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.

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 frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Random genetic drift in the population-level dynamics of an infectious disease outbreak results from the randomness of inter-host transmission and the randomness of host recovery or death. The strength of genetic drift has been found to be high for SARS-CoV-2 due to superspreading, and this is expected to substantially impact the disease epidemiology and evolution. Noise that results from the measurement process, such as biases in data collection across time, geographical areas, etc., can potentially confound estimates of genetic drift as both processes contribute "noise" to the data. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude. Corrections taking into account epidemiological dynamics (susceptible-infected-recovered or susceptible-exposed-infected-recovered models) do not explain the discrepancy. Moreover, the levels of genetic drift that we observe are higher than the estimated levels of superspreading found by modeling studies that incorporate data on actual contact statistics in England. We discuss how even in the absence of superspreading, high levels of genetic drift can be generated via community structure in the host contact network. Our results suggest that further investigations of heterogeneous host contact structure may be important for understanding the high levels of genetic drift observed for SARS-CoV-2 in England.

Inconsistent directions of change in case severity across successive SARS-CoV-2 variant waves suggests an unpredictable future

ObjectiveTo determine how the severity of successively dominant SARS-CoV-2 variants changed over the course of the COVID-19 pandemic. DesignRetrospective cohort analysis. SettingCommunity- and hospital-sequenced COVID-19 cases in the NHS Greater Glasgow and Clyde (NHS GG&C) Health Board. ParticipantsAll sequenced non-nosocomial adult COVID-19 cases in NHS GG&C infected with the relevant SARS-CoV-2 lineages during analysis periods. B.1.177/Alpha: 1st November 2020 - 30th January 2021 (n = 1640). Alpha/Delta: 1st April - 30th June 2021 (n = 5552). AY.4.2 Delta/non-AY.4.2 Delta: 1st July - 31st October 2021 (n = 9613). Non-AY.4.2 Delta/Omicron: 1st - 31st December 2021 (n = 3858). Main outcome measuresAdmission to hospital, ICU, or death within 28 days of positive COVID-19 test ResultsFor B.1.177/Alpha, 300 of 807 B.1.177 cases were recorded as hospitalised or worse, compared to 232 of 833 Alpha cases. After adjustment, the cumulative odds ratio was 1.51 (95% CI: 1.08-2.11) for Alpha versus B.1.177. For Alpha/Delta, 113 of 2104 Alpha cases were recorded as hospitalised or worse, compared to 230 of 3448 Delta cases. After adjustment, the cumulative odds ratio was 2.09 (95% CI: 1.42-3.08) for Delta versus Alpha. For non-AY.4.2 Delta/AY.4.2 Delta, 845 of 8644 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 101 of 969 AY.4.2 Delta cases. After adjustment, the cumulative odds ratio was 0.99 (95% CI: 0.76-1.27) for AY.4.2 Delta versus non-AY.4.2 Delta. For non-AY.4.2 Delta/Omicron, 30 of 1164 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 26 of 2694 Omicron cases. After adjustment, the median cumulative odds ratio was 0.49 (95% CI: 0.22-1.06) for Omicron versus non-AY.4.2 Delta. ConclusionsThe direction of change in disease severity between successively emerging SARS-CoV-2 variants of concern was inconsistent. This heterogeneity demonstrates that severity associated with future SARS-CoV-2 variants is unpredictable.

Recurrent SARS-CoV-2 Mutations in Immunodeficient Patients

Long-term SARS-CoV-2 infections in immunodeficient patients are an important source of variation for the virus but are understudied. Many case studies have been published which describe one or a small number of long-term infected individuals but no study has combined these sequences into a cohesive dataset. This work aims to rectify this and study the genomics of this patient group through a combination of literature searches as well as identifying new case series directly from the COG-UK dataset. The spike gene receptor binding domain (RBD) and N-terminal domains (NTD) were identified as mutation hotspots. Numerous mutations associated with variants of concern were observed to emerge recurrently. Additionally a mutation in the envelope gene, - T30I was determined to be the most recurrent frequently occurring mutation arising in persistent infections. A high proportion of recurrent mutations in immunodeficient individuals are associated with ACE2 affinity, immune escape, or viral packaging optimisation. There is an apparent selective pressure for mutations which aid intra-host transmission or persistence which are often different to mutations which aid inter-host transmission, although the fact that multiple recurrent de novo mutations are considered defining for variants of concern strongly indicates that this potential source of novel variants should not be discounted.

