Recovery trajectories and predictors of symptom resolution in post-COVID-19 condition: a population-based cohort study

Abstract

Background SARS-CoV-2 infection can lead to persistent symptoms, known as Post-COVID-19 Condition (PCC). Previous studies on PCC prognosis mainly looked at severe cases in rehabilitation settings and without knowledge about pre-infection symptom levels. Uncertainty remains about recovery trajectory in the general population, its predictors, and whether recovery differs by symptom. Methods We analysed data from Lifelines, a prospective population-based observational cohort. Adults completed 31 COVID-19 questionnaires between March 2020 and October 2022 providing longitudinal symptom data to assess PCC status, and recovery. PCC was defined as at least one moderately severe symptom, among 12 identified as PCC-specific, that worsened 90–150 days after infection. Cox-proportional hazard models estimated recovery, defined as symptom decline to an individual's pre-infection baseline, adjusted for symptoms present at PCC diagnosis, age, sex, BMI, smoking, hospitalization, vaccination, and comorbidities. Findings We analysed time series of 809 cases (mean age 55.0; [SD 11.0]; 590 [73%] female; mean follow up 368 days; [SD 200]). Symptom decline to pre-infection baseline or below was observed in 558 participants; the Kaplan–Meier 24-month symptom decline estimate was 92%. Greater symptom burden was associated with a lower likelihood of recovery (HR per additional symptom 0.69, 95% CI 0.63–0.76), whereas younger age had a higher likelihood of recovery compared with middle adulthood (HR 1.52, 95% CI 1.06–2.18). Median time to symptom decline was 226 days (IQR 182–372), with most improvement within the first 235 days before slowing and plateauing. Interpretation Most individuals with PCC recover, but older adults and those with multiple symptoms are at higher risk of prolonged illness, underscoring the need for ongoing support. Funding This work was supported by The Netherlands Organisation for Health Research and Development (ZonMw) COVID-19 Program. The data collection in this project is co-financed by EU Horizon Europe Program grant Long Covid.