117 results found
Ferguson N, Ghani A, Hinsley W, et al., 2022, Report 51: Evidence for age dependence in the severity of the Omicron SARS-CoV variant of concern relative to the Delta variant
Twohig KA, Nyberg T, Zaidi A, et al., 2022, Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study., Lancet Infect Dis, Vol: 22, Pages: 35-42
BACKGROUND: The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. METHODS: This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. FINDINGS: Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17-43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32-3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients
Ferguson N, Ghani A, Hinsley W, et al., 2021, Report 50: Hospitalisation risk for Omicron cases in England
To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the
Kraemer M, McCrone J, Hill V, et al., 2021, Context-specific emergence and growth of the SARS-CoV-2 Delta variant., Res Sq
The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. 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 Delta's 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. Deltaâ€™s 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.
Vohringer HS, Sanderson T, Sinnott M, et al., 2021, Genomic reconstruction of the SARS-CoV-2 epidemic in England, NATURE, Vol: 600, Pages: 506-+, ISSN: 0028-0836
Ferguson N, Ghani A, Cori A, et al., 2021, Report 49: Growth, population distribution and immune escape of Omicron in England
To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron.We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta.Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by da
Helekal D, Ledda A, Volz E, et al., 2021, Bayesian inference of clonal expansions in a dated phylogeny., Syst Biol
Microbial population genetics models often assume that all lineages are constrained by the same population size dynamics over time. However, many neutral and selective events can invalidate this assumption, and can contribute to the clonal expansion of a specific lineage relative to the rest of the population. Such differential phylodynamic properties between lineages result in asymmetries and imbalances in phylogenetic trees that are sometimes described informally but which are difficult to analyse formally. To this end, we developed a model of how clonal expansions occur and affect the branching patterns of a phylogeny. We show how the parameters of this model can be inferred from a given dated phylogeny using Bayesian statistics, which allows us to assess the probability that one or more clonal expansion events occurred. For each putative clonal expansion event we estimate its date of emergence and subsequent phylodynamic trajectory, including its long-term evolutionary potential which is important to determine how much effort should be placed on specific control measures. We demonstrate the applicability of our methodology on simulated and real datasets. Inference under our clonal expansion model can reveal important features in the evolution and epidemiology of infectious disease pathogens.
Sonabend R, Whittles LK, Imai N, et al., 2021, Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study, The Lancet, Vol: 398, Pages: 1825-1835, ISSN: 0140-6736
Background:England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.Methods:This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.Findings:The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69–83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500–5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fol
Mishra S, Mindermann S, Sharma M, et al., 2021, Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England, ECLINICALMEDICINE, Vol: 39
Kraemer MUG, Hill V, Ruis C, et al., 2021, Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence, Science, Vol: 373, Pages: 889-895, ISSN: 0036-8075
Understanding the causes and consequences of the emergence of SARS-CoV-2 variants of concern is crucial to pandemic control yet difficult to achieve, as they arise in the context of variable human behavior and immunity. We investigate the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based PCR data. We identify a multi-stage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explore how B.1.1.7 spread was shaped by non-pharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.
Didelot X, Geidelberg L, COVID-19 Genomics UK COG-UK consortium, et al., 2021, Model design for non-parametric phylodynamic inference and applications to pathogen surveillance., bioRxiv
Inference of effective population size from genomic data can provide unique information about demographic history, and when applied to pathogen genetic data can also provide insights into epidemiological dynamics. The combination of non-parametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for non-parametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on non-parametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. We demonstrate the flexibility and speed of this approach in a series of simulation experiments, and apply the methodology to reconstruct the previously described waves in the seventh pandemic of cholera. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.
