Long COVID risk and severity after COVID-19 infections and reinfections in Quebec healthcare workers
Bibliographic record
Abstract
ABSTRACT Importance Long COVID, a chronic condition following SARS-CoV-2 infection, affects millions of people worldwide and can lead to significant functional impairment. Estimates of long COVID risk after a first COVID-19 infection vary, and data on risk following reinfections remain lacking. Objective To estimate and compare long COVID risk and severity with first COVID-19 infection versus reinfections among healthcare workers (HCWs). Design Retrospective cohort study based on an electronic survey among Quebec HCWs conducted between May 16 and June 15, 2023. A short telephone survey among randomly selected non-respondents further assessed potential response bias. Setting Population-based study in Quebec, Canada. Participants 397 222 HCWs were invited to participate in the electronic survey and 10 500 in the telephone survey. Main outcomes and measures We defined long COVID cases as HCWs self-reporting COVID-19-attributed symptoms lasting ≥12 weeks, classified as mild, moderate, or severe based on perceived symptom intensity. We compared self-reported symptoms and functional limitations of cases to COVID controls (infected participants without long COVID) and non-COVID controls (uninfected participants). Risk and prevalence were estimated by number of infections, likely infecting variant and perceived acute COVID-19 severity. We conducted symptom clustering analyses using unsupervised learning techniques. Results Estimated long COVID risk following any COVID-19 infection was similar among 22 496 online survey participants (17.0% [95%CI, 16.3%–17.6%] and 3 978 telephone survey participants (15.9% [14.6%–17.2%]. The cumulative risk increased with the number of infections, but reinfections were associated with three times lower risk of long COVID than first infections. Pre-Omicron infections and severe acute COVID-19 episodes correlated with higher long COVID risk and severity. Among prevalent long COVID cases, 43% were moderate and 33% severe. Compared to controls, dyspnea, neurocognitive symptoms, post-exertional malaise and smell/taste disturbances were most strongly associated with long COVID. Cluster analysis identified seven symptom groups with systemic, neurocognitive, pulmonary, and mood-related clusters being the most prevalent. Severe long COVID cases exhibited multiple symptom clusters and greater functional limitations. Conclusions Long COVID is a common and disabling condition among HCWs. Societal and healthcare burden remains important and will continue to accrue given ongoing SARS-CoV-2 transmission and long COVID risk with reinfections. KEY POINTS Question Does the risk and severity of long COVID differ for first COVID-19 infections versus reinfections among healthcare workers in Quebec, Canada? Findings The risk of long COVID was ∼15% with first COVID-19 infection, but three-fold lower with reinfections. Risk was higher with COVID-19 infections due to ancestral strains and with more severe acute episodes. Long COVID risk and severity compromised self-rated health, physical capacity and cognitive function. Meaning Long COVID is a common and disabling condition among workers. Societal and healthcare burden remains important and will continue to accrue given ongoing SARS-CoV-2 transmission and long COVID risk with reinfections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".