High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study (preprint)

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may act as viral reservoirs that could seed future outbreaks 1-5, give rise to highly divergent lineages 6-8, and contribute to cases with post-acute Coronavirus disease 2019 (COVID-19) sequelae (Long Covid) 9,10. However, the population prevalence of persistent infections, their viral load kinetics, and evolutionary dynamics over the course of infections remain largely unknown. We identified 381 infections lasting at least 30 days, of which 54 lasted at least 60 days. These persistently infected individuals had more than 50% higher odds of self-reporting Long Covid compared to the infected controls, and we estimate that 0.09-0.5% of SARS-CoV-2 infections can become persistent and last for at least 60 days. In nearly 70% of the persistent infections we identified, there were long periods during which there were no consensus changes in virus sequences, consistent with prolonged presence of non-replicating virus. Our findings also suggest reinfections with the same major lineage are rare and that many persistent infections are characterised by relapsing viral load dynamics. Furthermore, we found a strong signal for positive selection during persistent infections, with multiple amino acid substitutions in the Spike and ORF1ab genes emerging independently in different individuals, including mutations that are lineage-defining for SARS-CoV-2 variants, at target sites for several monoclonal antibodies, and commonly found in immunocompromised patients 11-14. This work has significant implications for understanding and characterising SARS-CoV-2 infection, epidemiology, and evolution.

Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1 (preprint)

SARS-CoV-2 variants of concern (VOCs) arise against the backdrop of increasingly heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron genomes, we identified >6,000 independent introductions of the antigenically distinct virus into England and reconstructed the dispersal history of resulting local transmission. Travel restrictions on southern Africa did not reduce BA.1 importation intensity as secondary hubs became major exporters. We explored potential drivers of BA.1 spread across England and discovered an early period during which viral lineage movements mainly occurred between larger cities, followed by a multi-focal spatial expansion shaped by shorter distance mobility patterns. We also found evidence that disease incidence impacted human commuting behaviours around major travel hubs. Our results offer a detailed characterisation of processes that drive the invasion of an emerging VOC across multiple spatial scales and provide unique insights on the interplay between disease spread and human mobility.

Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias. (preprint)

In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burdens, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. Analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior infection, the average Ct value was 0.94 lower among Alpha variant infections, compared those with the predecessor strain, B.1.177. However, among vaccinated individuals, it was 0.34 lower among Delta variant infections, compared to those with the Alpha variant. In addition, the average Ct value decreased by 0.20 for every 10 year age increment of the infected individual. In summary, within-host viral burdens are associated with age, in addition to the interplay of vaccination status and viral variant.

Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey (preprint)

The Office for National Statistics COVID-19 Infection Survey is a large household-based surveillance study based in the United Kingdom. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing sequenced samples collected up until 13th November 2021. We observed four distinct sweeps or partial-sweeps, by lineages B.1.177, B.1.1.7/Alpha, B.1.617.2/Delta, and finally AY.4.2, a sublineage of B.1.617.2, with each sweeping lineage having a distinct growth advantage compared to their predecessors. Evolution was characterised by steady rates of evolution and increasing diversity within lineages, but with step increases in divergence associated with each sweeping major lineage, leading to a faster overall rate of evolution and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly as routine PCR testing is phased out or in settings where large-scale sequencing is not feasible.

Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions (preprint)

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and calibration of an stochastic agent-based model Covasim to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. We used these estimates in Covasim (calibrated between September 01, 2020 and June 20, 2021), in June 2021, to explore whether planned relaxation of restrictions should proceed or be delayed. We found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination.

EpiBeds: Data informed modelling of the COVID-19 hospital burden in England (preprint)

The first year of the COVID-19 pandemic put considerable strain on the national healthcare system in England. In order to predict the effect of the local epidemic on hospital capacity in England, we used a variety of data streams to inform the construction and parameterisation of a hospital progression model, which was coupled to a model of the generalised epidemic. We named this model EpiBeds. Data from a partially complete patient-pathway line-list was used to provide initial estimates of the mean duration that individuals spend in the different hospital compartments. We then fitted EpiBeds using complete data on hospital occupancy and hospital deaths, enabling estimation of the proportion of individuals that follow different clinical pathways, and the reproduction number of the generalised epidemic. The construction of EpiBeds makes it straightforward to adapt to different patient pathways and settings beyond England. As part of the UK response to the pandemic, EpiBeds has provided weekly forecasts to the NHS for hospital bed occupancy and admissions in England, Wales, Scotland, and Northern Ireland.

