IMPACT OF COVID-19 PANDEMIC ON SICKNESS ABSENCE FOR MENTAL ILL HEALTH IN NATIONAL HEALTH SERVICE STAFF

ObjectiveTo explore the patterns of sickness absence in National Health Service (NHS) staff attributable to mental ill health during the first wave of the Covid-19 epidemic in March - July 2020 DesignCase-referent analysis of a secondary data set SettingNHS Trusts in England ParticipantsPseudonymised data on 959,356 employees who were continuously employed by NHS trusts during 1 January 2019 to 31 July 2020 Main Outcome MeasuresTrends in the burden of sickness absence due to mental ill health from 2019 to 2020 according to demographic, regional and occupational characteristics. ResultsOver the study period, 164,202 new sickness absence episodes for mental ill health were recorded in 12.5% (119,525) of the study sample. There was a spike of sickness absence for mental ill health in March-April 2020 (899,730 days lost) compared with 519,807 days in March-April 2019; the surge was driven by an increase in new episodes of long-term absence and had diminished by May/June 2020. The increase was greatest in those aged >60 years (227%) and among employees of Asian and Black ethnic origin (109%-136%). Among doctors and dentists the number of days absent declined by 12.7%. The biggest increase was in London (122%) and the smallest in the East Midlands (43.7%); the variation between regions reflected the rates of Covid-19 sickness absence during the same period. ConclusionAlthough the Covid-19 epidemic led to an increase in sickness absence attributed to mental ill health in NHS staff, this had substantially declined by May/June 2020, corresponding with the decrease in pressures at work as the first wave of the epidemic subsided. Article SummaryStrengths and limitations of this study O_LILarge study population C_LIO_LIStudy population were not self-selected C_LIO_LIJob exposure matrix allowed adjustment for occupational exposure C_LIO_LIData did not extend to the start of the second wave in September 2020 C_LI

Occupational risks of COVID-19 in NHS workers in England

ObjectiveTo quantify occupational risks of Covid-19 among healthcare staff during the first wave of the pandemic in England MethodsUsing pseudonymised data on 902,813 individuals continuously employed by 191 National Health Service trusts during 1.1.19 to 31.7.20, we explored demographic and occupational risk factors for sickness absence ascribed to Covid-19 during 9.3.20 to 31.7.20 (n = 92,880). We estimated odds ratios (ORs) by multivariable logistic regression. ResultsWith adjustment for employing trust, demographic characteristics, and previous frequency of sickness absence, risk relative to administrative/clerical occupations was highest in additional clinical services (including care assistants) (OR 2.31 [2.25-2.37]), registered nursing and midwifery professionals (OR 2.28 [2.23-2.34]) and allied health professionals (OR 1.94 [1.88-2.01]), and intermediate in doctors and dentists (OR 1.55 [1.50-1.61]). Differences in risk were higher after the employing trust had started to care for documented Covid-19 patients, and were reduced, but not eliminated, following additional adjustment for exposure to infected patients or materials, assessed by a job-exposure matrix. For prolonged Covid-19 sickness absence (episodes lasting >14 days), the variation in risk by staff group was somewhat greater. ConclusionsAfter allowance for possible bias and confounding by non-occupational exposures, we estimated that relative risks for Covid-19 among most patient-facing occupations were between 1.5 and 2.5. The highest risks were in those working in additional clinical services, nursing and midwifery and in allied health professions. Better protective measures for these staff groups should be a priority. Covid-19 may meet criteria for compensation as an occupational disease in some healthcare occupations. Key messagesO_LIWhat is already known about this subject? Healthcare workers and other keyworkers (workers whose job was considered essential to societal functioning) had a higher likelihood of testing positive for COVID-19 than other workers during the first lockdown in England. Amongst healthcare workers, those working in inpatient settings had the highest rate of infection. C_LIO_LIWhat are the new findings? Between March and July 2000, the overall risk of COVID-19 sickness absence in National Health Service staff in England was lower at older ages, higher in non-white staff, and (in comparison with administrative and clerical staff) more than doubled in registered nurses and among workers such as healthcare assistants providing support to health professionals. Risk in health care scientists was little different from that in administrative and clerical occupations C_LIO_LIHow might this impact on policy or clinical practice in the foreseeable future? Our results suggest that the risk reduction strategies that were in place for healthcare scientists were effective. However, the protection for nursing and supporting health professionals was insufficient. In the event of a further wave of infections resulting in high hospital admissions, attention should be paid to ensuring that risk reduction strategies for nurses and supporting health professionals are improved. C_LI

Changing patterns of sickness absence among healthcare workers in England during the COVID-19 pandemic.

