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ObjectivesSotrovimab is one of several therapeutic agents that have been licensed to treat people at risk of severe outcomes following COVID-19 infection. However, there are concerns that it has reduced efficacy to treat people with the BA.2 sub-lineage of the Omicron (B.1.1.529) SARS-CoV-2 variant. We compared individuals with the BA.1 or BA.2 sub-lineage of the Omicron variant treated Sotrovimab in the community to assess their risk of hospital admission. MethodsWe performed a retrospective cohort study of individuals treated with Sotrovimab in the community and either had BA.1 or BA.2 variant classification. ResultsUsing a Stratified Cox regression model it was estimated that the hazard ratios (HR) of hospital admission with a length of stay of two or more days was 1.17 for BA.2 compared to BA.1 (95% CI 0.74-1.86) and for such admissions where COVID-19 ICD-10 codes was recorded the HR was 0.98 (95% CI 0.58-1.65). ConclusionThese results suggest that the risk of hospital admission is similar between BA.1 and BA.2 cases treated with Sotrovimab in the community.
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BackgroundOver the course of the pandemic, testing policies for SARS-CoV-2 have varied considerably in England, particularly in the five months up to 1 April 2022 when free community testing ended. We described the trends and demographics of COVID-19 cases during this period. MethodsCOVID-19 cases reported between 15 November 2021 and 30 April 2022 were extracted and aggregated by testing pillar: Pillar 1 for those tested within the NHS, private or public health laboratories, and Pillar 2 for community testing. COVID-19 cases were described by epi-week, and stratified by test type, age, sex, index of multiple deprivation (IMD), region, and population density. Incidence rates were also calculated and stratified by IMD and region. ResultsOf 10,196,425 COVID-19 cases, 7.3% were reported under Pillar 1 and 92.7% under Pillar 2. From 15 November 2021 to 31 March 2022, most Pillar 2 cases were tested either by polymerase chain reaction (PCR) only or PCR with lateral flow device (LFD) (70.8%) and three in ten cases tested using LFD only. However, between 1 April and 30 April 2022 this rose to nine out of ten cases testing using LFD only. Over the whole period studied and under both pillars, the majority of cases were female (55.2%), resided in the South East (17.0%) and in the age group 30-39 years (18.6%). Trends in IMD and population density varied over the period. When stratifying by IMD the highest case numbers and incidence rates reported under Pillar 1 and NHS were in those in the most deprived quintile. This was also seen for cases reported under Pillar 2 by LFD until 11 January 2022, where a reverse in the trend occurred with the highest cases and rates in the least deprived quintile. This same pattern was observed when describing the cases by population density, with Pillar 2 LFD reported cases being highest in the most densely populated regions until 11 January, from when there was a switch to the highest cases being in the least densely populated regions. ConclusionDifferences and trends were observed in reported COVID-19 cases in England, particularly those tested under Pillar 2 following the introduction of testing policy changes. To better understand the impact of these changes over the course of the COVID-19 pandemic, as well as to predict the impact of future testing policies, it would be beneficial to investigate the accessibility of testing amongst different populations. Currently, Pillar 1 COVID-19 cases are likely to be more representative of symptomatic cases requiring testing for a clinical need, as these are less impacted by variations in testing patterns compared to Pillar 2. However, a limitation of that approach is that use of Pillar 1 alone would be biased towards those more likely to be clinically unwell.
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PurposeThe Gamma variant of SARS-CoV-2, first detected in travellers from Brazil, was found to have high transmissibility and virulence; following this finding, this paper aims to describe the epidemiology of Gamma cases in England from its first detection on 12 February 2021 to 31 August 2021. MethodsThe demographic analysis of Gamma cases was stratified by travel exposure. Travel-associated cases were further analysed by countries travelled from, stratified by categories set in place by the Red (highest risk countries), Amber, Green (lowest risk countries) travel policy, which was implemented from May to October 2021. ResultsThere were 251 confirmed Gamma cases detected in England in the study period. 35.1% were imported, 5.6% were secondary, and 29.5% were not travel associated. Early cases were predominantly travel-associated, with later cases likely obtained through community transmission. 51.0% of travel-related cases were travellers from Amber countries, and 40.2% had at least one Red country in their journey. ConclusionThe Gamma variant has not seen the same expansion as other variants such as Delta, most likely due to Delta out-competing community transmission of Gamma. Findings indicate the travel policy requiring quarantine for Red and Amber list travellers may have also contributed to preventing onward transmission of Gamma.
