Risk of hospitalisation or death in households with a case of COVID-19 in England: an analysis using the HOSTED dataset

Objective: To determine whether household contacts of confirmed cases of COVID-19 have an increased risk of hospitalisation or death. Methods: We used the HOSTED dataset of index cases of COVID-19 in England between June and November 2020, linked to Secondary Uses Service data on hospital episodes and Office for National Statistics’ mortality data. Multivariable logistic regression models of the odds of household contacts being hospitalised or dying within six weeks of an index case, adjusted for case type, age, sex and calendar month were calculated. Excess risk was determined by comparing the first six weeks after the index case with 6-12 weeks after the index case in a survival analysis framework. Results: Index cases were more likely to be hospitalised or die than either secondary cases or non-cases, having adjusted for age and sex. There was an increased risk of hospitalisation for non-cases (adjusted hazard ratio (aHR) 1.10 (95% CI 1.04, 1.16)) and of death (aHR 1.57 (95% CI 1.14, 2.16)) in the first six weeks after an index case, compared to 6-12 weeks after. Conclusion: Risks of hospitalisation and mortality are predictably higher in cases compared to non-cases. The short-term increase in risks for non-case contacts following diagnosis of the index case may suggest incomplete case ascertainment among contacts, although this was relatively small

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

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

Increase in Legionnaires' disease cases associated with travel to Dubai among travellers from the United Kingdom, Sweden and the Netherlands, October 2016 to end August 2017.

Between 1 October 2016 and 31 August 2017, 51 Legionnaires' disease (LD) cases from the United Kingdom, Sweden and the Netherlands were identified with associated travel to Dubai. Cases did not all stay in the same accommodation, indicating that no single accommodation could be the source for all these infections. While local investigations continue into other potential sources, clinicians should remain alert to the possibility of LD among travellers returning from Dubai with respiratory illness

Refusal of HIV testing among black Africans attending sexual health clinics in England, 2014: a review of surveillance data.

OBJECTIVES: Black Africans are one of the key risk groups for HIV in the UK and, among those living with HIV, an estimated 16% and 12% of black African heterosexual men and women, respectively, are undiagnosed and at risk of unknowingly transmitting HIV to their sex partners. Increased HIV test uptake is needed to address this, but there is limited information on how frequently HIV test refusal occurs among those attending sexual health clinics (SHCs). We identified factors associated with HIV test refusal among black African SHC attendees. METHODS: Data on all SHC attendances in England in 2014 were obtained from the genitourinary medicine clinic activity dataset, the mandatory surveillance system for STIs. Analyses were restricted to attendances by HIV-negative black Africans, and bivariate and multivariable associations between demographic and clinical characteristics and HIV test refusal were assessed. All associations were determined using generalised estimating equations logistic regression, and adjusted ORs (aORs) with 95% CIs are reported. RESULTS: Black Africans made 80 743 attendances at SHCs in 2014 and refused an HIV test on 9021 (11.2%) occasions. HIV test refusal was significantly more likely in women (aOR (95% CI) 1.54 (1.46 to 1.62) vs heterosexual men), and those living in the most deprived areas (1.44 (1.24 to 1.67)), diagnosed with a new STI (1.26 (1.18 to 1.34)) or living in London (1.06 (1.01 to 1.12)). Test refusal was significantly less likely with increasing age (0.99 (0.99 to 0.99)) and men who have sex with men (0.52 (0.43 to 0.63) vs heterosexual men), and in those tested for HIV in the past year (0.85 (0.81 to 0.89)), born outside the UK (0.73 (0.69 to 0.77)) or those attending following partner notification (0.11 (0.03 to 0.38)). CONCLUSIONS: Targeted interventions are needed to improve HIV testing uptake and reduce undiagnosed HIV infection among black Africans attending SHCs, especially heterosexuals residing in deprived areas

Rapid rise in COVID-19 among young people in England – learning for the future

Objectives We determined the age and sociodemographic distribution of COVID-19 cases between January and September 2020 to identify the group with the highest incidence rates at the beginning of the second wave in England. Study Design We undertook a retrospective cohort study design. Methods SARS-CoV-2 cases in England were linked with area-level socioeconomic status indicators using quintiles of the Index of Multiple Deprivation (IMD). Age-specific incidence rates were stratified by IMD quintile to further assess rates by area-level socioeconomic status. Results Between July and September 2020, SARS-CoV-2 incidence rates were highest amongst those aged 18 to 21 years, reaching rates of 213.9 (18-19 years) and 143.2 (20-21 years) per 100,000 population by week ending 21 September 2022. Stratification of incidence rates by IMD quintile evidenced that, despite high rates observed in the most deprived areas of England amongst the very young and older age groups, the highest rates were observed in the most affluent areas of England amongst the 18- to 21-year-olds. Conclusions The reversal of sociodemographic trend in COVID-19 cases in England for those aged 18 to 21 years at the end of the summer of 2020 and beginning of the second wave showed a novel pattern of COVID-19 risk. For other age groups, rates remained highest for those from more deprived areas, which highlighted persisting inequalities. Combined, this demonstrates the need to reinforce awareness of COVID-19 risk for young people, particularly given the late inclusion of the 16-17-year age group for vaccination administration, as well as continued efforts to reduce impact of COVID-19 on vulnerable populations

The spatio-temporal distribution of COVID-19 infection in England between January and June 2020

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 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 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 of our results 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

Risk of symptomatic COVID-19 due to aircraft transmission: a retrospective cohort study of contact-traced flights during England's containment phase.

BACKGROUND: Knowledge gaps remain regarding SARS-CoV-2 transmission on flights. We conducted a retrospective cohort study to estimate risk of acquiring symptomatic SARS-CoV-2 on aircraft, to inform contact tracing and infection control efforts. METHODS: We identified co-passengers of infectious passengers on 18 England-bound flights from European cities up to 12/03/2020, using manifests received for contact tracing. Infectious passengers were laboratory-confirmed cases with symptom onset from 7 days before to 2 days after the flight. Possible aircraft-acquired cases were laboratory-confirmed with onset 3-14 days post-flight with no known non-flight exposure. Manifests was merged with the national case management dataset (identifying cases, onset dates, contact tracing status) and the national COVID-19 linelist. Contact tracing notes were reviewed to identify non-flight exposures. We calculated attack rates (ARs) among all co-passengers and within subgroups, including by distance from infectious cases and number of infectious cases on-board. RESULTS: There were 55 infectious passengers and 2313 co-passengers, including 2221 flight-only contacts. Five possible aircraft-acquired cases were identified; ARs of 0.2% (95%CI 0.1-0.5) among all flight-only contacts and 3.8% (95%CI 1.3-10.6) among contact-traced flight-only contacts sat within a two-seat radius. The AR among 92 co-travellers with known non-flight exposure to infectious cases was 13.0% (95%CI 7.6%-21.4%). There were insufficient numbers to assess differences between subgroups. CONCLUSION: We conclude that risk of symptomatic COVID-19 due to transmission on short to medium-haul flights is low, and recommend prioritising contact-tracing of close contacts and co-travellers where resources are limited. Further research on risk on aircraft is encouraged

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

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

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

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