Helekal D, Ledda A, Volz E, et al., 2021, Bayesian inference of clonal expansions in a dated phylogeny
<jats:title>ABSTRACT</jats:title><jats:p>Microbial population genetics models often assume that all lineages are constrained by the same population size dynamics over time. However, many neutral and selective events can invalidate this assumption, and can contribute to the clonal expansion of a specific lineage relative to the rest of the population. Such differential phylodynamic properties between lineages result in asymmetries and imbalances in phylogenetic trees that are sometimes described informally but which are difficult to analyse formally. To this end, we developed a model of how clonal expansions occur and affect the branching patterns of a phylogeny. We show how the parameters of this model can be inferred from a given dated phylogeny using Bayesian statistics, which allows us to assess the probability that one or more clonal expansion events occurred. For each putative clonal expansion event we estimate their date of emergence and subsequent phylodynamic trajectories, including their long-term evolutionary potential which is important to determine how much effort should be placed on specific control measures. We demonstrate the applicability of our methodology on simulated and real datasets.</jats:p>
Dennis AM, Frost SDW, Enders K, et al., 2021, HIV-1 Transmission linkages among persons with incident infection to inform public health surveillance, ECLINICALMEDICINE, Vol: 37
Meng B, Kemp SA, Papa G, et al., 2021, Recurrent emergence of SARS-CoV-2 spike deletion H69/V70 and its role in the Alpha variant B.1.1.7, Cell Reports, Vol: 35
We report severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike ΔH69/V70 in multiple independent lineages, often occurring after acquisition of receptor binding motif replacements such as N439K and Y453F, known to increase binding affinity to the ACE2 receptor and confer antibody escape. In vitro, we show that, although ΔH69/V70 itself is not an antibody evasion mechanism, it increases infectivity associated with enhanced incorporation of cleaved spike into virions. ΔH69/V70 is able to partially rescue infectivity of spike proteins that have acquired N439K and Y453F escape mutations by increased spike incorporation. In addition, replacement of the H69 and V70 residues in the Alpha variant B.1.1.7 spike (where ΔH69/V70 occurs naturally) impairs spike incorporation and entry efficiency of the B.1.1.7 spike pseudotyped virus. Alpha variant B.1.1.7 spike mediates faster kinetics of cell-cell fusion than wild-type Wuhan-1 D614G, dependent on ΔH69/V70. Therefore, as ΔH69/V70 compensates for immune escape mutations that impair infectivity, continued surveillance for deletions with functional effects is warranted.
Ragonnet-Cronin M, Golubchik T, Moyo S, et al., 2021, HIV genetic diversity informs stage of HIV-1 infection among patients receiving antiretroviral therapy in Botswana, The Journal of Infectious Diseases, ISSN: 0022-1899
BackgroundHIV-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However the effect of antiretroviral treatment (ART) on the inference remains unknown.MethodsParticipants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n=1944). Full-length HIV genome sequencing was performed from proviral DNA. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic and clinical data.ResultsThe best predictive model included variables for genetic diversity of HIV-1 gag, pol and env, viral load, age, sex and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95%CI:86.7%-94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record.ConclusionsThese results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.
Mishra S, Mindermann S, Sharma M, et al., 2021, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Publisher: Imperial College London, 44
Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 rapidly became the dominant lineage across much of Europe. Simultaneously, several other VOCs were identified globally. Unlike B.1.1.7, some of these VOCs possess mutations thought to confer partial immune escape. Understanding when, whether, and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. This is particularly true for England, which has high coverage from vaccines that are likely more protective against B.1.1.7 than some other VOCs. We examine trends in B.1.1.7’s prevalence in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. Our results suggest shifts in the composition of SARS-CoV-2 lineages driving transmission in England between March and April 2021. Local transmission of non-B.1.1.7 VOCs may be increasing; this warrants urgent further investigation.
Volz E, Mishra S, Chand M, et al., 2021, Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England, Nature, Vol: 593, Pages: 266-269, ISSN: 0028-0836
The SARS-CoV-2 lineage B.1.1.7, designated a Variant of Concern 202012/01 (VOC) by Public Health England1, originated in the UK in late Summer to early Autumn 20202. Whole genome SARS-CoV-2 sequence data collected from community-based diagnostic testing shows an unprecedentedly rapid expansion of the B.1.1.7 lineage during Autumn 2020, suggesting a selective advantage. 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. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Time-varying reproduction numbers for the VOC and cocirculating lineages were estimated using SGTF and genomic data. The best supported models did not indicate a substantial difference in VOC transmissibility among different age groups. There is a consensus among all analyses that the VOC has a substantial transmission advantage with a 50% to 100% higher reproduction number.
Eales O, Page AJ, Tang S, et al., 2021, SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples
Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.
