Considerable concerns exist about persistent and debilitating symptoms experienced by people who have had COVID-19 infection, often referred to as 'long-COVID'.(1) However, population-based data remain rare, with the majority of COVID-19 research focused on severe adverse physical consequences of acute disease. There is growing evidence that a substantial number of people experience persisting symptoms such as fatigue and chest pain months after infection. (2) While the mental health consequences of societal changes during the pandemic (including lockdown) have been studied, (3, 4) the impact of COVID-19 infection on mental health and the role of psychiatric symptoms in long-COVID remain unclear.
Research from previous coronavirus outbreaks demonstrates potential for psychiatric consequences of infection. (5) An initial study using administrative data from the US demonstrates a COVID-19 diagnosis was associated with an increased incidence of psychiatric diagnoses (particularly anxiety and insomnia) in the following 14 to 90 days. (6) However, electronic health records may not capture more minor initial COVID-19 symptoms and people with less severe psychological problems that do not present to health services. Changes in healthcare seeking and treatment may lead to substantial potential bias in the context of a pandemic, where disruptions to health systems have been widespread. Data from surveys may therefore be better placed to capture impacts on mental health and need for intervention. To explore the relationship between COVID-19 infection and mental health in the UK context, we assessed associations between experiencing COVID-19 symptoms and changes in psychological distress in a representative longitudinal survey of adults.
The UK Household Longitudinal Study (also referred to as Understanding Society) is a nationally representative longitudinal household panel survey, based on a clustered stratified probability sample of UK households, described in detail previously.(7) All adults (aged 16+ years) in chosen households are invited to participate. Data collection for each wave usually takes place over 24 months, with participants re-interviewed every year by online, face-toface or telephone survey. We used pre-pandemic data from wave 9 (2017-19), which achieved a household response rate of over 80%. (7, 8) In response to the COVID-19 pandemic, additional waves of data were collected via online survey during April (24 th to 30 th April), May (27 th May to 2 nd June), June (25 th to 1 st July) and July (24 th to 31 st July).(9) The response rate for the first COVID wave was 48.6% of those who took part at wave 9. (10) . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint
The copyright holder for this this version posted November 28, 2020. ; https://doi.org/10.1101/2020.11.24.20237909 doi: medRxiv preprint Psychological distress was measured at each wave (pre-pandemic in 2017-19 and during the pandemic in April, May, June and July 2020) via the General Health Questionnaire 12 item instrument (GHQ-12). GHQ-12 assesses psychological distress and respondents reporting a score of four or more are likely experiencing symptoms to a clinically significant level.(3) Self-reported symptoms of cough, fever and anosmia allowed identification of individuals with probable COVID-19 infection in April 2020 (Supplementary Material). Of 28 people reporting hospitalisation for COVID-19 in April 2020, 23 were classified as probable COVID-19 according to our definition. We assessed associations between probable COVID-19 infection and psychological distress at one, two and three months later using logistic regression, with models adjusted to account for pre-pandemic psychological distress (GHQ score) and other covariates (gender, age, ethnicity and longstanding illness or disability). We also conducted subgroup analyses by age group (under 45, 45-64, 65+ years) and gender (men, women). Analyses used inverse probability weights to adjust for non-response and standard errors were adjusted for the complex survey design. Statistical analyses were performed in Stata/MP 15.1.
The University of Essex Ethics Committee approved all data collection for the Understanding Society main survey and COVID waves, which were performed in accordance with the Declaration of Helsinki. All survey participants provided fully informed consent. No additional ethical approval was necessary for this secondary data analysis.
