Long Covid Symptom Clusters, Correlates and Predictors in a Highly Vaccinated Australian Population in 2023

Bibliographic Data

ID19506794
AuthorsEssa Tawfiq (0000-0001-8147-079X, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Rosalie Chen (Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Damian Alexander Honeyman (0000-0002-4339-1801, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Rebecca Dawson (0000-0002-9752-3531, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Mohana Kunasekaran (0000-0001-5779-7979, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Adriana Notaras (0000-0003-0251-9626, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia), Deepti Gurdasani (0000-0001-9996-6929, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia, corresponding author), Helen Skouteris (0000-0001-9959-5750, Health and Social Care Unit School of Public Health and Preventive Medicine, Monash University in collaboration with Monash Health Melbourne Australia), Darshini Ayton (0000-0002-2754-2024, Health and Social Care Unit School of Public Health and Preventive Medicine, Monash University in collaboration with Monash Health Melbourne Australia), C Raina Macintyre (0000-0002-3060-0555, Biosecurity Program The Kirby Institute, Faculty of Medicine and Health The University of New South Wales Sydney Australia, corresponding author)
Year2025
Volume28
Issue3
Pagese70273-e70273
Publication date2025-06-01
Open AccessYes
TypeARTICLE
VenueHealth Expectations (JOURNAL)
Journal identifiersISSN: 1369-6513 • E-ISSN: 1369-7625
PublisherWiley (PUBLISHER • GB)
DOI10.1111/hex.70273
PMID40342248
OpenAlexW4410214122
LanguageEN
References cited45

BACKGROUND: Limited data exists regarding long Covid burden following Omicron infection in highly vaccinated populations. OBJECTIVE: To (1) characterise long Covid prevalence and predictors and (2) identify key symptom clusters and their correlates among long Covid patients, during an Omicron-predominant period in a highly vaccinated population. DESIGN: Anonymous, online, cross-sectional survey. SETTING: January 2023, Australia. PARTICIPANTS: Residents aged ≥ 18 years with self-reported history of test-positive Covid-19. The main variables studied were socio-demographic characteristics, Covid-19 risk factors, vaccination, infection history and experiences with long Covid. MAIN OUTCOME MEASURES: Long Covid symptoms. Symptom-based clustering was used to identify long Covid symptom clusters and their functional correlates. Predictors of long Covid occurrence and severity were assessed using multivariable logistic regression. RESULTS: Overall, 240/1205 participants (19.9%) reported long Covid. Long Covid risk was significantly higher for women OR 1.71 (95% CI: 1.17-2.51), people with comorbidities 2.19 (95% CI: 1.56-3.08) and those using steroid inhalers for Covid-19 treatment (2.34 [95% CI: 1.29-4.24]). Long-Covid risk increased with increasing Covid-19 infection severity (moderately severe symptoms: 2.23 [95% CI: 1.50-3.30], extremely severe symptoms: 5.80 [95% CI: 3.48-9.66], presented to ED/hospitalised: 7.22 [95% CI: 3.06-17.03]). We found no significant difference in the likelihood of long Covid between the Omicron and pre-Omicron periods, vaccination status and participant age. We identified two long Covid clusters (pauci-symptomatic, n = 170, vs. polysymptomatic, n = 66). Polysymptomatic cluster membership was associated with worse functioning (impacts on work, moderate activity, emotions and energy). Severity acute infection was strongly predictive of polysymptomatic cluster membership (5.72 [2.04-17.58]). Monoclonal antibody treatment was strongly associated with pauci-symptomatic cluster membership (0.02 [0.00-0.13]). DISCUSSION: Our study shows that long Covid is an important health burden in Australia, including during the Omicron era, and identifies several risk factors. We found a subgroup of patients characterised by more symptoms and worse functional outcomes. Our findings can inform policies for protecting vulnerable populations and frameworks for long Covid risk assessment and management. CONCLUSIONS: One-in-five people may suffer long Covid after acute Covid-19 infection, with similar risk across age groups. Omicron variants appear not to have a lower risk compared to earlier variants in our study. A cumulative number of symptoms can help triage long Covid patients. PATIENT OR PUBLIC CONTRIBUTION: We did not involve patients or the public in the design of the questionnaire. However, after a soft launch, we revised some survey questions by reviewing early responses from patients and the public

Cross-sectional study · Disease · Environmental health · Logistic regression · Pathology · Population · Vaccination · COVID-19 and Mental Health · COVID-19 Clinical Research Studies · Demography · Long-Term Effects of COVID-19 · Medicine · Immunology · Internal Medicine

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