Graham MS, Sudre CH, May A, et al., 2021, Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study, The Lancet Public Health, Vol: 6, Pages: e335-e345, ISSN: 2468-2667
BACKGROUND: The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. METHODS: We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. FINDINGS: From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in repo
Ragonnet-Cronin M, Boyd O, Geidelberg L, et al., 2021, Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions, Nature Communications, Vol: 12, Pages: 1-7, ISSN: 2041-1723
Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non- pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced 30 much less severe COVID-19 morbidity and mortality during the period of study.
Kemp SA, Collier DA, Datir RP, et al., 2021, SARS-CoV-2 evolution during treatment of chronic infection., Nature, Vol: 592, Pages: 277-282
The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein1 and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing an
Li X, Liu H, Rife Magalis B, et al., 2021, Molecular Evolution of Human Norovirus GII.2 Clusters, FRONTIERS IN MICROBIOLOGY, Vol: 12
Aggarwal D, Page AJ, Schaefer U, et al., 2021, An integrated analysis of contact tracing and genomics to assess the efficacy of travel restrictions on SARS-CoV-2 introduction and transmission in England from June to September, 2020
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Mitigation of SARS-CoV-2 transmission from international travel is a priority. Travellers from countries with travel restrictions (closed travel-corridors) were required to quarantine for 14 days over Summer 2020 in England. We describe the genomic epidemiology of travel-related cases in England and evaluate the effectiveness of this travel policy.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Between 27/05/2020 and 13/09/2020, probable travel-related SARS-CoV-2 cases and their contacts were identified and combined with UK SARS-CoV-2 sequencing data. The epidemiology and demographics of cases was identified, and the number of contacts per case modelled using negative binomial regression to estimate the effect of travel restriction, and any variation by age, sex and calendar date. Unique travel-related SARS-CoV-2 genomes in the COG-UK dataset were identified to estimate the effect travel restrictions on cluster size generated from these. The Polecat Clustering Tool was used to identify a travel-related SARS-CoV-2 cluster of infection.</jats:p></jats:sec><jats:sec><jats:title>Findings</jats:title><jats:p>4,207 travel-related SARS-CoV-2 cases are identified. 51.2% (2155/4207) of cases reported travel to one of three countries; 21.0% (882) Greece, 16.3% (685) Croatia and 14.0% (589) Spain. Median number of contacts per case was 3 (IQR 1-5), and greatest for the 16-20 age-group (9.0, 95% C.I.=5.6-14.5), which saw the largest attenuation by travel restriction. Travel restriction was associated with a 40% (rate ratio=0.60, 95% C.I.=0.37-0.95) lower rate of contacts. 827/4207 (19.7%) of cases had high-quality SARS-CoV-2 genomes available. Fewer genomically-linked cases were observed for index cases related to countries with travel restrictions compared to cases
Smith TP, Dorigatti I, Mishra S, et al., 2021, Environmental drivers of SARS-CoV-2 lineage B.1.1.7 transmission intensity
<jats:title>Abstract</jats:title><jats:p>Previous work has shown that environment affects SARS-CoV-2 transmission, but it is unclear whether emerging strains show similar responses. Here we show that, like other SARS-CoV-2 strains, lineage B.1.1.7 spread with greater transmission in colder and more densely populated parts of England. However, we also find evidence of B.1.1.7 having a transmission advantage at warmer temperatures compared to other strains. This implies that spring and summer conditions are unlikely to slow B.1.1.7’s invasion in Europe and across the Northern hemisphere - an important consideration for public health interventions.</jats:p>
In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts.Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world.Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation.In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.
