Estimating Impact of SARS-CoV-2 Infection on Health-Related Quality of Life among Persons Aged 8 years and Older, August 2020-July 2022
Bibliographic record
Abstract
Abstract Background Severe COVID-19 results in substantial economic burden and impacts quality of life. Assessing how non-hospitalized COVID-19 impacts health utilities during acute infection and long term is important to estimate the full economic impact of SARS-CoV-2 infection. Methods We analyzed EQ-5D-3L survey data from SARS-CoV-2 infected adults (aged ≥16 years) and children (aged 8-15 years) from three community and household cohorts in the United States (2020-2022). EQ-5D-3L scores were analyzed at three time points after symptom onset or first positive SARS-CoV-2 test result and converted to health utilities on a scale of 0-1 (1=perfect health). Among adults, regression models were used to compare differences in health utility by demographic/clinical characteristics. Results Among 538 SARS-CoV-2 non-hospitalized asymptomatic/symptomatic infections from 575 adults with EQ-5D-3L surveys, mean utilities were near 1 throughout the observation period. During 0-14 days, vaccinated participants had higher health utilities (Beta:0.57, 95% CI:0.07,1.07). Seeking medical care and having gastrointestinal symptoms (vs. none), were associated with lower health utilities (Beta, 95% CI:-0.96, −1.60, −0.31; and −0.76, −1.30, −0.21 respectively). During 15-30 days, unemployment was associated with lower health utility (Beta:-0.64, 95% CI:-1.15,-0.14). During 31-90 days, underlying conditions were associated with lower health utilities (Beta:-0.32, 95% CI:-0.54, −0.09). Results for children were similar to adults. Conclusion Non-hospitalized COVID-19 may have minimal overall impact on quality of life; however, health utilities differed by vaccination status, presence of gastrointestinal symptoms, employment status, and presence of underlying conditions. Vaccination may play an important role in minimizing illness impact from SARS-CoV-2 infection. Key points Severe COVID-19 illness causes substantial economic burden and impacts on quality of life; however, the incidence of non-hospitalized COVID-19 is far greater. Assessing how non-hospitalized COVID-19 impacts health during acute infection and long term is important to understand the full impact of SARS-CoV-2 infection. This study utilizes the EQ-5D-3L, a standardized generic preference-based instrument used in population health studies, to estimate health utilities at multiple time points following SARS-CoV-2 infection. The study also examines demographic/medical characteristics that are associated with health utility over time. While mean health utilities were high for all infection periods regardless of age, health utility was lower at varying time points post-infection among adults who sought medical care, reported gastrointestinal symptoms, were unemployed, and with underlying conditions. Vaccinated adults (vs. unvaccinated) had higher health utility and were less likely to report reduced health. Findings can be used as inputs for economic evaluation and assessing impact of interventions for non-hospitalized SARS-CoV-2 illness, such as vaccination.
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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 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".