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ObjectiveTo quantify occupational risks of COVID-19 among healthcare staff during the first wave (9 March 2020–31 July 2020) of the pandemic in England.MethodsWe used pseudonymised data on 902 813 individuals employed by 191 National Health Service trusts to explore demographic and occupational risk factors for sickness absence ascribed to COVID-19 (n=92 880). We estimated 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’ (care assistants and other occupations directly supporting those in clinical roles) (OR 2.31 (2.25 to 2.37)), registered nursing and midwifery professionals (OR 2.28 (2.23 to 2.34)) and allied health professionals (OR 1.94 (1.88 to 2.01)) and intermediate in doctors and dentists (OR 1.55 (1.50 to 1.61)). Differences in risk were higher after the employing trust had started to care for documented patients with COVID-19, 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.Trial registration numberISRCTN36352994.

Introduction The importance of elucidating the relationships between pain, mood and quality of life (QoL) amongst people with amyotrophic lateral sclerosis/motor neuron disease is evident to clinicians, yet the literature is limited and inconsistent. We explored the relationships between pain, depression, anxiety and QoL to reconcile the previous contrasting findings and inform future research and clinical practice. Methods Patient-reported outcomes were obtained as part of the Trajectories of Outcomes in Neurological Conditions study. Mood and QoL scales underwent Rasch analysis. Correlation coefficients examined the strength of association between variables of interest. A bivariate regression model was developed to examine the effects of pain, depression and anxiety on joint psychological and physical QoL domains. Results Of 636 people with ALS, 69% reported pain, of these most had mild pain. Seven percent (7%) of participants exceeded published cutoffs for probable depression and 14% had probable anxiety. Pain, depression and anxiety all influence quality of life; depression has a significant effect on both physical and psychological domains of QoL, whereas pain affects physical QoL and anxiety psychological QoL. Conclusions These results show the importance of expressing quality of life in a conceptually appropriate way, as failing to take account of the multidimensional nature of QoL can result in important nuances being overlooked. Clinicians must be aware that pain, depression and anxiety all worsen QoL across their ranges, and not just when pain is severe or when anxiety or depression reach case level.

BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key data gap is the absence of data on uptake by occupation. This study investigates differences in vaccination rates by occupation in England, using nationwide population-level data.MethodsWe calculated the proportion of people who had received three COVID-19 vaccinations (assessed on 28 February 2022) by detailed occupational categories in adults aged 18–64 and estimated adjusted ORs to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.ResultsOur study population included 15 456 651 adults aged 18–64 years. Vaccination rates differed markedly by occupation, being higher in health professionals (84.7%) and teaching and other educational professionals (83.6%) and lowest in people working in elementary trades and related occupations (57.6%). We found substantial differences in vaccination rates looking at finer occupational groups. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were associated with ability to work from home, the rate being higher in occupations which can be done from home. Many occupations with low vaccination rates also involved contact with the public or with vulnerable peopleConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection. Efforts should be made to increase vaccination rates in occupations that cannot be done from home and involve contact with the public.

Introduction This cross-sectional study looked at the impact of the SARS-CoV-2/COVID-19 pandemic on pediatric emergency department (PED) attendances and admissions (as a proxy for severity of illness) in the United States and United Kingdom. Methods Data were extracted for children and adolescents, younger than 16 years, attending Royal Manchester Children's Hospital (RMCH, United Kingdom), and Yale New Haven Children's Hospital (YNHCH, United States). Attendances for weeks 1 to 20 of 2020 and 2019 were compared, and likelihood of admission was assessed via calculation of odds ratios, using week 13 (lockdown) as a cutoff. Results Attendance numbers for each PED decreased in 2020 compared with 2019 (RMCH, 29.2%; YNHCH, 24.8%). Odds of admission were significantly higher after lockdown than in 2019—RMCH (odds ratio, 1.26; 95% confidence interval, 1.08–1.46) and YNHCH (odds ratio, 1.60; 95% confidence interval, 1.31–1.98). Conclusions Although the absolute numbers of children and adolescents attending the PED and being admitted decreased after lockdown, the acuity of illness of those attending appears to be higher.

IntroductionThe Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics.MethodsWe used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network.ResultsOf the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics.ConclusionsThis medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.

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 dataset.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.

The Chief Medical Officer recommends that all health care workers receive an influenza vaccination annually. High vaccination coverage is believed to be the best protection against the spread of influenza within a hospital, although uptake by health care workers remains low. We conducted semistructured interviews with seven medical students and nine early career doctors, to explore the factors informing their influenza vaccination decision making. Data collection and analysis took place iteratively, until theoretical saturation was achieved, and a thematic analysis was performed. Socialization was important although its effects were attenuated by participants’ previous experiences and a lack of clarity around the risks and benefits of vaccination. Many participants did not have strong intentions regarding vaccination. There was considerable disparity between an individual’s opinion of the vaccine, their intentions, and their vaccination status. The indifference demonstrated here suggests few are strongly opposed to the vaccination—there is potential to increase vaccination coverage.