ years: -39.0% [-50.8, -27.2]); there was no change in antibody positivity between rounds 1 and 3 in healthcare workers (+3.45% [-5.7, +12.7]). The decline from rounds 1 to 3 was largest in those who did not report a history of COVID-19, (-64.0% [-75.6, -52.3]), compared to -22.3% ([-27.0, -17.7]) in those with SARS-CoV-2 infection confirmed on PCR. DiscussionThese findings provide evidence of variable waning in antibody positivity over time such that, at the start of the second wave of infection in England, only 4.4% of adults had detectable IgG antibodies using an LFIA. Antibody positivity was greater in those who reported a positive PCR and lower in older people and those with asymptomatic infection. These data suggest the possibility of decreasing population immunity and increasing risk of reinfection as detectable antibodies decline in the population.

REACT-1 round 10 report: Level prevalence of SARS-CoV-2 swab-positivity in England during third national lockdown in March 2021

BackgroundIn England, hospitalisations and deaths due to SARS-CoV-2 have been falling consistently since January 2021 during the third national lockdown of the COVID-19 pandemic. The first significant relaxation of that lockdown occurred on 8 March when schools reopened. MethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study augments routine surveillance data for England by measuring swab-positivity for SARS-CoV-2 in the community. The current round, round 10, collected swabs from 11 to 30 March 2021 and is compared here to round 9, in which swabs were collected from 4 to 23 February 2021. ResultsDuring round 10, we estimated an R number of 1.00 (95% confidence interval 0.81, 1.21). Between rounds 9 and 10 we estimated national prevalence has dropped by [~]60% from 0.49% (0.44%, 0.55%) in February to 0.20% (0.17%, 0.23%) in March. There were substantial falls in weighted regional prevalence: in South East from 0.36% (0.29%, 0.44%) in round 9 to 0.07% (0.04%, 0.12%) in round 10; London from 0.60% (0.48%, 0.76%) to 0.16% (0.10%, 0.26%); East of England from 0.47% (0.36%, 0.60%) to 0.15% (0.10%, 0.24%); East Midlands from 0.59% (0.45%, 0.77%) to 0.19% (0.13%, 0.28%); and North West from 0.69% (0.54%, 0.88%) to 0.31% (0.21%, 0.45%). Areas of apparent higher prevalence remain in parts of the North West, and Yorkshire and The Humber. The highest prevalence in March was found among school-aged children 5 to 12 years at 0.41% (0.27%, 0.62%), compared with the lowest in those aged 65 to 74 and 75 and over at 0.09% (0.05%, 0.16%). The close approximation between prevalence of infections and deaths (suitably lagged) is diverging, suggesting that infections may have resulted in fewer hospitalisations and deaths since the start of widespread vaccination. ConclusionWe report a sharp decline in prevalence of infections between February and March 2021. We did not observe an increase in the prevalence of SARS-CoV-2 following the reopening of schools in England, although the decline of prevalence appears to have stopped. Future rounds of REACT-1 will be able to measure the rate of growth or decline from this current plateau and hence help assess the effectiveness of the vaccination roll-out on transmission of the virus as well as the potential size of any third wave during the ensuing months.

REACT-1 round 9 final report: Continued but slowing decline of prevalence of SARS-CoV-2 during national lockdown in England in February 2021

BackgroundEngland will start to exit its third national lockdown in response to the COVID-19 pandemic on 8th March 2021, with safe effective vaccines being rolled out rapidly against a background of emerging transmissible and immunologically novel variants of SARS-CoV-2. A subsequent increase in community prevalence of infection could delay further relaxation of lockdown if vaccine uptake and efficacy are not sufficiently high to prevent increased pressure on healthcare services. MethodsThe PCR self-swab arm of the REal-time Assessment of Community Transmission Study (REACT-1) estimates community prevalence of SARS-CoV-2 infection in England based on random cross-sections of the population ages five and over. Here, we present results from the complete round 9 of REACT-1 comprising round 9a in which swabs were collected from 4th to 12th February 2021 and round 9b from 13th to 23rd February 2021. We also compare the results of REACT-1 round 9 to round 8, in which swabs were collected mainly from 6th January to 22nd January 2021. ResultsOut of 165,456 results for round 9 overall, 689 were positive. Overall weighted prevalence of infection in the community in England was 0.49% (0.44%, 0.55%), representing a fall of over two thirds from round 8. However the rate of decline of the epidemic has slowed from 15 (13, 17) days, estimated for the period from the end of round 8 to the start of round 9, to 31 days estimated using data from round 9 alone (lower confidence limit 17 days). When comparing round 9a to 9b there were apparent falls in four regions, no apparent change in one region and apparent rises in four regions, including London where there was a suggestion of sub-regional heterogeneity in growth and decline. Smoothed prevalence maps suggest large contiguous areas of growth and decline that do not align with administrative regions. Prevalence fell by 50% or more across all age groups in round 9 compared to round 8, with prevalence (round 9) ranging from 0.21% in those aged 65 and over to 0.71% in those aged 13 to 17 years. Round 9 prevalence was highest among Pakistani participants at 2.1% compared to white participants at 0.45% and Black participants at 0.83%. There were higher adjusted odds of infection for healthcare and care home workers, for those working in public transport and those working in education, school, nursery or childcare and lower adjusted odds for those not required to work outside the home. ConclusionsCommunity prevalence of swab-positivity has declined markedly between January and February 2021 during lockdown in England, but remains high; the rate of decline has slowed in the most recent period, with a suggestion of pockets of growth. Continued adherence to social distancing and public health measures is required so that infection rates fall to much lower levels. This will help to ensure that the benefits of the vaccination roll-out programme in England are fully realised.