The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK

The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.

City-wide wastewater genomic surveillance through the successive emergence of SARS-CoV-2 Alpha and Delta variants

Genomic surveillance of SARS-CoV-2 has been essential to provide an evidence base for public health decisions throughout the SARS-CoV-2 pandemic. Sequencing data from clinical cases has provided data crucial to understanding disease transmission and the detection, surveillance, and containment of outbreaks of novel variants, which continue to pose fresh challenges. However, genomic wastewater surveillance can provide important complementary information by providing estimates of variant frequencies which do not suffer from sampling bias, and capturing all variants circulating in a population. Here we show that genomic SARS-CoV-2 wastewater surveillance can detect fine-scale differences within urban centres, specifically within the city of Liverpool, UK, during the emergence of Alpha and Delta variants between November 2020 and June 2021. Overall, the correspondence between wastewater and clinical variant frequencies demonstrates the reliability of wastewater surveillance. Yet, discrepancies between the two approaches when the Alpha variant was first detected emphasises that wastewater monitoring can also capture missing information resulting from asymptomatic cases or communities less engaged with testing programmes, as found by a simultaneous surge testing effort across the city.

Spatio-temporal epidemiology of SARS-CoV-2 virus lineages in Teesside, UK, in 2020: effects of social deprivation, weather and lockdown on lineage dynamics

SARS-CoV-2 emerged in the UK in January 2020 and the Government introduced national lockdowns and regional tiers to control virus transmission. As the outbreak continued, new variants were detected. We analysed spatio-temporal dynamics of positive tests for COVID-19 on Teesside, UK throughout 2020, in relation to: socio-economic deprivation, weather, and Government interventions. We used a combination of disease mapping and mixed-effect modelling to investigate the dynamics of positive tests from two sampling strategies and the spread of particular variants of the virus as they emerged on Teesside. SARS-CoV-2 spread was related to the extent of social deprivation, lockdown interventions and weather. SARS-CoV-2 spread faster in some lineages than others, with positive tests related to levels of socio-economic deprivation. The interventions appeared to have different effects in the two waves of disease, and were associated with reduced numbers of records in the first wave, but having no effect during the second. ARTICLE SUMMARY LINERegional spread of SARS-CoV-2 is dependent on weather, socio-economic and mandatory lockdowns, but the effectiveness of the latter varies with virus lineage.

Spatial Growth Rate of Emerging SARS-CoV-2 Lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020-December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81x faster than the Delta (B.1.617.2 and AY) variant and 3.76x faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to routine assessments of the growth of emerging SARS-CoV-2 lineages in a defined population.

Severe outcomes in residents of Long Term Care Facilities following infection with SARS-CoV-2 Omicron variant (VIVALDI study)

BackgroundRecently there has been a rapid, global increase in SARS-CoV-2 infections associated with the Omicron variant (B.1.1.529). Although severity of Omicron cases may be reduced, the scale of infection suggests hospital admissions and deaths may be substantial. Definitive conclusions about disease severity require evidence from populations with the greatest risk of severe outcomes, such as residents of Long-Term Care Facilities (LTCFs). MethodsWe used a cohort study to compare the risk of hospital admission or death in LTCF residents in England who had tested positive for SARS-CoV-2 in the period shortly before Omicron emerged (Delta dominant) and the Omicron-dominant period, adjusting for age, sex, vaccine type, and booster vaccination. Variants were confirmed by sequencing or spike-gene status in a subset. ResultsRisk of hospital admission was markedly lower in 1241 residents infected in the Omicron-period (4.01% hospitalised, 95% CI: 2.87-5.59) compared to 398 residents infected in the pre-Omicron period (10.8% hospitalised, 95% CI: 8.13-14.29, adjusted Hazard Ratio 0.50, 95% CI: 0.29-0.87, p=0.014); findings were similar in residents with confirmed variant. No residents with previous infection were hospitalised in either period. Mortality was lower in the Omicron versus the pre-Omicron period, (p<0.0001). ConclusionsRisk of severe outcomes in LTCF residents with the SARS-CoV-2 Omicron variant was substantially lower than that seen for previous variants. This suggests the current wave of Omicron infections is unlikely to lead to a major surge in severe disease in LTCF populations with high levels of vaccine coverage and/or natural immunity. Trial Registration NumberISRCTN 14447421

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

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.

