Development of a symptom-based severity score anchored to health-related quality of life post-COVID-19 within the population-based EPILOC cohorts

Purpose

Because simple symptom counts treat all symptoms as equally important and may not adequately capture the HRQoL impact of heterogeneous post-COVID-19 symptoms, we aimed to develop an HRQoL-anchored symptom severity score providing an interpretable measure of post-COVID-19 disease burden.

Methods

Baseline data from the population-based EPILOC and EPILOC Omicron surveys (adults aged 18–65 years) were used to develop a symptom-based severity score anchored to physical and mental HRQoL assessed with the SF-12. A two-stage modelling approach was applied to identify HRQoL-relevant symptoms and to derive symptom-specific weights for physical and mental component scores, incorporating 30 ordinal symptom severity variables. Symptom-specific weights were extracted to compute physical, mental, and composite severity scores. Score interpretation was examined using external reference measures, including EPILOC case status, self-reported health recovery, and functional consequences.

Results

A total of 19,004 participants (mean age 44.3 years, 59.6% female) were included. Sixteen symptoms contributed to the physical and eleven to the mental HRQoL score, with a limited subset accounting for most of the HRQoL loss. Severity scores were heavily right-skewed, with 50.6% of participants showing no measurable HRQoL impairment. Higher scores correlated with lower self-reported recovery, and increased probability of rehabilitation use and health-related changes in working time, supporting convergent and criterion-related validity.

Conclusions

This study introduces a transparent, HRQoL-anchored symptom severity score that measures graded post-COVID-19 burden beyond simple symptom counts. The score may be particularly suited for longitudinal assessment of recovery trajectories.

Plain English summary

Many people report ongoing symptoms after a COVID-19 infection, but it is hard to explain how much these symptoms impact daily life and well-being. Simply counting symptoms is not effective because some are more severe or disruptive than others.

This study focuses on how to measure the overall effect of post-COVID symptoms on people’s quality of life in a clear and meaningful way. The goal was to develop a score that shows how strongly different symptoms are associated with limitations in physical and mental health.

Using data from over 19,000 participants, we connected symptom severity to well-established measures of physical and mental quality of life. We found that only a few symptoms had strongly impaired daily functioning, while many others had little or no measurable effect. The resulting score clearly differentiated individuals who had fully recovered from those with ongoing health issues.

Overall, this study demonstrates that a quality-of-life-based symptom score offers a clearer and more useful view of post-COVID health compared to simple symptom counts. Such a score can help researchers and healthcare providers better understand recovery and ongoing health needs after COVID-19.