REACT-1 round 9 interim report: downward trend of SARS-CoV-2 in England inFebruary 2021 but still at high prevalence

Background and MethodsEngland entered its third national lockdown of the COVID-19 pandemic on 6th January 2021 with the aim of reducing the daily number of deaths and pressure on healthcare services. The real-time assessment of community transmission study (REACT-1) obtains throat and nose swabs from randomly selected people in England in order to describe patterns of SARS-CoV-2 prevalence. Here, we report data from round 9a of REACT-1 for swabs collected between 4th and 13th February 2021. ResultsOut of 85,473 tested-swabs, 378 were positive. Overall weighted prevalence of infection in the community in England was 0.51%, a fall of more than two thirds since our last report (round 8) in January 2021 when 1.57% of people tested positive. We estimate a halving time of 14.6 days and a reproduction number R of 0.72, based on the difference in prevalence between the end of round 8 and the beginning of round 9. Although prevalence fell in all nine regions of England over the same period, there was greater uncertainty in the trend for North West, North East, and Yorkshire and The Humber. Prevalence fell substantially across all age groups with highest prevalence among 18- to 24-year olds at 0.89% (0.47%, 1.67%) and those aged 5 to12 years at 0.86% (0.60%, 1.24%). Large household size, living in a deprived neighbourhood, and Asian ethnicity were all associated with increased prevalence. Healthcare and care home workers were more likely to test positive compared to other workers. ConclusionsThere is a strong decline in prevalence of SARS-CoV-2 in England among the general population five to six weeks into lockdown, but prevalence remains high: at levels similar to those observed in late September 2020. Also, the number of COVID-19 cases in hospitals is higher than at the peak of the first wave in April 2020. The effects of easing of social distancing when we transition out of lockdown need to be closely monitored to avoid a resurgence in infections and renewed pressure on health services.

REACT-1 round 8 final report: high average prevalence with regional heterogeneity of trends in SARS-CoV-2 infection in the community in England during January 2021

In early January 2021, England entered its third national lockdown of the COVID-19 pandemic to reduce numbers of deaths and pressure on healthcare services, while rapidly rolling out vaccination to healthcare workers and those most at risk of severe disease and death. REACT-1 is a survey of SARS-CoV-2 prevalence in the community in England, based on repeated cross-sectional samples of the population. Between 6th and 22nd January 2021, out of 167,642 results, 2,282 were positive giving a weighted national prevalence of infection of 1.57% (95% CI, 1.49%, 1.66%). The R number nationally over this period was estimated at 0.98 (0.92, 1.04). Prevalence remained high throughout, but with suggestion of a decline at the end of the study period. The average national trend masked regional heterogeneity, with robustly decreasing prevalence in one region (South West) and increasing prevalence in another (East Midlands). Overall prevalence at regional level was highest in London at 2.83% (2.53%, 3.16%). Although prevalence nationally was highest in the low-risk 18 to 24 year old group at 2.44% (1.96%, 3.03%), it was also high in those over 65 years who are most at risk, at 0.93% (0.82%, 1.05%). Large household size, living in a deprived neighbourhood, and Black and Asian ethnicity were all associated with higher levels of infections compared to smaller households, less deprived neighbourhoods and other ethnicities. Healthcare and care home workers, and other key workers, were more likely to test positive compared to other workers. If sustained lower prevalence is not achieved rapidly in England, pressure on healthcare services and numbers of COVID-19 deaths will remain unacceptably high.