The hyper-transmissible SARS-CoV-2 Omicron variant exhibits significant antigenic change, vaccine escape and a switch in cell entry mechanism

Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron, the fifth VOC to be described, harbours 30 amino acid mutations in spike including 15 in the receptor-binding domain. Here, we demonstrate substantial evasion of neutralisation by Omicron in vitro using sera from vaccinated individuals. Importantly, these data are mirrored by a substantial reduction in real-world vaccine effectiveness that is partially restored by booster vaccination. We also demonstrate that Omicron does not induce cell syncytia and favours a TMPRSS2-independent endosomal entry pathway. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant.

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

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.

Context-specific emergence and growth of the SARS-CoV-2 Delta variant

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases1-3. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions4,5. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Deltas nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Deltas invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

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

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 found to be slowing down during the study period, with AY.4.2 further found to have a reduced mutation rate relative to AY.4. As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

Genomics-informed outbreak investigations of SARS-CoV-2 using civet

The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 5 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different catchments and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.

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

BackgroundThe Delta (B.1.617.2) variant became the predominant UK circulating SARS-CoV-2 strain in May 2021. How Delta infection compares with previous variants is unknown. MethodsThis prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. Findings3,581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta vs. Alpha infection (including fever, sore throat and headache) and vice versa (dyspnoea). Symptom burden in the first week was higher with Delta vs. Alpha infection; however, the odds of any given symptom lasting [≥]7 days was either lower or unchanged. Illness duration [≥]28 days was lower with Delta vs. Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1{middle dot}47) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly (69-84%) reduced risk of Delta infection. InterpretationCOVID-19 from Delta or Alpha infections is clinically similar. The Delta variant is more transmissible than Alpha; however, current vaccines show good efficacy against disease. FundingUK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, Alzheimers Society, and ZOE Limited. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for differences (including illness, transmissibility, and vaccine effectiveness) from SARS-CoV-2 infection due to Alpha (B.1.1.7) and Delta (B.1.617.2) variants, we searched PubMed for peer-reviewed articles and medRxiv for preprint publications between March 1 and November 18, 2021 using keywords ("SARS-CoV-2" OR "COVID-19") AND ("delta variant" OR "B.1.617.2") AND (symptom* OR transmiss* OR "disease duration" OR "illness duration" OR "symptom* duration"). Searches were not restricted by language. Among 169 identified PubMed articles, we found evidence that Delta variant has increased replication capacity (from 4-fold, up to 21-fold, compared with wild-type) and greater transmissibility (estimated between +20% and +97%), compared with previous strains. Currently available vaccines may have 2- to 5-fold lower neutralizing response to Delta vs. previous variants, depending on vaccine formulation, although their protective effect against severe disease and death appears to remain strong. REACT-1 study found that in UK infections were increasing exponentially in the 5-17-year old children in September 2021, coinciding with the start of the autumn school term in England. This was interpreted as an effect of the relatively low rate of vaccinated individuals in this age group. Other studies found that in unvaccinated individuals, Delta variant may be associated with higher odds of pneumonia, oxygen requirement, emergency care requests, ICU admission, and death. In a study of 27 (mainly young) cases, 22 persons were symptomatic, with fever (41%), cough (33%), headache (26%), and sore throat (26%) the commonest symptoms. We found no studies, beyond case series, investigating symptom and/or illness duration due to Delta variant infection otherwise. Added value of this studyUsing data from one of the largest UK citizen science epidemiological initiatives, we describe and compare illness (symptom duration, burden, profile, risk of long illness, and hospital attendance) in symptomatic community-based adults presenting when either the Alpha or Delta variant was the predominant circulating strain of SARS-CoV-2 in the UK. We assess evidence of transmission, reinfection, and vaccine effectiveness. Our data show that the seven most common symptoms with Delta infection were the same as with Alpha infection. Risks of illness duration [≥]7 days and [≥]28 days, and of requiring hospital care, were not increased. In line with previous research, we found increased transmissibility of Delta vs. previous variants; and no evidence of increased re-infection rates. Our data support high vaccine efficacy of BNT162b2 and ChAdOx1 nCoV-19 formulations against Delta variant infection. Overall, our study adds quantitative information regarding meaningful clinical differences in COVID-19 due to Delta vs. other variants. Implications of all the available evidenceOur observational data confirm that COVID-19 disease in UK in adults is generally comparable to infection with the Alpha variant, including in elderly individuals. Our data contribute to epidemiological surveillance from the wider UK population and may capture information from COVID-19 presentation within the community that might be missed in healthcare-based surveillance. Our data may be useful in informing healthcare service planning, vaccination policies, and measures for social protection.

