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Identifying potential post-COVID-19 condition among people experiencing homelessness using longitudinal symptom
Lucie Richard1, Rosane Nisenbaum2, Allison Dyer3
1MAP Centre for Urban Health Solutions, Unity Health Toronto, 30 Bond St., Toronto, Ontario, Canada, M5B 1W8.
Public Health
|January 18, 2026
Summary
Self-reported symptoms are unreliable for identifying post-COVID-19 condition (PCC) in people experiencing homelessness. High baseline symptom rates and asymptomatic infections make symptom tracking ineffective for diagnosing PCC in this vulnerable population.
Area of Science:
- Public Health
- Infectious Diseases
- Symptomology
Background:
- People experiencing homelessness face a high burden of SARS-CoV-2 infection and reinfection.
- Identifying post-COVID-19 condition (PCC) is challenging in this population due to high baseline symptom rates.
Purpose of the Study:
- To evaluate the utility of longitudinal symptom patterns in identifying potential PCC among individuals experiencing homelessness.
- To assess the effectiveness of symptom-based approaches for PCC identification in a vulnerable population.
Main Methods:
- Prospective cohort study of 736 individuals experiencing homelessness in Toronto, Canada.
- Longitudinal assessment of twelve self-reported symptoms over approximately 12 months using latent transition analysis.
- Generalized estimating equations used to determine associations between symptom patterns and risk of potential PCC.
Main Results:
- Three symptom status groups were identified: 'No/Few Symptoms,' 'Non-Specific Symptoms,' and 'Infection-Related Symptoms.'
- Symptom statuses were associated with risk of PCC following symptomatic infection but not overall PCC risk.
- Symptom-based identification of potential PCC was suboptimal, with modest predictive value.
Conclusions:
- Self-reported symptoms are not a reliable method for identifying potential PCC in people experiencing homelessness.
- High rates of underlying symptoms and asymptomatic SARS-CoV-2 infections complicate symptom-based PCC identification.
- Strengths-based, alternative approaches are recommended for equitable PCC identification in this population.
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