Occupational inequalities in the prevalence of COVID-19: A longitudinal observational study of England, August 2020 to January 2021.

The COVID-19 pandemic has reinforced, amplified and created new health inequalities. Examining how COVID-19 prevalence varies by measures of work and occupation may help to understand these inequalities. The aim of the study is to evaluate how occupational inequalities in the prevalence of COVID-19 varies across England and their possible explanatory factors. We used data for 363,651 individuals (2,178,835 observations) aged 18 years and over between 1st May 2020 and 31st January 2021 from the Office for National Statistics Covid Infection Survey, a representative longitudinal survey of individuals in England. We focus on two measures of work; employment status for all adults, and work sector of individuals currently working. Multi-level binomial regression models were used to estimate the likelihood of testing positive of COVID-19, adjusting for known explanatory covariates. 0.9% of participants tested positive for COVID-19 over the study period. COVID-19 prevalence was higher among adults who were students or furloughed (i.e., temporarily not working). Among adults currently working, COVID-19 prevalence was highest in adults employed in the hospitality sector, with higher prevalence for individuals employed in transport, social care, retail, health care and educational sectors. Inequalities by work were not consistent over time. We find an unequal distribution of infections relating to COVID-19 by work and employment status. While our findings demonstrate the need for greater workplace interventions to protect employees tailored to their specific work sector needs, focusing on employment alone ignores the importance of SARS-CoV-2 transmission outside of employed work (i.e., furloughed and student populations).

Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection: protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales.

INTRODUCTION: SARS-CoV-2 infection rarely causes hospitalisation in children and young people (CYP), but mild or asymptomatic infections are common. Persistent symptoms following infection have been reported in CYP but subsequent healthcare use is unclear. We aim to describe healthcare use in CYP following community-acquired SARS-CoV-2 infection and identify those at risk of ongoing healthcare needs. METHODS AND ANALYSIS: We will use anonymised individual-level, population-scale national data linking demographics, comorbidities, primary and secondary care use and mortality between 1 January 2019 and 1 May 2022. SARS-CoV-2 test data will be linked from 1 January 2020 to 1 May 2022. Analyses will use Trusted Research Environments: OpenSAFELY in England, Secure Anonymised Information Linkage (SAIL) Databank in Wales and Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 in Scotland (EAVE-II). CYP aged ≥4 and <18 years who underwent SARS-CoV-2 reverse transcription PCR (RT-PCR) testing between 1 January 2020 and 1 May 2021 and those untested CYP will be examined.The primary outcome measure is cumulative healthcare cost over 12 months following SARS-CoV-2 testing, stratified into primary or secondary care, and physical or mental healthcare. We will estimate the burden of healthcare use attributable to SARS-CoV-2 infections in the 12 months after testing using a matched cohort study of RT-PCR positive, negative or untested CYP matched on testing date, with adjustment for confounders. We will identify factors associated with higher healthcare needs in the 12 months following SARS-CoV-2 infection using an unmatched cohort of RT-PCR positive CYP. Multivariable logistic regression and machine learning approaches will identify risk factors for high healthcare use and characterise patterns of healthcare use post infection. ETHICS AND DISSEMINATION: This study was approved by the South-Central Oxford C Health Research Authority Ethics Committee (13/SC/0149). Findings will be preprinted and published in peer-reviewed journals. Analysis code and code lists will be available through public GitHub repositories and OpenCodelists with meta-data via HDR-UK Innovation Gateway.

Early use of Antibiotics for at Risk CHildren with InfluEnza (ARCHIE): protocol for a double-blind, randomised, placebo-controlled trial.

INTRODUCTION: Influenza and influenza-like illness (ILI) create considerable burden on healthcare resources each winter. Children with pre-existing conditions such as asthma, diabetes mellitus and cerebral palsy are among those at greatest risk of clinical deterioration from influenza/ILI. The Antibiotics for at Risk CHildren with InfluEnza (ARCHIE) trial aims to determine whether early oral treatment with the antibiotic co-amoxiclav reduces the likelihood of reconsultation due to clinical deterioration in these 'at risk' children. METHODS AND ANALYSIS: The ARCHIE trial is a double-blind, parallel, randomised, placebo-controlled trial. 'At risk' children aged 6 months to 12 years inclusive who present within the first 5 days of an ILI episode will be randomised to receive a 5-day course of oral co-amoxiclav 400/57 twice daily or placebo. Randomisation will use a non-deterministic minimisation algorithm to balance age and seasonal influenza vaccination status.To detect respiratory virus infections, a nasal swab will be obtained from each participant before commencing study medication. To identify carriage of potential bacterial respiratory pathogens, we will also obtain a throat swab where possible.The primary outcome is reconsultation in any healthcare setting due to clinical deterioration within 28 days of randomisation. We will analyse this outcome using log-binomial regression model adjusted for region, age and seasonal influenza vaccination status.Secondary outcomes include duration of fever, duration of symptoms and adverse events. Continuous outcomes will be compared using regression analysis (or equivalent non-parametric method for non-normal data) adjusting for minimisation variables. Binary outcomes will be compared using χ2/Fisher's exact test and log-binomial regression. ETHICS: The ARCHIE trial has been reviewed and approved by the North West-Liverpool East Research Ethics Committee, Health Research Authority and Medicines and Healthcare Products Regulatory Agency. Our findings will be published in peer-reviewed journals and disseminated via our study website (www.archiestudy.com) and links with relevant charities. TRIAL REGISTRATION NUMBERS: ISRCTN 70714783; Pre-results. EudraCT 2013-002822-21; Pre-results.