SARS-CoV-2 testing in the community: Testing positive samples with the TaqMan SARS-CoV-2 Mutation Panel to find variants in real-time

Genome sequencing is a powerful tool for identifying SARS-CoV-2 variant lineages, however there can be limitations due to sequence drop-out when used to identify specific key mutations. Recently, Thermo Fisher Scientific have developed genotyping assays to help bridge the gap between testing capacity and sequencing capability to generate real-time genotyping results based on specific variants. Over a 6-week period during the months of April and May 2021, we set out to assess the Thermo Fisher TaqMan Mutation Panel Genotyping Assay, initially for three mutations of concern and then an additional two mutations of concern, against SARS-CoV-2 positive clinical samples and the corresponding COG-UK sequencing data. We demonstrate that genotyping is a powerful in-depth technique for identifying specific mutations, an excellent complement to genome sequencing and has real clinical health value potential allowing laboratories to report and action variants of concern much quicker.

Defining the analytical and clinical sensitivity of the ARTIC method for the detection of SARS-CoV-2

The SARS-CoV-2 ARTIC amplicon protocol is the most widely used genome sequencing method for SARS-CoV-2, accounting for over 43% of publicly-available genome sequences. The protocol utilises 98 primers to amplify [~]400bp fragments of the SARS-CoV-2 genome covering all 30,000 bases. Understanding the analytical performance metrics of this protocol will improve how the data is used and interpreted. Different concentrations of SARS-CoV-2 control material were used to establish the limit of detection (LoD) of the ARTIC protocol. Results demonstrated the LoD was a minimum of 25-50 virus particles per mL. The sensitivity of ARTIC was comparable to the published sensitivities of commercial diagnostics assays and could therefore be used to confirm diagnostic testing results. A set of over 3,600 clinical samples from three UK regions were then evaluated to compare the protocols performance to clinical diagnostic assays (Roche Lightcycler 480 II, AusDiagnostics, Roche Cobas, Hologic Panther, Corman RdRp, Roche Flow, ABI QuantStudio 5, Seegene Nimbus, Qiagen Rotorgene, Abbott M2000, Thermo TaqPath, Xpert). We developed a Python tool, RonaLDO, to perform this validation (available under the GNU GPL3 open-source licence from https://github.com/quadram-institute-bioscience/ronaldo). Positives detected by diagnostic platforms were generally supported by sequencing data; platforms that used RT-qPCR were the best predictors of whether the sample would subsequently sequence successfully. To maximise success of sample sequencing for phylogenetic analysis, samples with Ct <31 should be chosen. For diagnostic tests that do not provide a quantifiable Ct value, adding a quantification step is recommended. The ARTIC SARS-CoV-2 sequencing protocol is highly sensitive, capable of detecting SARS-CoV-2 in samples with Cts in the high 30s. However, to routinely obtain whole genome coverage, samples with Ct <31 are recommended. Comparing different virus detection methods close to their LoD was challenging and significant discordance was observed.

Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021

BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain. MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England. ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity. DiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.

The SARS-CoV-2 Alpha variant is associated with increased clinical severity of disease

ObjectivesThe SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. MethodsIn this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. ResultsOur cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus non-Alpha variant). ConclusionsThe Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.