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BackgroundThe SARS-CoV-2 Omicron variant (B.1.1.529) has rapidly replaced the Delta variant (B.1.617.2) to become dominant in England. This epidemiological study assessed differences in transmissibility between the Omicron and Delta using two methods and data sources. MethodsOmicron and Delta cases were identified through genomic sequencing, genotyping and S-gene target failure in England from 5-11 December 2021. Secondary attack rates for Omicron and Delta using named contacts and household clustering were calculated using national surveillance and contact tracing data. We used multivariable logistic regression was used to control for factors associated with transmission. FindingsAnalysis of contact tracing data identified elevated secondary attack rates for Omicron vs Delta in household (15.0% vs 10.8%) and non-household (8.2% vs 3.7%) settings. The proportion of index cases resulting in residential clustering was twice as high for Omicron (16.1%) compared to Delta (7.3%). Transmission was significantly less likely from cases, or in named contacts, in receipt of three compared to two vaccine doses in household settings, but less pronounced for Omicron (aRR 0.78 and 0.88) compared to Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed for Delta cases and contacts (aRR 0.84 and 0.51) but only for Omicron contacts (aRR 0.76, 95% CI: 0.58-0.93) and not cases in receipt of three vs two doses (aRR 0.95, 0.77-1.16). InterpretationOur study identified increased risk of onward transmission of Omicron, consistent with its successful global displacement of Delta. We identified a reduced effectiveness of vaccination in lowering risk of transmission, a likely contributor for the rapid propagation of Omicron. FundingStudy funded by the UK Health Security Agency.
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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.
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BackgroundA rapid increase in cases due to the SARS-CoV-2 Omicron (B.1.1.529) variant in highly vaccinated populations has raised concerns about the effectiveness of current vaccines. MethodsWe used a test-negative case-control design to estimate vaccine effectiveness (VE) against symptomatic disease caused by the Omicron and Delta variants in England. VE was calculated after primary immunisation with two BNT162b2 or ChAdOx1 doses, and at 2+ weeks following a BNT162b2 booster. ResultsBetween 27 November and 06 December 2021, 581 and 56,439 eligible Omicron and Delta cases respectively were identified. There were 130,867 eligible test-negative controls. There was no effect against Omicron from 15 weeks after two ChAdOx1 doses, while VE after two BNT162b2 doses was 88.0% (95%CI: 65.9 to 95.8%) 2-9 weeks after dose 2, dropping to between 34 and 37% from 15 weeks post dose 2.From two weeks after a BNT162b2 booster, VE increased to 71.4% (95%CI: 41.8 to 86.0%) for ChAdOx1 primary course recipients and 75.5% (95%CI: 56.1 to 86.3%) for BNT162b2 primary course recipients. For cases with Delta, VE was 41.8% (95%CI: 39.4-44.1%) at 25+ weeks after two ChAdOx1 doses, increasing to 93.8% (95%CI: 93.2-94.3%) after a BNT162b2 booster. With a BNT162b2 primary course, VE was 63.5% (95%CI: 61.4 to 65.5%) 25+ weeks after dose 2, increasing to 92.6% (95%CI: 92.0-93.1%) two weeks after the booster. ConclusionsPrimary immunisation with two BNT162b2 or ChAdOx1 doses provided no or limited protection against symptomatic disease with the Omicron variant. Boosting with BNT162b2 following either primary course significantly increased protection.
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BackgroundHousehold transmission has been demonstrated to be an important factor in the population-level growth of COVID-19. UK Health Security Agency (UKHSA) maintains data on positive tests for COVID-19 and the residential addresses of cases. We sought to use this information to characterise clusters of COVID-19 in multi-generational households in England. MethodsUsing cross-sectional design, cases of COVID-19 were assigned to clusters if they occurred in the same residential property in a 14-day rolling window. Patient demographic data were supplemented with reference to the ONS index of multiple deprivation and population density. Multi-generational households were defined as a cluster with at least three people, with one case in a person who was 0-16 years old and one case in a person who was [≥] 60 years old, with at least 16 years between two members of each age group. ResultsA total of 3,647,063 COVID-19 cases were reported between 01 April 2020 and 20 May 2021. Of these, 1,980,527 (54.3 %) occurred in residential clusters. Multi-generational households formed 1.5 % of clusters, with these more likely to occur in areas of higher population density and higher relative deprivation. Multi-generational clusters were more common among households of non-White ethnicity and formed larger clusters than non-multi-generational clusters (median cluster size 6, IQR 4-11 vs 3, IQR 3-4, respectively). ConclusionMulti-generational clusters were not highly prevalent in England during the study period, however were more common in certain populations. BOX TEXTO_ST_ABSWhat is already known on this subjectC_ST_ABSGreater risk of infection with SARS-CoV-2 in England is associated with being of non-White ethnicity, residence in an area of greater deprivation and higher population density. What is less clear is the role of household composition in the risk of COVID-19 transmission. It has been hypothesised that multi-generational housing (in which at least three different generations are resident in the same property) accounted for a substantial proportion of COVID-19 cases. We sought to test this hypothesis. What this study addsThis study provides descriptive evidence around the role of multi-generational households in the COVID-19 pandemic in England between April 2020 and March 2021. It does not support the hypothesis that this period (a period of low incidence in England), a substantial proportion of COVID-19 cases occurred in multi-generational households.
