11 research outputs found

    Effect of Returning University Students on COVID-19 Infections in England, 2020

    Get PDF
    Each September in England, ≈1 million students relocate to study at universities. To determine COVID-19 cases and outbreaks among university students after their return to university during the COVID pandemic in September 2020, we identified students with COVID-19 (student case-patients) by reviewing contact tracing records identifying attendance at university and residence in student accommodations identified by matching case-patients’ residential addresses with national property databases. We determined COVID-19 rates in towns/cities with and without a university campus. We identified 53,430 student case-patients during September 1–December 31, 2020, which accounted for 2.7% of all cases during this period. Student case-patients increased rapidly after the start of the term, driven initially by cases and outbreaks in student accommodations. Case rates among students 18–23 years of age doubled at the start of term in towns with universities. Our findings highlight the need for face-to-face and control measures to reduce virus transmission

    Risk of hospital admission for patients with SARS-CoV-2 variant B.1.1.7: cohort analysis

    Get PDF
    Abstract: Objective: To evaluate the relation between diagnosis of covid-19 with SARS-CoV-2 variant B.1.1.7 (also known as variant of concern 202012/01) and the risk of hospital admission compared with diagnosis with wild-type SARS-CoV-2 variants. Design: Retrospective cohort analysis. Setting: Community based SARS-CoV-2 testing in England, individually linked with hospital admission data. Participants: 839 278 patients with laboratory confirmed covid-19, of whom 36 233 had been admitted to hospital within 14 days, tested between 23 November 2020 and 31 January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF), a proxy test for the B.1.1.7 variant. Patient data were stratified by age, sex, ethnicity, deprivation, region of residence, and date of positive test. Main outcome measures: Hospital admission between one and 14 days after the first positive SARS-CoV-2 test. Results: 27 710 (4.7%) of 592 409 patients with SGTF variants and 8523 (3.5%) of 246 869 patients without SGTF variants had been admitted to hospital within one to 14 days. The stratum adjusted hazard ratio of hospital admission was 1.52 (95% confidence interval 1.47 to 1.57) for patients with covid-19 infected with SGTF variants, compared with those infected with non-SGTF variants. The effect was modified by age (P<0.001), with hazard ratios of 0.93-1.21 in patients younger than 20 years with versus without SGTF variants, 1.29 in those aged 20-29, and 1.45-1.65 in those aged ≥30 years. The adjusted absolute risk of hospital admission within 14 days was 4.7% (95% confidence interval 4.6% to 4.7%) for patients with SGTF variants and 3.5% (3.4% to 3.5%) for those with non-SGTF variants. Conclusions: The results suggest that the risk of hospital admission is higher for people infected with the B.1.1.7 variant compared with wild-type SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults older than 30 years

    Comparative transmission of SARS-CoV-2 Omicron (B.1.1.529) and Delta (B.1.617.2) variants and the impact of vaccination: national cohort study, England

    Get PDF
    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) rapidly replaced Delta (B.1.617.2) to become dominant in England. Our study assessed differences in transmission between Omicron and Delta using two independent data sources and methods. Omicron 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 named contacts were calculated in household and non-household settings using contact tracing data, while household clustering was identified using national surveillance data. Logistic regression models were applied to control for factors associated with transmission for both methods. For contact tracing data, higher secondary attack rates for Omicron vs. Delta were identified in households (15.0% vs. 10.8%) and non-households (8.2% vs. 3.7%). For both variants, in household settings, onward transmission was reduced from cases and named contacts who had three doses of vaccine compared to two, but this effect was less pronounced for Omicron (adjusted risk ratio, aRR 0.78 and 0.88) than Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed only in contacts who had three doses vs. two doses for both Delta (aRR 0.51) and Omicron (aRR 0.76). For national surveillance data, the risk of household clustering, was increased 3.5-fold for Omicron compared to Delta (aRR 3.54 (3.29-3.81)). Our 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

    SHOT is affiliated to the Royal College of Pathologists. This report is produced by SHOT working with MHRA.

    No full text
    Transfusion delays, particularly in major haemorrhage and major trauma situations, must be prevented. Delays in provision and administration of blood components including delays in anticoagulant reversal, particularly in patients with intracranial haemorrhage, can result in death, or serious sequelae. Every minute counts in these situations. Effective and reliable transfusion information technology systems should be implemented to reduce the risk of errors at all steps in the transfusion pathway, provided they are configured and used correctly. Effective investigation of all incidents and near miss events, application of effective corrective and preventive actions, and closing the loop by measuring the effectiveness of interventions should be carried out to optimise learning from incidents Taken from Key recommendations from summary: https://www.shotuk.org/wp-content/uploads/myimages/SHOT-Summary-ZCard-2020-v2.2.pdf Full text available at: https://www.shotuk.org/wp-content/uploads/myimages/SHOT-REPORT-2020.pd

