Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic (preprint)

Objectives: To describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap. Design: Ten population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs). Setting: UK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database. Participants: Participants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people. Main outcome measures: In the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses. Results: The LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed. Conclusions: Multiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.

Risk of severe COVID-19 outcomes associated with immune-mediated inflammatory diseases and immune modifying therapies: a nationwide cohort study in the OpenSAFELY platform (preprint)

BackgroundIt is unclear if people with immune-mediated inflammatory diseases (IMIDs) (joint, bowel and skin) and on immune modifying therapy have increased risk of serious COVID-19 outcomes. MethodsWith the approval of NHS England we conducted a cohort study, using OpenSAFELY, analysing routinely-collected primary care data linked to hospital admission, death and previously unavailable hospital prescription data. We used Cox regression (adjusting for confounders) to estimate hazard ratios (HR) comparing risk of COVID-19-death, death/critical care admission, and hospitalisation (March to September 2020) in: 1) people with IMIDs compared to the general population; and 2) people with IMIDs on targeted immune modifying drugs (e.g., biologics) compared to standard systemic treatment (e.g., methotrexate). FindingsWe identified 17,672,065 adults; of 1,163,438 (7%) with IMIDs, 19,119 people received targeted immune modifying drugs, and 200,813 received standard systemics. We saw evidence of increased COVID-19-death (HR 1.23, 95%CI 1.20, 1.27), and COVID-19 hospitalisation (HR 1.32, 95%CI 1.29, 1.35) in individuals with IMIDs overall compared to individuals without IMIDs of the same age, sex, deprivation and smoking status. We saw no evidence of increased COVID-19 deaths with targeted compared to standard systemic treatments (HR 1.03, 95%CI 0.80, 1.33). There was no evidence of increased COVID-19-related death in those prescribed TNF inhibitors, IL-12/23, IL7, IL-6 or JAK inhibitors compared to standard systemics. Rituximab was associated with increased COVID-19 death (HR 1.68, 95%CI 1.11, 2.56); however, this finding may relate to confounding. InterpretationCOVID-19 death and hospitalisation was higher in people with IMIDs. We saw no increased risk of adverse COVID-19 outcomes in those on most targeted immune modifying drugs for IMIDs compared to standard systemics. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed on May 19th, 2021, using the terms "COVID-19", "SARS-CoV-2" and "rheumatoid arthritis", "psoriatic arthritis" "ankylosing spondylitis", "Crohns disease" "ulcerative colitis" "hidradenitis suppurativa" and "psoriasis", to identify primary research articles examining severe COVID-19 outcome risk in individuals with immune-mediated inflammatory diseases (IMIDs) and those on immune modifying therapy. The studies identified (including matched cohort studies and studies in disease-specific registries) were limited by small sample sizes and number of outcomes. Most studies did not show a signal of increased adverse COVID-19 outcomes in those on targeted therapies, with the exception of rituximab. Additionally, disease- specific registries are subject to selection bias and lack denominator populations. Added value of the studyIn our large population-based study of 17 million individuals, including 1 million people with IMIDs and just under 200,000 receiving immune modifying medications, we saw evidence that people with IMIDs had an increased risk of COVID-19-related death compared to the general population after adjusting for potential confounders (age, sex, deprivation, smoking status) (HR 1.23, 95%CI 1.20, 1.27). We saw differences by IMID type, with COVID-19-related death being increased by the most in people with inflammatory joint disease (HR 1.47, 95%CI 1.40, 1.54). We also saw some evidence that those with IMIDs were more likely, compared to the general population, to have COVID-19-related critical care admission/death (HR 1.24, 95%CI 1.21, 1.28) and hospitalisation (HR 1.32, 95%CI 1.29, 1.35). Compared to people with IMIDs taking standard systemics, we saw no evidence of differences in severe COVID-19-related outcomes with TNF inhibitors, IL-17 inhibitors, IL-12/23 inhibitors, IL-6 inhibitors and JAK inhibitors. However, there was some evidence that rituximab was associated with an increased risk of COVID-19-related death (HR 1.68, 95%CI 1.11, 2.56) and death/critical care admission (HR 1.92, 95%CI 1.31, 2.81). We also saw evidence of an increase in COVID-19-related hospital admissions in people prescribed rituximab (HR 1.59, 95%CI 1.16, 2.18) or JAK inhibition (HR 1.81, 95%CI 1.09, 3.01) compared to those on standard systemics, although this could be related to worse underlying health rather than the drugs themselves, and numbers of events were small. This is the first study to our knowledge to use high-cost drug data on medicines supplied by hospitals at a national scale in England (to identify targeted therapies). The availability of these data fills an important gap in the medication record of those with more specialist conditions treated by hospitals creating an important opportunity to generate insights to these conditions and these medications Implications of all of the available evidenceOur study offers insights into future risk mitigation strategies and SARS-CoV-2 vaccination priorities for individuals with IMIDs, as it highlights that those with IMIDs and those taking rituximab may be at risk of severe COVID-19 outcomes. Critically, our study does not show a link between most targeted immune modifying medications compared to standard systemics and severe COVID-19 outcomes. However, the increased risk of adverse COVID-19 outcomes that we saw in people with IMIDs and those treated with rituximab merits further study.