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BackgroundThis study measured the long-term health-related quality of life of non-hospitalised COVID-19 cases with PCR-confirmed SARS-CoV-2(+) infection using the recommended instrument in England (the EQ-5D). MethodsProspective cohort study of SARS-CoV-2(+) cases aged 12-85 years and followed up for six months from 01 December 2020, with cross-sectional comparison to SARS-CoV-2(-) controls. Main outcomes were loss of quality-adjusted life days (QALDs); physical symptoms; and COVID-19-related private expenditures. We analysed results using multivariable regressions with post-hoc weighting by age and sex, and conditional logistic regressions for the association of each symptom and EQ-5D limitation on cases and controls. ResultsOf 548 cases (mean age 41.1 years; 61.5% female), 16.8% reported physical symptoms at month 6 (most frequently extreme tiredness, headache, loss of taste and/or smell, and shortness of breath). Cases reported more limitations with doing usual activities than controls. Almost half of cases spent a mean of {pound}18.1 on non-prescription drugs (median: {pound}10.0), and 52.7% missed work or school for a mean of 12 days (median: 10). On average, all cases lost 15.9 (95%-CI: 12.1, 19.7) QALDs, while those reporting symptoms at month 6 lost 34.1 (29.0, 39.2) QALDs. Losses also increased with older age. Cumulatively, the health loss from morbidity contributes at least 21% of the total COVID-19-related disease burden in England. ConclusionsOne in 6 cases report ongoing symptoms at 6 months, and 10% report prolonged loss of function compared to pre-COVID-19 baselines. A marked health burden was observed among older COVID-19 cases and those with persistent physical symptoms. summaryLosses of health-related quality of life in non-hospitalised COVID-19 cases increase by age and for cases with symptoms after 6 months. At a population level, at least 21% of the total COVID-19-related disease burden in England is attributable to morbidity.
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BackgroundThe B.1.617.2 COVID-19 variant has contributed to the surge in cases in India and has now been detected across the globe, including a notable increase in cases in the UK. We estimate the effectiveness of the BNT162b2 and ChAdOx1 COVID-19 vaccines against this variant. MethodsA test negative case control design was used to estimate the effectiveness of vaccination against symptomatic disease with both variants over the period that B.1.617.2 began circulating with cases identified based on sequencing and S-gene target status. Data on all symptomatic sequenced cases of COVID-19 in England was used to estimate the proportion of cases with B.1.617.2 compared to the predominant strain (B.1.1.7) by vaccination status. ResultsEffectiveness was notably lower after 1 dose of vaccine with B.1.617.2 cases 33.5% (95%CI: 20.6 to 44.3) compared to B.1.1.7 cases 51.1% (95%CI: 47.3 to 54.7) with similar results for both vaccines. With BNT162b2 2 dose effectiveness reduced from 93.4% (95%CI: 90.4 to 95.5) with B.1.1.7 to 87.9% (95%CI: 78.2 to 93.2) with B.1.617.2. With ChAdOx1 2 dose effectiveness reduced from 66.1% (95% CI: 54.0 to 75.0) with B.1.1.7 to 59.8% (95%CI: 28.9 to 77.3) with B.1.617.2. Sequenced cases detected after 1 or 2 doses of vaccination had a higher odds of infection with B.1.617.2 compared to unvaccinated cases (OR 1.40; 95%CI: 1.13-1.75). ConclusionsAfter 2 doses of either vaccine there were only modest differences in vaccine effectiveness with the B.1.617.2 variant. Absolute differences in vaccine effectiveness were more marked with dose 1. This would support maximising vaccine uptake with two doses among vulnerable groups.
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The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed. A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk. Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rd March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout. In terms of controlling transmission, the most important practical application is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.
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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.
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BackgroundHouseholds appear to be the highest risk setting for transmission of COVID-19. Large household transmission studies were reported in the early stages of the pandemic in Asia with secondary attack rates ranging from 5-30% but few large scale household transmission studies have been conducted outside of Asia. MethodsA prospective case ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. Household secondary attack rates and serial intervals were estimated. Individual and household basic reproduction numbers were also estimated. The incubation period was estimated using known point source exposures that resulted in secondary cases. ResultsA total of 233 households with two or more people were included with a total of 472 contacts. The overall household SAR was 37% (95% CI 31-43%) with a mean serial interval of 4.67 days, an R0 of 1.85 and a household reproduction number of 2.33. We find lower secondary attack rates in larger households. SARs were highest when the primary case was a child. We estimate a mean incubation period of around 4.5 days. ConclusionsHigh rates of household transmission of COVID-19 were found in the UK emphasising the need for preventative measures in this setting. Careful monitoring of schools reopening is needed to monitor transmission from children.
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ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases. MethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. FindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. ConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.