    Impact of SARS-CoV-2 Alpha variant (B.1.1.7) on prisons, England

    No full text
    Objectives: prisons are high-risk settings for infectious disease outbreaks because of their highly dynamic and crowded nature. During late 2020, prisons in England observed a surge in COVID-19 infection. This study describes the emergence of the Alpha variant in prisons during this period.Methods: Alpha and non-Alpha variant COVID-19 cases were identified in prisoners in England using address-matched laboratory notifications and genomic information from COG-UK.Results: of 14,094 COVID-19-positive prisoner cases between 1 October 2020 and 28 March 2021, 11.5% (n = 1621) had sequencing results. Of these, 1082 (66.7%) were identified as the Alpha variant. Twenty-nine (2.7%) Alpha cases required hospitalisation compared with only five (1.0%; P = 0.02) non-Alpha cases. A total of 14 outbreaks were identified with the median attack rate higher for Alpha (17.9%, interquartile range [IQR] 3.2%-32.2%; P = 0.11) than non-Alpha outbreaks (3.5%, IQR 2.0%-10.2%).Conclusion: higher attack rates and increased likelihood of hospitalisations were observed for Alpha cases compared with non-Alpha. This suggests a key contribution to the rise in cases, hospitalisations and outbreaks in prisons in the second wave. With prisons prone to COVID-19 outbreaks and the potential to act as reservoirs for variants of concern, sequencing of prison-associated cases alongside whole-institution vaccination should be prioritised.</p

    Kinetics of viral loads and genotypic analysis of elephant endotheliotropic herpesvirus-1 infection in captive Asian elephants (Elephas maximus)

    No full text
    Elephant endotheliotropic herpesviruses (EEHVs) can cause fatal hemorrhagic disease in juvenile Asian elephants (Elephas maximus); however, sporadic shedding of virus in trunk washes collected from healthy elephants also has been detected. Data regarding the relationship of viral loads in blood compared with trunk washes are lacking, and questions about whether elephants can undergo multiple infections with EEHVs have not been addressed previously. Real-time quantitative polymerase chain reaction was used to determine the kinetics of EEHV1 loads, and genotypic analysis was performed on EEHV1 DNA detected in various fluid samples obtained from five Asian elephants that survived detectable EEHV1 DNAemia on at least two separate occasions. In three elephants displaying clinical signs of illness, preclinical EEHV1 DNAemia was detectable, and peak whole-blood viral loads occurred 3 “8 days after the onset of clinical signs. In two elephants with EEHV1 DNAemia that persisted for 7 “21 days, no clinical signs of illness were observed. Detection of EEHV1 DNA in trunk washes peaked approximately 21 days after DNAemia, and viral genotypes detected during DNAemia matched those detected in subsequent trunk washes from the same elephant. In each of the five elephants, two distinct EEHV1 genotypes were identified in whole blood and trunk washes at different time points. In each case, these genotypes represented both an EEHV1A and an EEHV1B subtype. These data suggest that knowledge of viral loads could be useful for the management of elephants before or during clinical illness. Furthermore, sequential infection with both EEHV1 subtypes occurs in Asian elephants, suggesting that they do not elicit cross-protective sterilizing immunity. These data will be useful to individuals involved in the husbandry and clinical care of Asian elephants

    Household transmission of COVID-19 cases associated with SARS-CoV-2 delta variant (B.1.617.2): national case-control study

    Get PDF
    Background: The SARS-CoV-2 Delta variant (B.1.617.2), first detected in India, has rapidly become the dominant variant in England. Early reports suggest this variant has an increased growth rate suggesting increased transmissibility. This study indirectly assessed differences in transmissibility between the emergent Delta variant compared to the previously dominant Alpha variant (B.1.1.7). Methods: A matched case-control study was conducted to estimate the odds of household transmission (≥ 2 cases within 14 days) for Delta variant index cases compared with Alpha cases. Cases were derived from national surveillance data (March to June 2021). One-to-two matching was undertaken on geographical location of residence, time period of testing and property type, and a multivariable conditional logistic regression model was used for analysis. Findings: In total 5,976 genomically sequenced index cases in household clusters were matched to 11,952 sporadic index cases (single case within a household). 43.3% (n=2,586) of cases in household clusters were confirmed Delta variant compared to 40.4% (n= 4,824) of sporadic cases. The odds ratio of household transmission was 1.70 among Delta variant cases (95% CI 1.48-1.95, p <0.001) compared to Alpha cases after adjusting for age, sex, ethnicity, index of multiple deprivation (IMD), number of household contacts and vaccination status of index case. Interpretation: We found evidence of increased household transmission of SARS-CoV-2 Delta variant, potentially explaining its success at displacing Alpha variant as the dominant strain in England. With the Delta variant now having been detected in many countries worldwide, the understanding of the transmissibility of this variant is important for informing infection prevention and control policies internationally
    corecore