The characteristics of participants are described in Supplementary Table S1. In total, 9.0% experienced probable COVID-19 symptoms in April 2020 (N=12,561). Psychological distress was more prevalent in May (27.5%), but reduced over time to 21.0% in July. In comparison to participants without probable COVID-19 infection, psychological distress was more common at one (OR 1.40, 95% CI 1.10-1.76), two (OR 1.41, 95% CI 1.08-1.86), and three (OR 1.31, 95% CI 0.99-1.73) months after reporting COVID-19 symptoms during April 2020 in May, June and July, respectively in adjusted analyses (Table 1, Supplementary Table S2-S4) . Subgroup analyses demonstrated greater associations in men (OR=1.54 in May, 95% CI: 1.04-2.29) and younger adults (OR=1.50 in May, 95% CI: 1.02-2.20). Overall, women, younger age groups and those with a limiting illness or disability also had consistently higher levels of psychological distress across the first few months of the pandemic.
Our study suggests that COVID-19 infection could lead to an increase in clinically significant psychological distress which persists months after infection and is additional to the mental health impacts of societal changes during the pandemic. Younger people and men with probable COVID-19 infection were more likely to report clinical levels of psychological distress compared to older age groups and women. Study strengths include the longitudinal data over multiple points of follow-up during the pandemic, representative study population and accounting for pre-pandemic mental health to limit reverse causation. An important limitation is the ascertainment of COVID-19 infection which was based on self-report and the classification of probable COVID-19 infection at only one time point. However, misclassification may be more likely to result in under-estimation of any underlying association. Further research based on confirmed infection is required and that takes into account any change in the symptoms of long-COVID. Triangulation of survey and . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted November 28, 2020. ; https://doi.org/10.1101/2020.11.24.20237909 doi: medRxiv preprint administrative data (e.g. primary care and psychotropic prescribing records) would also be helpful to disentangle the discrepancy between likely clinical need and service use.
The potential adverse impacts of COVID-19 infection on mental health reinforces the benefits of minimising COVID-19 infection among the general population, not only in those at greatest risk of mortality. When considered alongside the mental health impacts generated by mitigation measures, there is potential for a high demand for mental health services resulting from the pandemic. Further research to examine the longer-term psychological sequelae of COVID-19 infection is urgently required.
. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint
The copyright holder for this this version posted November 28, 2020. ; https://doi.org/10.1101/2020.11.24.20237909 doi: medRxiv preprint Results for May 2020 include people who participated in Wave 9, COVID Wave A (April 2020) and B (May 2020)
Results for June 2020 include people who participated in Wave 9, COVID Wave A (April 2020) and C (June 2020)
Results for July 2020 include people who participated in Wave 9, COVID Wave A (April 2020) and D (July 2020)
. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint
The copyright holder for this this version posted November 28, 2020. ; https://doi.org/10.1101/2020.11.24.20237909 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint
The copyright holder for this this version posted November 28, 2020. ; https://doi.org/10.1101/2020.11.24.20237909 doi: medRxiv preprint
SVK and CLN conceived the idea for the study. CLN and SVK led the study design, with input from AHL. CLN and SVK conducted the analysis, with assistance from KH. SVK and CLN drafted the paper, with all authors critically revising the manuscript.
We received the following funding: The National Core Studies Health & Wellbeing initiative was funded by the Medical Research Council (MC_PC_20030). AHL and SVK acknowledge funding from the Medical Research Council (MC_UU_12017/13) and Scottish Government Chief Scientist Office (SPHSU13). CLN acknowledges funding from a Medical Research Council Fellowship (MR/R024774/1) and SVK acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02). MB acknowledges funding from the Economic and Social Research Council (ES/N00812X/1). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.
SVK is a member of the UK Government's Scientific Advisory Group on Emergencies (SAGE) subgroup on ethnicity and COVID-19. SVK is co-chair of the Scottish Government's Expert Reference Group on ethnicity and COVID-19. MB is director of the Understanding Society Study. All authors write in an independent capacity and the views expressed do not necessarily represent any government or funding organisation.
Understanding Society deidentified survey participant data are available through the UK Data Service (http://doi.org/10.5255/UKDA-SN-6614-13; http://doi.org/10.5255/UKDA-SN-8644-4). Researchers who would like to use Understanding Society need to register with the UK Data Service (https://ukdataservice.ac.uk/) before being allowed to download datasets.