Modelling the effectiveness and social costs of daily lateral flow antigen tests versus quarantine in preventing onward transmission of COVID-19 from traced contacts (preprint)

Quarantining close contacts of individuals infected with SARS-CoV-2 for 10 to 14 days is a key strategy in reducing transmission. However, quarantine requirements are often unpopular, with low adherence, especially when a large fraction of the population has been vaccinated. Daily contact testing (DCT), in which contacts are required to isolate only if they test positive, is an alternative to quarantine for mitigating the risk of transmission from traced contacts. In this study, we developed an integrated model of COVID-19 transmission dynamics and compared the strategies of quarantine and DCT with regard to reduction in transmission and social/economic costs (days of quarantine/self-isolation). Specifically, we compared 10-day quarantine to 7 days of self-testing using rapid lateral flow antigen tests, starting 3 days after exposure to a case. We modelled both incomplete adherence to quarantine and incomplete adherence to DCT. We found that DCT reduces transmission from contacts with similar effectiveness, at much lower social/economic costs, especially for highly vaccinated populations. The findings were robust across a spectrum of scenarios with varying assumptions on the speed of contact tracing, sensitivity of lateral flow antigen tests, adherence to quarantine and uptake of testing. Daily tests would also allow rapid initiation of a new round of tracing from infected contacts.

Efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine against SARS-CoV-2 lineages circulating in Brazil; an exploratory analysis of a randomised controlled trial (preprint)

Background Emerging evidence shows the substantial real-world impact of authorised vaccines against COVID-19 and provides insight into the potential role of vaccines in curbing the pandemic. However, there remains uncertainty about the efficacy of vaccines against different variants of the virus. Here we assessed efficacy of ChAdOx1 nCoV-19 (AZD1222) against lineages of SARS-CoV-2 circulating in Brazil from June 2020 until early 2021. Methods Participants aged 18 and above were enrolled into a randomised phase 3 trial of ChAdOx1 nCoV-19 vaccine against symptomatic SARS-CoV-2 infection. Participants received two doses of ChAdOx1 nCoV-19 or control (1st dose: Men ACWY vaccine, 2nd dose: normal saline). Nasopharyngeal and oropharyngeal swabbing was performed if participants developed symptoms of COVID-19 (cough, shortness of breath, fever >37.8°C, ageusia, anosmia). Swabs were tested by nucleic acid amplification (NAAT) for SARS-CoV-2, sequenced, and viral load determined. For those samples where a genotype could not be ascertained from sequencing, allele specific PCR was performed. The efficacy analysis included symptomatic COVID-19 in seronegative participants with a NAAT positive swab more than 14 days after a second dose of vaccine. Participants were unblinded after the vaccine was authorised for use, and the control participants offered vaccination. Infections occurring after unblinding were excluded from analysis. Vaccine efficacy was calculated as 100% x (1 – relative risk (RR)), where RR was estimated from a robust Poisson model. The trial is registered at ISRCTN89951424. Findings 9433 participants were eligible for inclusion in the pre-specified primary efficacy population, having reached more than 14 days after a second dose of ChAdOx1 nCoV-19, of whom 307 were NAAT+, in this post-hoc analysis. From June 2020 to February 2021, the two most frequently identified lineages were P.2 (N=153) and B.1.1.28 (N=49). P.1 emerged during the study (N=18) but became dominant only after study unblinding. Viral loads were highest amongst those with P.1 infection. Vaccine efficacy (VE) for B.1.1.33 (88.2%, 95%CI 5, 99), B.1.1.28 (73%, 95% CI, 46, 86), P.2 (69% 95% CI, 55, 78) and P.1 (64%, 95% CI, -2, 87) was estimated. In participants who had received two doses of vaccine, one COVID-19 hospitalisation occurred in the ChAdOx1 nCoV-19 group and 18 in the control group, with VE against hospitalisation 95% (95% CI 61, 99). There were 2 COVID-19 deaths in the control group and none in the vaccine group. Interpretation ChAdOx1 nCoV-19 provides high efficacy against hospitalisation, severe disease and death from COVID-19 in Brazil and there is strong evidence of protection being maintained against P.2, despite the presence of the spike protein mutation E484K. Real world effectiveness studies are ongoing in Brazil to further establish protection against P.1 and other emerging variants.

Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings (preprint)

Background Non-pharmaceutical intervention (NPI) remains the most reliable COVID-19 containment tool for low- and middle-income countries (LMICs) given the inequality of vaccine distribution and their vulnerable healthcare systems. We aimed to develop mathematical models that capture LMIC demographic characteristics such as young population and large household size and assess NPI effectiveness in rural and urban communities. Methods We constructed synthetic populations for rural, non-slum urban and slum settings to capture LMIC demographic characteristics that vary across communities. We integrated age mixing and household structure into contact networks for each community setting and simulated COVID-19 outbreaks within the networks. Using this agent-based model, we evaluate NPIs including testing and isolation, tracing and quarantine, and physical distancing. We explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic test, symptom screening, contact tracing and physical distancing. We performed extensive simulations to capture the uncertainty of outbreak trajectories and the impact of varying model parameters. Findings We found the impact of testing, tracing and distancing varies with rural-urban settings. In rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. Additionally, antibody rapid diagnostic tests and symptom-based diagnosis could be useful for mitigating the transmission. In non-slum urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In slum communities, we found physical distancing is less effective compared to rural and non-slum urban communities. Lastly, for all communities considered, we demonstrated contact quarantine is essential for effective containment and is effective at a low compliance rate (30%). Interpretation Our findings could guide setting-specific strategy design for different communities in LMICs. Our assessments also have implications on applying rapid diagnostic tests and symptom-based diagnosis for case finding, tracing and distancing in lower-income communities.

Epidemiological and public health requirements for COVID-19 contact tracing apps and their evaluation (preprint)

Digital contact tracing is a public health intervention. It should be integrated with local health policy, provide rapid and accurate notifications to exposed individuals, and encourage high app uptake and adherence to quarantine. Real-time monitoring and evaluation of effectiveness of app-based contact tracing is key for improvement and public trust.

Early Analysis of a potential link between viral load and the N501Y mutation in the SARS-COV-2 spike protein (preprint)

A new variant of SARS-CoV-2 has emerged which is increasing in frequency, primarily in the South East of England (lineage B.1.1.7 (1); VUI-202012/01). One potential hypothesis is that infection with the new variant results in higher viral loads, which in turn may make the virus more transmissible. We found higher (sequence derived) viral loads in samples from individuals infected with the new variant with median inferred viral loads were three-fold higher in individuals with the new variant. Most of the new variants were sampled in Kent and Greater London. We observed higher viral loads in Kent compared to Greater London for both the new variant and other circulating lineages. Outside Greater London, the variant has higher viral loads, whereas within Greater London, the new variant does not have significantly higher viral loads compared to other circulating lineages. Higher variant viral loads outside Greater London could be due to demographic effects, such as a faster variant growth rate compared to other lineages or concentration in particular age-groups. However, our analysis does not exclude a causal link between infection with the new variant and higher viral loads. This is a preliminary analysis and further work is needed to investigate any potential causal link between infection with this new variant and higher viral loads, and whether this results in higher transmissibility, severity of infection, or affects relative rates of symptomatic and asymptomatic infection Document Description and PurposeThis is an updated report submitted to NERVTAG in December 2020 as part of urgent investigations into the new variant of SARS-COV-2 (VUI-202012/01). It makes full use of (and is restricted to) all sequence data and associated metadata available to us at the time this original report was submitted and remains provisional. Under normal circumstances more genomes and metadata would be obtained and included before making this report public. We will update this preprint when more genomes and metadata are available and before submitting for peer review.

