Age-specific associations between underlying health conditions and hospitalisation, death and in-hospital death among confirmed COVID-19 cases: a multi-country study based on surveillance data, June to December 2020.

BackgroundUnderlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.AimWe sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.MethodsWe analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition-age group combination.ResultsCancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5-5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.ConclusionWhile supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.

Rapid influenza molecular testing in secondary care and influenza surveillance in England: Any impact?

INTRODUCTION: The use of rapid molecular testing for influenza diagnosis is becoming increasingly popular. Used at the point of care or in a clinical laboratory, these tests detect influenza A and B viruses, though many do not distinguish between influenza A subtypes. The UK Severe Influenza Surveillance System (USISS) collects surveillance data on laboratory-confirmed influenza admissions to secondary care in England. This study set out to understand how rapid influenza molecular testing was being used and how it might influence the availability of subtyping data collected on influenza cases admitted to secondary care in England. METHODS: At the end of the 2017/2018 and 2018/2019 influenza seasons, a questionnaire was sent to all National Health Service Hospital Trusts in England to evaluate the use of rapid influenza testing. Surveillance data collected through USISS was analysed from 2011/2012 to 2020/2021. RESULTS: Of responding trusts, 42% (13/31) in 2017/2018 and 55% (9/17) in 2018/2019 used rapid influenza molecular tests, either alone or in combination with other testing. The majority of rapid tests used did not subtype the influenza A result, and limited follow-up testing occurred. Surveillance data showed significant proportions of influenza A hospital and intensive care unit/high dependency unit admissions without subtyping information, increasing by approximately 35% between 2012/2013 and 2020/2021. CONCLUSIONS: The use of rapid influenza molecular tests is a likely contributing factor to the large proportion of influenza A hospitalisations in England that were unsubtyped. Given their clear clinical advantages, further work must be done to reinforce these data for public health through integrated genomic surveillance.

Live-attenuated influenza vaccine effectiveness against hospitalization in children aged 2-6 years, the first three seasons of the childhood influenza vaccination program in England, 2013/14-2015/16.

INTRODUCTION: In 2013, the United Kingdom began to roll-out a universal annual influenza vaccination program for children. An important component of any new vaccination program is measuring its effectiveness. Live-attenuated influenza vaccines (LAIVs) have since shown mixed results with vaccine effectiveness (VE) varying across seasons and countries elsewhere. This study aims to assess the effectiveness of influenza vaccination in children against severe disease during the first three seasons of the LAIV program in England. METHODS: Using the screening method, LAIV vaccination coverage in children hospitalized with laboratory-confirmed influenza infection was compared with vaccination coverage in 2-6-year-olds in the general population to estimate VE in 2013/14-2015/16. RESULTS: The overall LAIV VE, adjusted for age group, week/month and geographical area, for all influenza types pooled over the three influenza seasons was 50.1% (95% confidence interval [CI] 31.2, 63.8). By age, there was evidence of protection against hospitalization from influenza vaccination in both the pre-school (2-4-year-olds) (48.1%, 95% CI 27.2, 63.1) and school-aged children (5-6-year-olds) (62.6%, 95% CI 2.6, 85.6) over the three seasons. CONCLUSION: LAIV vaccination in children provided moderate annual protection against laboratory-confirmed influenza-related hospitalization in England over the three influenza seasons. This study contributes further to the limited literature to date on influenza VE against severe disease in children.

Estimated number of deaths directly averted in people 60 years and older as a result of COVID-19 vaccination in the WHO European Region, December 2020 to November 2021.

Since December 2019, over 1.5 million SARS-CoV-2-related fatalities have been recorded in the World Health Organization European Region - 90.2% in people ≥ 60 years. We calculated lives saved in this age group by COVID-19 vaccination in 33 countries from December 2020 to November 2021, using weekly reported deaths and vaccination coverage. We estimated that vaccination averted 469,186 deaths (51% of 911,302 expected deaths; sensitivity range: 129,851-733,744; 23-62%). Impact by country ranged 6-93%, largest when implementation was early.

Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010.

BACKGROUND: During 2009-2010, pandemic influenza A (H1N1) pdm09 virus (pH1N1) infections in England occurred in two epidemic waves. Reasons for a reported increase in case-severity during the second wave are unclear. METHODS: We analysed hospital-based surveillance for patients with pH1N1 infections in England during 2009-2010 and linked national data sets to estimate ethnicity, socio-economic status and death within 28 days of admission. We used multivariable logistic regression to assess whether changes in demographic, clinical and management characteristics of patients could explain an increase in ICU admission or death, and accounted for missing values using multiple imputation. RESULTS: During the first wave, 54/960 (6%) hospitalised patients required intensive care and 21/960 (2%) died; during the second wave 143/1420 (10%) required intensive care and 55/1420 (4%) died. In a multivariable model, during the second wave patients were less likely to be from an ethnic minority (OR 0.33, 95% CI 0.26-0.42), have an elevated deprivation score (OR 0.75, 95% CI 0.68-0.83), have known comorbidity (OR 0.78, 95% CI 0.63-0.97) or receive antiviral therapy ≤2 days before onset (OR 0.72, 95% CI 0.56-0.92). Increased case-severity during the second wave was not explained by changes in demographic, clinical or management characteristics. CONCLUSIONS: Monitoring changes in patient characteristics could help target interventions during multiple waves of COVID-19 or a future influenza pandemic. To understand and respond to changes in case-severity, surveillance is needed that includes additional factors such as admission thresholds and seasonal coinfections.