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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.

Background From 12th March 2020, individuals in England were advised to quarantine in their home if a household member tested positive for SARS-CoV-2. A mandatory isolation period of 10 days was introduced on 28th September 2020 and applied to all individuals with COVID-19. We assessed the frequency, timing, and characteristics of recovered COVID-19 cases requiring subsequent quarantine episodes due to household re-exposure. Methods In this case cohort study, all laboratory-confirmed COVID-19 cases notified in England (29th June to 28th December 2020) were analysed to identify consecutive household case(s). Multivariable logistic regression was used to determine associations between case characteristics and need to quarantine following recent infection (within 28 days of diagnosis). Results Among 1,651,550 cases resident in private dwellings and Houses of Multiple Occupancy (HMOs), 744,548 (45.1%) were the only case in their home and 56,179 (3.4%) were succeeded by further household cases diagnosed within 11–28 days of their diagnosis. Of 1,641,412 cases arising in private homes, the likelihood of further household cases was highest for Bangladeshi (aOR = 2.20, 95% CI = 2.10–2.31) and Pakistani (aOR = 2.15, 95% CI = 2.08–2.22) individuals compared to White British, as well as among young people (17-24y vs. 25-64y; aOR = 1.19, 95% CI = 1.16–1.22), men (vs. women; aOR = 1.06, 95% CI = 1.04–1.08), London residents (vs. Yorkshire and Humber; aOR = 1.57, 95% CI = 1.52–1.63) and areas of high deprivation (IMD 1 vs. 10; aOR = 1.13, 95% CI = 1.09–1.19). Conclusion Policies requiring quarantine on re-exposure differentially impact some of the most disadvantaged populations. Quarantine exemption for recently recovered individuals could mitigate the socioeconomic impact of responses to COVID-19 or similar infectious disease outbreaks.

AbstractObjectiveTo 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.DesignRetrospective cohort analysis.SettingCommunity based SARS-CoV-2 testing in England, individually linked with hospital admission data.Participants839 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 measuresHospital admission between one and 14 days after the first positive SARS-CoV-2 test.Results27 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.ConclusionsThe 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.

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.

Persons experiencing homelessness (PEH) or rough sleeping are a vulnerable population, likely to be disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. The impact of COVID-19 infection on this population is yet to be fully described in England. We present a novel method to identify COVID-19 cases in this population and describe its findings. A phenotype was developed and validated to identify PEH or rough sleeping in a national surveillance system. Confirmed COVID-19 cases in England from March 2020 to March 2022 were address-matched to known homelessness accommodations and shelters. Further cases were identified using address-based indicators, such as NHS pseudo postcodes. In total, 1835 cases were identified by the phenotype. Most were <39 years of age (66.8%) and male (62.8%). The proportion of cases was highest in London (29.8%). The proportion of cases of a minority ethnic background and deaths were disproportionality greater in this population, compared to all COVID-19 cases in England. This methodology provides an approach to track the impact of COVID-19 on a subset of this population and will be relevant to policy making. Future surveillance systems and studies may benefit from this approach to further investigate the impact of COVID-19 and other diseases on select populations.

Background The COVID‐19 pandemic has had disproportionate impact on vulnerable populations including those with learning disabilities. Assessing the incidence and risk of death in such settings can improve the prevention of COVID‐19. We describe individuals who tested positive for SARS‐CoV‐2 while residing in care homes for learning disabilities and/or autism and investigate the risk of death compared with individuals living in their own homes. Methods Surveillance records for COVID‐19 infections in England from 02 February 2020 to 31 March 2022 were extracted. Data on property type, variant wave, vaccination, hospitalisation and death were derived through data linkage and enrichment. Care home residents with learning disabilities and/or autism and diagnosed with COVID‐19 were identified and analysed, and logistic regression analyses compared the risk of death of individuals living in private residence. We assessed interaction parameters by post‐estimation analyses. Results A total of 3501 individuals were identified as diagnosed with SARS‐CoV‐2 whilst living in 632 care home properties for learning disabilities and/or autism. Of the 3686 episodes of infection, 80.4% were part of an outbreak. The crude case fatality rate was 2.6% and 0.6% among care home residents with autism and/or learning disabilities and their counterparts in households, respectively. The post‐estimation analyses found over eight times the odds of death among care home residents in 60 years old compared with their counterparts living in private homes. Conclusions Care home residents with learning disabilities and/or autism have a greater risk of death from COVID‐19. Optimising guidance to meet their needs is of great importance.

Residents of long-term care facilities (LTCFs) were disproportionately affected by the COVID-19 pandemic. We assessed the extent to which hospital-associated infections contributed to COVID-19 LTCF outbreaks in England. We matched addresses of cases between March 2020 and June 2021 to reference databases to identify LTCF residents. Linkage to health service records identified hospital-associated infections, with the number of days spent in hospital before positive specimen date used to classify these as definite or probable. Of 149,129 cases in LTCF residents during the study period, 3,748 (2.5%) were definite or probable hospital-associated and discharged to an LTCF. Overall, 431 (0.3%) were identified as index cases of potentially nosocomial-seeded outbreaks (2.7% (431/15,797) of all identified LTCF outbreaks). These outbreaks involved 4,521 resident cases and 1,335 deaths, representing 3.0% and 3.6% of all cases and deaths in LTCF residents, respectively. The proportion of outbreaks that were potentially nosocomial-seeded peaked in late June 2020, early December 2020, mid-January 2021, and mid-April 2021. Nosocomial seeding contributed to COVID-19 LTCF outbreaks but is unlikely to have accounted for a substantial proportion. The continued identification of such outbreaks after the implementation of preventative policies highlights the challenges of preventing their occurrence.

Objective: To evaluate the relationship between coronavirus disease 2019 (COVID-19) diagnosis with SARS-CoV-2 variant B.1.1.7 (also known as Variant of Concern 202012/01) and the risk of hospitalisation compared to diagnosis with wildtype SARS-CoV-2 variants. Design: Retrospective cohort, analysed using stratified Cox regression. Setting: Community-based SARS-CoV-2 testing in England, individually linked with hospitalisation data. Participants: 839,278 laboratory-confirmed COVID-19 patients, of whom 36,233 had been hospitalised within 14 days, tested between 23rd November 2020 and 31st January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF). SGTF is 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: Hospitalisation between 1 and 14 days after the first positive SARS-CoV-2 test. Results: 27,710 of 592,409 SGTF patients (4.7%) and 8,523 of 246,869 non-SGTF patients (3.5%) had been hospitalised within 1-14 days. The stratum-adjusted hazard ratio (HR) of hospitalisation was 1.52 (95% confidence interval [CI] 1.47 to 1.57) for COVID-19 patients infected with SGTF variants, compared to those infected with non-SGTF variants. The effect was modified by age (P<0.001), with HRs of 0.93-1.21 for SGTF compared to non-SGTF patients below age 20 years, 1.29 in those aged 20-29, and 1.45-1.65 in age groups 30 years or older. Conclusions: The results suggest that the risk of hospitalisation is higher for individuals infected with the B.1.1.7 variant compared to wildtype SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults above the age of 30.

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