Development of processes allowing near real-time refinement and validation of triage tools during the early stage of an outbreak in readiness for surge: the FLU-CATs Study.

BACKGROUND: During pandemics of novel influenza and outbreaks of emerging infections, surge in health-care demand can exceed capacity to provide normal standards of care. In such exceptional circumstances, triage tools may aid decisions in identifying people who are most likely to benefit from higher levels of care. Rapid research during the early phase of an outbreak should allow refinement and validation of triage tools so that in the event of surge a valid tool is available. The overarching study aim is to conduct a prospective near real-time analysis of structured clinical assessments of influenza-like illness (ILI) using primary care electronic health records (EHRs) during a pandemic. This abstract summarises the preparatory work, infrastructure development, user testing and proof-of-concept study. OBJECTIVES: (1) In preparation for conducting rapid research in the early phase of a future outbreak, to develop processes that allow near real-time analysis of general practitioner (GP) assessments of people presenting with ILI, management decisions and patient outcomes. (2) As proof of concept: conduct a pilot study evaluating the performance of the triage tools 'Community Assessment Tools' and 'Pandemic Medical Early Warning Score' to predict hospital admission and death in patients presenting with ILI to GPs during inter-pandemic winter seasons. DESIGN: Prospective near real-time analysis of structured clinical assessments and anonymised linkage to data from EHRs. User experience was evaluated by semistructured interviews with participating GPs. SETTING: Thirty GPs in England, Wales and Scotland, participating in the Clinical Practice Research Datalink. PARTICIPANTS: All people presenting with ILI. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Study outcome is proof of concept through demonstration of data capture and near real-time analysis. Primary patient outcomes were hospital admission within 24 hours and death (all causes) within 30 days of GP assessment. Secondary patient outcomes included GP decision to prescribe antibiotics and/or influenza-specific antiviral drugs and/or refer to hospital - if admitted, the need for higher levels of care and length of hospital stay. DATA SOURCES: Linked anonymised data from a web-based structured clinical assessment and primary care EHRs. RESULTS: In the 24 months to April 2015, data from 704 adult and 159 child consultations by 30 GPs were captured. GPs referred 11 (1.6%) adults and six (3.8%) children to hospital. There were 13 (1.8%) deaths of adults and two (1.3%) of children. There were too few outcome events to draw any conclusions regarding the performance of the triage tools. GP interviews showed that although there were some difficulties with installation, the web-based data collection tool was quick and easy to use. Some GPs felt that a minimal monetary incentive would promote participation. CONCLUSIONS: We have developed processes that allow capture and near real-time automated analysis of GP's clinical assessments and management decisions of people presenting with ILI. FUTURE WORK: We will develop processes to include other EHR systems, attempt linkage to data on influenza surveillance and maintain processes in readiness for a future outbreak. STUDY REGISTRATION: This study is registered as ISRCTN87130712 and UK Clinical Research Network 12827. FUNDING: The National Institute for Health Research Health Technology Assessment programme. MGS is supported by the UK NIHR Health Protection Research Unit in Emerging and Zoonotic Infections.

An evaluation of community assessment tools (CATs) in predicting use of clinical interventions and severe outcomes during the A(H1N1)pdm09 pandemic.

During severe influenza pandemics healthcare demand can exceed clinical capacity to provide normal standards of care. Community Assessment Tools (CATs) could provide a framework for triage decisions for hospital referral and admission. CATs have been developed based on evidence that supports the recognition of severe influenza and pneumonia in the community (including resource limited settings) for adults, children and infants, and serious feverish illness in children. CATs use six objective criteria and one subjective criterion, any one or more of which should prompt urgent referral and admission to hospital. A retrospective evaluation of the ability of CATs to predict use of hospital-based interventions and patient outcomes in a pandemic was made using the first recorded routine clinical assessment on or shortly after admission from 1520 unselected patients (800 female, 480 children <16 years) admitted with PCR confirmed A(H1N1)pdm09 infection (the FLU-CIN cohort). Outcome measures included: any use of supplemental oxygen; mechanical ventilation; intravenous antibiotics; length of stay; intensive or high dependency care; death; and "severe outcome" (combined: use of intensive or high dependency care or death during admission). Unadjusted and multivariable analyses were conducted for children (age <16 years) and adults. Each CATs criterion independently identified both use of clinical interventions that would in normal circumstances only be provided in hospital and patient outcome measures. "Peripheral oxygen saturation ≤ 92% breathing air, or being on oxygen" performed well in predicting use of resources and outcomes for both adults and children; supporting routine measurement of peripheral oxygen saturation when assessing severity of disease. In multivariable analyses the single subjective criterion in CATs "other cause for clinical concern" independently predicted death in children and in adults predicted length of stay, mechanical ventilation and "severe outcome"; supporting the role of clinical acumen as an important independent predictor of serious illness.