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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.
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We report the first local transmission of the SARS-CoV-2 Delta variant in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of the quarantined subjects indicated that the viral loads of Delta infections, when they first become PCR+, were on average [~]1000 times greater compared to A/B lineage infections during initial epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. We performed high-quality sequencing on samples from 126 individuals. Reliable epidemiological data meant that, for 111 transmission events, the donor and recipient cases were known. The estimated transmission bottleneck size was 1-3 virions with most minor intra-host single nucleotide variants (iSNVs) failing to transmit to the recipients. However, transmission heterogeneity of SARS-CoV-2 was also observed. The transmission of minor iSNVs resulted in at least 4 of the 30 substitutions identified in the outbreak, highlighting the contribution of intra-host variants to population level viral diversity during rapid spread. Disease control activities, such as the frequency of population testing, quarantine during pre-symptomatic infection, and level of virus genomic surveillance should be adjusted in order to account for the increasing prevalence of the Delta variant worldwide.
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Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.
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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.
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BackgroundShort-term forecasts of infectious disease can aid situational awareness and planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time. MethodsWe evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models into ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We compared model performance to a null model of no change. ResultsIn most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble. ConclusionsEnsembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.
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Extensive global sampling and whole genome sequencing of the pandemic virus SARS-CoV-2 have enabled researchers to characterise its spread, and to identify mutations that may increase transmission or enable the virus to escape therapies or vaccines. Two important components of viral spread are how frequently variants arise within individuals, and how likely they are to be transmitted. Here, we characterise the within-host diversity of SARS-CoV-2, and the extent to which genetic diversity is transmitted, by quantifying variant frequencies in 1390 clinical samples from the UK, many from individuals in known epidemiological clusters. We show that SARS-CoV-2 infections are characterised by low levels of within-host diversity across the entire viral genome, with evidence of strong evolutionary constraint in Spike, a key target of vaccines and antibody-based therapies. Although within-host variants can be observed in multiple individuals in the same phylogenetic or epidemiological cluster, highly infectious individuals with high viral load carry only a limited repertoire of viral diversity. Most viral variants are either lost, or occasionally fixed, at the point of transmission, consistent with a narrow transmission bottleneck. These results suggest potential vaccine-escape mutations are likely to be rare in infectious individuals. Nonetheless, we identified Spike variants present in multiple individuals that may affect receptor binding or neutralisation by antibodies. Since the fitness advantage of escape mutations in highly-vaccinated populations is likely to be substantial, resulting in rapid spread if and when they do emerge, these findings underline the need for continued vigilance and monitoring.
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The unconstrained growth rate of COVID-19 is crucial for measuring the impact of interventions, assessing worst-case scenarios, and calibrating mathematical models for policy planning. However, robust estimates are limited, with scientific focus on the time-insensitive basic reproduction number R0. Using multiple countries, data streams and methods, we consistently estimate that European COVID-19 cases doubled every three days when unconstrained, with the impact of physical distancing interventions typically seen about nine days after implementation, during which time cases grew eight-fold. The combination of fast growth and long detection delays explains the struggle in countries response better than large values of R0 alone, and warns against relaxing physical distancing measures too quickly. Testing and tracing are fundamental in shortening such delays, thus preventing cases from escalating unnoticed.