Genomic reconstruction of the SARS-CoV-2 epidemic across England from September 2020 to May 2021 (preprint)

Despite regional successes in controlling the SARS-CoV-2 pandemic, global cases have reached an all time high in April 2021 in part due to the evolution of more transmissible variants. Here we use the dense genomic surveillance generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 62 different lineages in each of 315 English local authorities between September 2020 and April 2021. This analysis reveals a series of sub-epidemics that peaked in the early autumn of 2020, followed by a singular jump in transmissibility of the B.1.1.7 lineage. B.1.1.7 grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown eventually suppressed B.1.1.7 and eliminated nearly all other lineages in early 2021. However, a series of variants (mostly containing the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. Accounting for sustained introductions, however, indicates that their transmissibility is unlikely to exceed that of B.1.1.7. Finally, B.1.617.2 was repeatedly introduced to England and grew rapidly in April 2021, constituting approximately 40% of sampled COVID-19 genomes on May 15.

Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data (preprint)

The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, we find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.

Patterns of within-host genetic diversity in SARS-CoV-2 (preprint)

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The Impact of COVID-19 Lockdown on Disordered Eating Behaviors in a Community Sample: The Mediation Role of Psychological Distress (preprint)

Objective: This study aims to explore associations between disordered eating behaviors in adults during the COVID-19 lockdown period, and the experienced psychosocial impact of the COVID-19 pandemic, depressive symptomatology, anxiety/stress levels.Methods: This was a community-based cross-sectional study assessing 254 Portuguese adults (82.7% women; 35.82 ±11.82 years) one week after the end of the mandatory COVID-19 lockdown in Portugal. An online survey was conducted to evaluate psychological distress, disordered eating, and psychosocial impact of the COVID-19 pandemic. Pearson correlations and Structural Equation Modeling (SEM) were performed.Results: Participants reported the presence of meal skipping (52.8%), grazing eating behavior (80.9%), overeating (81.0%), loss of control over eating (47.2%), and binge eating episodes (39.2%) during lockdown. Uncontrolled and emotional eating were significantly correlated with the psychosocial impact of COVID-19 pandemic, depression, anxiety, and stress levels. SEM analyses indicated that the relationship between experienced psychosocial impact of COVID-19 pandemic on disordered eating behaviors was mediated through psychological distress experienced (CMIN/DF= 1.499, CFI = .99, RMSEA = .045).Conclusions: The psychosocial impact of the COVID-19 pandemic crisis may lead to disordered eating, and this relation may occur through the elevation of psychological distress. These findings inform about clinical targets for preventive interventions to promote disordered eating in a community sample during potential similar future situations. 

MAJORA: Continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance (preprint)

Genomic epidemiology has become an increasingly common tool for epidemic response. Recent technological advances have made it possible to sequence genomes rapidly enough to inform outbreak response, and cheaply enough to justify dense sampling of even large epidemics. With increased availability of sequencing it is possible for agile networks of sequencing facilities to collaborate on the sequencing and analysis of epidemic genomic data. In response to the ongoing SARS-CoV-2 pandemic in the United Kingdom, the COVID-19 Genomics UK (COG-UK) consortium was formed with the aim of rapidly sequencing SARS-CoV-2 genomes as part of a national-scale genomic surveillance strategy. The network consists of universities, academic institutes, regional sequencing centres and the four UK Public Health Agencies. We describe the development and deployment of Majora, an encompassing digital infrastructure to address the challenge of collecting and integrating both genomic sequencing data and sample-associated metadata produced across the COG-UK network. The system was designed and implemented pragmatically to stand up capacity rapidly in a pandemic caused by a novel virus. This approach has underpinned the success of COG-UK, which has rapidly become the leading contributor of SARS-CoV-2 genomes to international databases and has generated over 60,000 sequences to date.

COVID-19 infection dynamics in care homes in the East of England: a retrospective genomic epidemiology study (preprint)

Background COVID-19 poses a major challenge to infection control in care homes. SARS-CoV-2 is readily transmitted between people in close contact and causes disproportionately severe disease in older people. Methods Data and SARS-CoV-2 samples were collected from patients in the East of England (EoE) between 26th February and 10th May 2020. Care home residents were identified using address search terms and Care Quality Commission registration information. Samples were sequenced at the University of Cambridge or the Wellcome Sanger Institute and viral clusters defined based on genomic and time differences between cases. Findings 7,406 SARS-CoV-2 positive samples from 6,600 patients were identified, of which 1,167 (18.2%) were residents from 337 care homes. 30/71 (42.3%) care home residents tested at Cambridge University Hospitals NHS Foundation Trust (CUH) died. Genomes were available for 700/1,167 (60%) residents from 292 care homes, and 409 distinct viral clusters were defined. We identified several probable transmissions between care home residents and healthcare workers (HCW). Interpretation Care home residents had a significant burden of COVID-19 infections and high mortality. Larger viral clusters were consistent with within-care home transmission, while multiple clusters per care home suggested independent acquisitions.