ObjectiveTo explore impacts of the COVID-19 pandemic on patterns of sickness absence among staff employed by the National Health Service (NHS) in England. MethodsWe analysed prospectively collected, pseudonymised data on 959,356 employees who were continuously employed by NHS trusts during 1 January 2019 to 31 July 2020, comparing the frequency of new sickness absence in 2020 with that at corresponding times in 2019. ResultsAfter exclusion of episodes directly related to COVID-19, the overall incidence of sickness absence during the initial 10 weeks of the pandemic (March-May 2020) was more than 20% lower than in corresponding weeks of 2019, but trends for specific categories of illness varied. Marked increases were observed for asthma (122%), infectious diseases (283%) and mental illness (42.3%), while reductions were apparent for gastrointestinal problems (48.4%), genitourinary/gynaecological disorders (33.8%), eye problems (42.7%), injury and fracture (27.7%), back problems (19.6%), other musculoskeletal disorders (29.3%), disorders of ear, nose and throat (32.7%), cough/flu (24.5%) and cancer (24.1%). A doubling of new absences for pregnancy-related disorders during 18 May to 19 July of 2020 was limited to women with earlier COVID-19 sickness absence. ConclusionsVarious factors will have contributed to the large and divergent changes that were observed. The findings add to concerns regarding delays in diagnosis and treatment of cancers, and support a need to plan for a large backlog of treatment for many other diseases. Further research should explore the rise in absence for pregnancy-related disorders among women with earlier COVID-19 sickness absence. O_TEXTBOX1. What is already known about this subject? Historically, rates of sickness absence among the NHS workforce in England have been relatively high but stable. Reports of a marked increase during the first wave of the COVID-19 pandemic have not distinguished between different categories of underlying illness. 2. What are the new findings? During the first wave of COVID-19, incidence of sickness-absence changed markedly when compared to the previous year, with major increases for some categories of illness, and large declines for many others, including cancer. 3. How might this impact on policy or clinical practice in the foreseeable future? The findings support a need to plan for effects from delayed diagnosis and treatment of cancer, and to manage a large backlog of treatment for many other diseases. C_TEXTBOX

Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population

IntroductionNovel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. Methods and analysisWe will use a prospective open cohort study of routinely collected data from 1205 general practices in England in the QResearch database. The primary outcome is COVID-19 mortality (in or out-of-hospital) defined as confirmed or suspected COVID-19 mentioned on the death certificate, or death occurring in a person with SARS-CoV-2 infection between 24th January and 30th April 2020. Our primary outcome in adults is COVID-19 mortality (including out of hospital and in hospital deaths). We will also examine COVID-19 hospitalisation in children. Time-to-event models will be developed in the training data to derive separate risk equations in adults (19-100 years) for males and females for evaluation of risk of each outcome within the 3-month follow-up period (24th January to 30th April 2020), accounting for competing risks. Predictors considered will include age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, pre-existing medical co-morbidities, and concurrent medication. Measures of performance (prediction errors, calibration and discrimination) will be determined in the test data for men and women separately and by ten-year age group. For children, descriptive statistics will be undertaken if there are currently too few serious events to allow development of a risk model. The final model will be externally evaluated in (a) geographically separate practices and (b) other relevant datasets as they become available. Ethics and disseminationThe project has ethical approval and the results will be submitted for publication in a peer-reviewed journal. Strengths and limitations of the studyO_LIThe individual-level linkage of general practice, Public Health England testing, Hospital Episode Statistics and Office of National Statistics death register datasets enable a robust and accurate ascertainment of outcomes C_LIO_LIThe models will be trained and evaluated in population-representative datasets of millions of individuals C_LIO_LIShielding for clinically extremely vulnerable was advised and in place during the study period, therefore risk predictions influenced by the presence of some shielding conditions may require careful consideration C_LI

ASSESSMENT OF WORKERS PERSONAL VULNERABILITY TO COVID-19 USING COVID-AGE

Decisions on fitness for employment that entails a risk of contracting Covid-19 require an assessment of the workers personal vulnerability should infection occur. Using recently published UK data, we have developed a risk model that provides estimates of personal vulnerability to Covid-19 according to sex, age, ethnicity, and various comorbidities. Vulnerability from each risk factor is quantified in terms of its equivalence to added years of age. Addition of the impact from each risk factor to an individuals true age generates their "Covid-age", a summary measure representing the age of a healthy UK white male with equivalent vulnerability. We discuss important limitations of the model, including current scientific uncertainties and limitations on generalisability beyond the UK setting and its use beyond informing assessments of individual vulnerability in the workplace. As new evidence becomes available, some of these limitations can be addressed. The model does not remove the need for clinical judgement or for other important considerations when managing occupational risks from Covid-19.