du Plessis L, McCrone JT, Zarebski AE, et al., 2021, Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK, SCIENCE, Vol: 371, Pages: 708-+, ISSN: 0036-8075
Volz E, Hill V, McCrone J, et al., 2021, Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity, Cell, Vol: 184, Pages: 64-75.e11, ISSN: 0092-8674
In February 2020 a substitution at the interface between SARS-CoV-2 Spike protein subunits, Spike D614G, was observed in public databases. The Spike 614G variant subsequently increased in frequency in many locations throughout the world. Global patterns of dispersal of Spike 614G are suggestive of a selective advantage of this variant, however the origin of Spike 614G is associated with early colonization events in Europe and subsequent radiations to the rest of the world. Increasing frequency of 614G may therefore be due to a random founder effect. We investigate the hypothesis for positive selection of Spike 614G at the level of an individual country, the United Kingdom, using more than 25,000 whole genome SARS-CoV-2 sequences collected by COVID-19 Genomics UK Consortium. Using phylogenetic analysis, we identify Spike 614G and 614D clades with unique origins in the UK and from these we extrapolate and compare growth rates of co-circulating transmission clusters. We find that Spike 614G clusters are introduced in the UK later on average than 614D clusters and grow to larger size after adjusting for time of introduction. Phylodynamic analysis does not show a significant increase in growth rates for clusters with the 614G variant, but population genetic modelling indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We also investigate the potential influence of Spike 614D versus G on virulence by matching a subset of records to clinical data on patient outcomes. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality, but younger patients have slightly increased odds of 614G carriage. Despite the availability of a very large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of higher transmission rate for 614G, but significant differences in growth, size, and composition of these lineages indicate a need
Fu H, Wang H, Xi X, et al., 2021, A database for the epidemic trends and control measures during the first wave of COVID-19 in mainland China, International Journal of Infectious Diseases, Vol: 102, Pages: 463-471, ISSN: 1201-9712
Objectives: This data collation effort aims to provide a comprehensive database to describe the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19)across main provinces in China. Methods: From mid-January to March 2020, we extracted publicly available data on the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted a descriptive analysis of the epidemics in the six most-affected provinces. Results: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends were different across provinces. Compared to Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as local transmission of COVID-19 declined, switching the focus of measures to testing and quarantine of inbound travellers could help to sustain the control of the epidemic. Conclusions: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database with these indicators and information on control measures provides useful source for exploring further research and policy planning for response to the COVID-19 epidemic.
Didelot X, Siveroni I, Volz EM, 2021, Additive uncorrelated relaxed clock models for the dating of genomic epidemiology phylogenies, Molecular Biology and Evolution, Vol: 38, Pages: 307-317, ISSN: 0737-4038
Phylogenetic dating is one of the most powerful and commonly used methods of drawing epidemiological interpretations from pathogen genomic data. Building such trees requires considering a molecular clock model which represents the rate at which substitutions accumulate on genomes. When the molecular clock rate is constant throughout the tree then the clock is said to be strict, but this is often not an acceptable assumption. Alternatively, relaxed clock models consider variations in the clock rate, often based on a distribution of rates for each branch. However, we show here that the distributions of rates across branches in commonly used relaxed clock models are incompatible with the biological expectation that the sum of the numbers of substitutions on two neighbouring branches should be distributed as the substitution number on a single branch of equivalent length. We call this expectation the additivity property. We further show how assumptions of commonly used relaxed clock models can lead to estimates of evolutionary rates and dates with low precision and biased confidence intervals. We therefore propose a new additive relaxed clock model where the additivity property is satisfied. We illustrate the use of our new additive relaxed clock model on a range of simulated and real datasets, and we show that using this new model leads to more accurate estimates of mean evolutionary rates and ancestral dates.
Geidelberg L, Boyd O, Jorgensen D, et al., 2021, Genomic epidemiology of a densely sampled COVID-19 outbreak in China, Virus Evolution, Vol: 7, Pages: 1-7, ISSN: 2057-1577
Analysis of genetic sequence data from the SARS-CoV-2 pandemic can provide insights into epidemic origins, worldwide dispersal, and epidemiological history. With few exceptions, genomic epidemiological analysis has focused on geographically distributed data sets with few isolates in any given location. Here we report an analysis of 20 whole SARS- CoV-2 genomes from a single relatively small and geographically constrained outbreak in Weifang, People’s Republic of China. Using Bayesian model-based phylodynamic methods, we estimate a mean basic reproduction number (R0) of 3.4 (95% highest posterior density interval: 2.1-5.2) in Weifang, and a mean effective reproduction number (Rt ) that falls below 1 on February 4th. We further estimate the number of infections through time and compare these estimates to confirmed diagnoses by the Weifang Centers for Disease Control. We find that these estimates are consistent with reported cases and there is unlikely to be a large undiagnosed burden of infection over the period we studied.
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