Long-term health impacts of COVID-19 among 242,712 adults in England

Abstract

The COVID-19 pandemic is having a lasting impact on health and well-being. We compare current self-reported health, quality of life and symptom profiles for people with ongoing symptoms following COVID-19 to those who have never tested positive for SARS-CoV-2 infection and those who have recovered from COVID-19. Overall, 276,840/800,000 (34·6%) of invited participants took part. Mental health and health-related quality of life were worse among participants with ongoing persistent symptoms post-COVID compared with those who had never had COVID-19 or had recovered. In this study, median duration of COVID-related symptoms (N = 130,251) was 1·3 weeks (inter-quartile range 6 days to 2 weeks), with 7·5% and 5·2% reporting ongoing symptoms ≥12 weeks and ≥52 weeks respectively. Female sex, ≥1 comorbidity and being infected when Wild-type variant was dominant were associated with higher probability of symptoms lasting ≥12 weeks and longer recovery time in those with persistent symptoms. Although COVID-19 is usually of short duration, some adults experience persistent and burdensome illness.

Fig. 1. Kaplan–Meier survival curve of time to symptom end date in those self-reporting symptomatic SARS-CoV-2 infection, overall and by dominant variant at the time of infection.

The curve shows the probability that a participant continues to have symptoms beyond time t. Participants infected at a time when Wild-type (blue) was dominant had a higher probability of symptoms continuing beyond time t compared to Alpha (red), Delta (grey) and Omicron (orange). The number at risk table below the curve shows, overall and by dominant variant at the time of infection, the number at risk at any specific time point. This is equal to the total number of participants remaining in the study including any individuals who experience the event of interest (symptom end date) or participants who are censored at this time point. The unit of time is “weeks,” so the number at risk is those participants who have not yet experienced the event of interest or been censored at the beginning of the week (before any event or censoring could occur). The number of participants who recovered within the previous time window are shown below the number at risk table. This is equal to the total number of participants with a symptom end date within the time window ending at this time point.

Fig. 2

Factors associated with persistent symptoms following COVID-19 lasting i) ≥12 weeks and ii) ≥52 weeks versus those who reported being asymptomatic or symptoms resolved within 4 weeks. Logistic regression models with one or more COVID-19 symptoms lasting ≥12 weeks (y/n) or ≥52 weeks (y/n) as the binary outcome variables. Modelling of persistent symptoms as a function of biological and demographic variables. In the forest plot, data were presented as adjusted odds ratios (central dot) and 95% confidence intervals (bars). Adjusted odds ratios compare participants with persistent symptoms lasting i) ≥12 weeks (black) or ii) ≥52 weeks (blue) with those who reported being asymptomatic or symptoms resolved within 4 weeks (n = 126,016 participants for ≥12 weeks analysis / n = 121,142 participants for ≥52 weeks analysis). Mutually adjusted for age, sex, ethnicity, IMD, comorbidities, smoking status, severity of initial infection, dominant variant at the time of infection, and vaccination status. Data used: Supplementary Table 2.

Fig. 3

Current symptoms profile by COVID-19 history a) Forest plot of current symptoms in those reporting ongoing persistent symptoms following COVID-19 versus all other respondents, and b) Prevalence of current symptoms by COVID-19 history. Panel a shows the results of logistic regression models with 29 individual symptoms currently experienced (y/n) as the binary outcome variable and COVID-19 history as the primary exposure variable of interest (n = 242,712 participants). In the forest plot, data were presented as adjusted odds ratios (central dot) and 95% confidence intervals (bars). Odds ratios adjusted for age, sex, ethnicity, IMD, comorbidities, smoking status. Panel b shows the prevalence of 29 symptoms surveyed (n = 242,712 participants). Unweighted survey data presented. Data used: Supplementary Tables 5, 6.