The Timing of COVID-19 Transmission (preprint)

Background: The timing of SARS-CoV-2 transmission is a critical factor to understand the epidemic trajectory and the impact of isolation, contact tracing and other non-pharmaceutical interventions on the spread of COVID-19 epidemics. Methods: We examined the distribution of transmission event times with respect to exposure and onset of symptoms. We analysed 119 transmission pairs with known date of onset of symptoms for both index and secondary cases and partial information on their intervals of exposure. We inferred the distribution for generation time and time from onset of symptoms to transmission by maximum likelihood. We modelled different relations between time of infection, onset of symptoms and transmission, inferring the most appropriate one according to the Akaike Information Criterion. Finally, we estimated the fraction of pre-symptomatic and early symptomatic transmissions among all pairs using a Bayesian approach.Findings: For symptomatic individuals, the timing of transmission of SARS-CoV-2 was more directly linked to the onset of clinical symptoms of COVID-19 than to the time since infection. The time of transmission was approximately centered and symmetric around the onset of symptoms, with three quarters of events occurring in the window from 2-3 days before to 2-3 days after. The pre-symptomatic infectious period extended further back in time for individuals with longer incubation periods. Overall, the fraction of transmission from strictly pre-symptomatic infections was high (41%; 95%CI 31-50%), but a comparably large fraction of transmissions occurred on the same day as the onset of symptoms or the next day (35%; 95%CI 26-45%). We caution against overinterpretation of the fraction and timing of late symptomatic transmissions, due to their dependence on behavioural factors and interventions. Interpretation: Infectiousness is causally driven by the onset of symptoms. Public health authorities should reassess their policies on the contact tracing window in the light of individual variability in presymptomatic infectious period. Information about when a case was infected should be collected where possible, in order to assess how far into the past their contacts should be traced. The large fraction of transmission from strictly pre-symptomatic infections limits the efficacy of symptom-based interventions, while the large fraction of early symptomatic transmissions underlines the critical importance of individuals distancing themselves from others as soon as they notice any symptoms, even if mild. Rapid or at-home testing and contextual risk information could greatly facilitate efficient early isolation.Funding Statement: The study was funded by an award from the Li Ka Shing Foundation to CF.Declaration of Interests: None of the authors have competing financial or non-financial interests.

OpenABM-Covid19 - an agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing (preprint)

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing. It can simulate a population of 1 million people in seconds per day allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 is its Python interface, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.

The timing of COVID-19 transmission (preprint)

The timing of SARS-CoV-2 transmission is a critical factor to understand the epidemic trajectory and the impact of isolation, contact tracing and other non- pharmaceutical interventions on the spread of COVID-19 epidemics. We examined the distribution of transmission events with respect to exposure and onset of symptoms. We show that for symptomatic individuals, the timing of transmission of SARS-CoV-2 is more strongly linked to the onset of clinical symptoms of COVID-19 than to the time since infection. We found that it was approximately centered and symmetric around the onset of symptoms, with three quarters of events occurring in the window from 2-3 days before to 2-3 days after. However, we caution against overinterpretation of the right tail of the distribution, due to its dependence on behavioural factors and interventions. We also found that the pre-symptomatic infectious period extended further back in time for individuals with longer incubation periods. This strongly suggests that information about when a case was infected should be collected where possible, in order to assess how far into the past their contacts should be traced. Overall, the fraction of transmission from strictly pre-symptomatic infections was high (41%; 95%CI 31-50%), which limits the efficacy of symptom-based interventions, and the large fraction of transmissions (35%; 95%CI 26-45%) that occur on the same day or the day after onset of symptoms underlines the critical importance of individuals distancing themselves from others as soon as they notice any symptoms, even if they are mild. Rapid or at-home testing and contextual risk information would greatly facilitate efficient early isolation.