COVID-19 collateral: Indirect acute effects of the pandemic on physical and mental health in the UK (preprint)

Background: Concerns have been raised that the response to the UK COVID-19 pandemic may have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We asked what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic? Methods: Using electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (2017-2020), we calculated weekly primary care contacts for selected acute physical and mental health conditions (including: anxiety, depression, acute alcohol-related events, asthma and chronic obstructive pulmonary disease [COPD] exacerbations, cardiovascular and diabetic emergencies). We used interrupted time series (ITS) analysis to formally quantify changes in conditions after the introduction of population-wide restrictions ('lockdown') compared to the period prior to their introduction in March 2020. Findings: The overall population included 9,863,903 individuals on 1st January 2017. Primary care contacts for all conditions dropped dramatically after introduction of population-wide restrictions. By July 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. The largest reductions were for contacts for: diabetic emergencies (OR: 0.35, 95% CI: 0.25-0.50), depression (OR: 0.53, 95% CI: 0.52-0.53), and self-harm (OR: 0.56, 95% CI: 0.54-0.58). Interpretation: There were substantial reductions in primary care contacts for acute physical and mental conditions with restrictions, with limited recovery by July 2020. It is likely that much of the deficit in care represents unmet need, with implications for subsequent morbidity and premature mortality. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people experiencing the conditions and healthcare provision. Maintaining access must be a key priority in future public health planning (including further restrictions). Funding: Wellcome Trust Senior Fellowship (SML), Health Data Research UK.

UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records (preprint)

BackgroundThis study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom in 2019. MethodsWe used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to describe the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. FindingsOn 5 March 2019, 24{middle dot}4% of the UK population were at risk due to a record of at least one underlying health condition, including 8{middle dot}3% of school-aged children, 19{middle dot}6% of working-aged adults, and 66{middle dot}2% of individuals aged 70 years or more. 7{middle dot}1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1{middle dot}6% of the population had a new diagnosis of cancer in the past five years. InterpretationThe population at risk of severe COVID-19 (aged [≥]70 years, or with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. FundingNIHR HPRU in Immunisation Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Pubmed for peer-reviewed articles, preprints, and research reports on the size and distribution of the population at risk of severe COVID. We used the terms (1) risk factor or co-morbidity or similar (2) COVID or SARS or similar and (3) prevalence to search for studies aiming to quantify the COVID-19 at-risk UK population published in the previous year to 19 July 2020, with no language restrictions. We found one study which modelled prevalence of risk factors based on the Global Burden of Disease (which included the UK) and one study which estimated that 8.4 million individuals aged [≥]30 years in the UK were at risk based on prevalence of a subset of relevant conditions in England. There were no studies which described the complete COVID-19 at-risk population across the UK. Added value of this studyWe used a large, nationally-representative dataset based on electronic health records to estimate prevalence of increased risk of severe COVID-19 across the United Kingdom, including all conditions in national guidance. We stratified by age, sex and region to enable regionally-tailored prediction of COVID-19-related healthcare burden and interventions to reduce transmission of infection, and planning and modelling of vaccination of the at-risk population. We also quantified the value of linked secondary care records to supplement primary care records. Implications of all the available evidenceIndividuals at moderate or high risk of severe COVID-19 according to current national guidance (aged [≥]70 years, or with a specified underlying health condition) comprise 18{middle dot}5 million individuals in the United Kingdom, rather than the 8.43 million previously estimated. The 8{middle dot}3% of school-aged children and 19{middle dot}6% of working-aged adults considered at-risk according to national guidance emphasises the need to consider younger at-risk individuals in shielding policies and when re-opening schools and workplaces, but also supports prioritising vaccination based on age and condition-specific mortality risk, rather than targeting all individuals with underlying conditions, who form a large population even among younger age groups. Among individuals aged [≥]70 years, 66{middle dot}2% had at least one underlying health condition, suggesting an age-targeted approach to vaccination may efficiently target individuals at risk of severe COVID-19. These national estimates broadly support the use of Global Burden of Disease modelled estimates and age-targeted vaccination strategies in other countries.

COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis (preprint)

Objectives: Following detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and identify risk factors for infection of the first few hundred cases. Methods: Information was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and risk factors for infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. Findings: The majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. Conclusion: This study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study was able to characterize the risk factors for infection with population prevalence estimates setting these relative risks into a public health context. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.