Mutational Analysis of SARS-CoV-2 Genome in African Population (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a highly infectious and pathogenic virus has claimed lot of lives globally since its outbreak in December 2019 posing dire threat on public health, global economy, social and human interaction. At moderate rate, mutations in the SARS-CoV-2 genome are evolving which might have contributed to viral genome variability, transmission, replication efficiency and virulence in different regions of the world. The present study elucidated the mutational landscape in SARS-CoV-2 genome among the African population, which may have contributed to the virulence, pathogenicity and transmission observed in the region. Multiple sequence alignment of the SARS-CoV-2 genome (356 viral protein sequences) was performed using ClustalX version 2.1 and phylogenetic tree was built using Molecular Evolutionary Genetics Analysis (MEGA) X software. ORF1ab polyprotein, spike glycoprotein, ORF3, ORF8 and nucleocapsid phosphoprotein were observed as mutational hotspots in the African population and may be of keen interest in the adaptability of SARS-CoV-2 to the human host. While, there is conservation in the envelope protein, membrane glycoprotein, ORF6, ORF7a, ORF7b and ORF10. The accumulation of moderate mutations (though slowly) in the SARS-CoV-2 genome as revealed in our study, could be a promising strategy to develop drugs or vaccines with respect to the viral conserved domains and host cellular proteins and/or receptors involved in viral invasion and replication to avoid a new viral wave due to drug resistance and vaccine evasion.

The SARS-CoV-2 multibasic cleavage site facilitates early serine protease-mediated entry into organoid-derived human airway cells (preprint)

After the SARS-CoV outbreak in 2003, a second zoonotic coronavirus named SARS-CoV-2, emerged late 2019 in China and rapidly caused the COVID-19 pandemic leading to a public health crisis of an unprecedented scale. Despite the fact that SARS-CoV-2 uses the same receptor as SARS-CoV, transmission and pathogenesis of both viruses seem to be quite distinct. A remarkable feature of the SARS-CoV-2 spike is the presence of a multibasic cleavage site, which is absent in the SARS-CoV spike. The viral spike protein not only attaches to the entry receptor, but also mediates fusion after cleavage by host proteases. Here, we report that the SARS-CoV-2 spike multibasic cleavage site increases infectivity on differentiated organoid-derived human airway cells. Compared with SARS-CoV, SARS-CoV-2 entered faster into the lung cell line Calu-3, and more frequently formed syncytial cells in differentiated organoid-derived human airway cells. Moreover, the multibasic cleavage site increased entry speed and plasma membrane serine protease usage relative to endosomal entry using cathepsins. Blocking serine protease activity using the clinically approved drug camostat mesylate effectively inhibited SARS-CoV-2 entry and replication in differentiated organoid-derived human airway cells. Our findings provide novel information on how SARS-CoV-2 enters relevant airway cells and highlight serine proteases as an attractive antiviral target.

Modeling the combined effect of digital exposure notification and non-pharmaceutical interventions on the COVID-19 epidemic in Washington state (preprint)

Contact tracing is increasingly being used to combat COVID-19, and digital implementations are now being deployed, many of them based on Apple and Google's Exposure Notification System. These systems are new and are based on smartphone technology that has not traditionally been used for this purpose, presenting challenges in understanding possible outcomes. In this work, we use individual-based computational models to explore how digital exposure notifications can be used in conjunction with non-pharmaceutical interventions, such as traditional contact tracing and social distancing, to influence COVID-19 disease spread in a population. Specifically, we use a representative model of the household and occupational structure of three counties in the state of Washington together with a proposed digital exposure notifications deployment to quantify impacts under a range of scenarios of adoption, compliance, and mobility. In a model in which 15% of the population participated, we found that digital exposure notification systems could reduce infections and deaths by approximately 8% and 6%, effectively complementing traditional contact tracing. We believe this can serve as guidance to health authorities in Washington state and beyond on how exposure notification systems can complement traditional public health interventions to suppress the spread of COVID-19.

ISARIC COVID-19 Clinical Data Report: 8 June 2020 (preprint)

ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global uptake of this resource has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report is a part of a series and includes the results of data analysis on 8 June 2020. We thank all of the data contributors for their ongoing support. As of 8JUN20, data have been entered for 67,130 patients from 488 sites across 37 countries. For this report, we show data for 42,656 patients with confirmed disease who were enrolled >14 days prior. This update includes about 2,400 new cases from France, and we thank these collaborators for this significant addition to the dataset. Some highlights from this report The median time from onset of symptoms to hospital admission is 5 days, but a proportion of patients take longer to get to the hospital (average 14.6 days, standard deviation 8.1). COVID-19 patients tend to require prolonged hospitalisation; of the 88% with a known outcome, the median length of admission to death or discharge is 8 days and the mean 11.5. 17% of patients were admitted to ICU/HDU, about 40% of these on the very day of hospital admission. Antibiotics were given to 83% of patients, antivirals to 9%, steroids to 15%, which becomes 93%, 50% and 27%, respectively for those admitted to ICU/HDU. Attention has been called on overuse of antibiotics and need to adhere to antibiotic stewardship principles. 67% of patients received some degree of oxygen supplementation: of these 23.4% received NIV and 15% IMV. This relatively high proportion of oxygen use will have implications for oxygen surge planning in healthcare facilities. Some centres may need to plan to boost capacity to deliver oxygen therapy if this is not readily available. WHO provides operational advice on surge strategy here https://apps.who.int/iris/bitstream/handle/10665/331746/WHO-2019-nCoV-Oxygen_sources-2020.1-eng.pdf

COVID-19 incidence and R decreased on the Isle of Wight after the launch of the Test, Trace, Isolate programme (preprint)

In May 2020 the UK introduced a Test, Trace, Isolate programme in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included Version 1 of the NHS contact tracing app. We used COVID-19 daily case data to infer incidence of new infections and estimate the reproduction number R for each of 150 Upper Tier Local Authorities in England, and at the National level, before and after the launch of the programme on the Isle of Wight. We used Bayesian and Maximum-Likelihood methods to estimate R, and compared the Isle of Wight to other areas using a synthetic control method. We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch. These results are robust across each of our approaches. Our results show that the sub-epidemic on the Isle of Wight was controlled significantly more effectively than the sub-epidemics of most other Upper Tier Local Authorities, changing from having the third highest reproduction number R (of 150) before the intervention to the tenth lowest afterwards. The data is not yet available to establish a causal link. However, the findings highlight the need for further research to determine the causes of this reduction, as these might translate into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination becomes available.

SARS-CoV-2 genomics beyond the consensus sequence: evidence for circulating mixed viral populations (preprint)

We gratefully acknowledge the UK COVID-19 Genomics Consortium (COG UK) for funding, and Public Health Wales / Cardiff University and MRC-University of Glasgow Centre for Virus Research for making their COG-UK sequence data publicly available. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. The research was supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z with funding from the NIHR Oxford BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We are deeply grateful to Robert Esnouf and the BMRC Research Computing team for unfailing assistance with computational infrastructure. We also thank Benjamin Carpenter and James Docker for assistance in the laboratory, and Lorne Lonie, Maria Lopopolo, Chris Allen, John Broxholme and the WHG high-throughput genomics team for sequencing and quality control. The HIV clone p92BR025.8 was obtained through the Centre For AIDS Reagents from Drs Beatrice Hahn and Feng Gao, and the UNAIDS Virus Network (courtesy of the NIH AIDS Research and Reference Reagent Program). KAL is supported by The Wellcome Trust and The Royal Society (107652/Z/15/Z). MH, LF, MdC, GMC, NO, LAD, DB, CF and TG are supported by Li Ka Shing Foundation funding awarded to CF. PS is supported by a Wellcome Investigator Award (WT103767MA). SummarySARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 causing a global pandemic, with the United Kingdom (UK) one of the hardest hit countries. Rapid sequencing and publication of consensus genomes have enabled phylogenetic analysis of the virus, demonstrating SARS-CoV-2 evolves relatively slowly1, but with multiple sites in the genome that appear inconsistent with the overall consensus phylogeny2. To understand these discrepancies, we used veSEQ3, a targeted RNA-seq approach, to quantify minor allele frequencies in 413 clinical samples from two UK locations. We show that SARS-CoV-2 infections are characterised by extensive within-host diversity, which is frequently shared among infected individuals with patterns consistent with geographical structure. These results were reproducible in data from two other sequencing locations in the UK, where we find evidence of mixed infection by major circulating lineages with patterns that cannot readily be explained by artefacts in the data. We conclude that SARS-CoV-2 diversity is transmissible, and propose that geographic patterns are generated by transient co-circulation of distinct viral populations. Co-transmission of mixed populations could open opportunities for resolving clusters of transmission and understanding pathogenesis.