JMIR Public Health and Surveillance (Oct 2024)

Associations Between Acute COVID-19 Symptom Profiles and Long COVID Prevalence: Population-Based Cross-Sectional Study

  • Jana L Hirschtick,
  • Elizabeth Slocum,
  • Yanmei Xie,
  • Laura E Power,
  • Michael R Elliott,
  • Robert C Orellana,
  • Nancy L Fleischer

DOI
https://doi.org/10.2196/55697
Journal volume & issue
Vol. 10
pp. e55697 – e55697

Abstract

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Abstract BackgroundGrowing evidence suggests that severe acute COVID-19 illness increases the risk of long COVID (also known as post–COVID-19 condition ObjectiveThis study aimed to examine associations between acute COVID-19 symptom profiles and long COVID prevalence using a population-based sample. MethodsWe used a dual mode (phone and web-based) population-based probability survey of adults with polymerase chain reaction–confirmed SARS-CoV-2 between June 2020 and May 2022 in the Michigan Disease Surveillance System to examine (1) how acute COVID-19 symptoms cluster together using latent class analysis, (2) sociodemographic and clinical predictors of symptom clusters using multinomial logistic regression accounting for classification uncertainties, and (3) associations between symptom clusters and long COVID prevalence using modified Poisson regression. ResultsIn our sample (n=4169), 15.9% (n=693) had long COVID, defined as new or worsening symptoms at least 90 days post SARS-CoV-2 infection. We identified 6 acute COVID-19 symptom clusters resulting from the latent class analysis, with flu-like symptoms (24.7%) and fever (23.6%) being the most prevalent in our sample, followed by nasal congestion (16.4%), multi-symptomatic (14.5%), predominance of fatigue (10.8%), and predominance of shortness of breath (10%) clusters. Long COVID prevalence was highest in the multi-symptomatic (39.7%) and predominance of shortness of breath (22.4%) clusters, followed by the flu-like symptom (15.8%), predominance of fatigue (14.5%), fever (6.4%), and nasal congestion (5.6%) clusters. After adjustment, females (vs males) had greater odds of membership in the multi-symptomatic, flu-like symptom, and predominance of fatigue clusters, while adults who were Hispanic or another race or ethnicity (vs non-Hispanic White) had greater odds of membership in the multi-symptomatic cluster. Compared with the nasal congestion cluster, the multi-symptomatic cluster had the highest prevalence of long COVID (adjusted prevalence ratio [aPR] 6.1, 95% CI 4.3‐8.7), followed by the predominance of shortness of breath (aPR 3.7, 95% CI 2.5‐5.5), flu-like symptom (aPR 2.8, 95% CI 1.9‐4.0), and predominance of fatigue (aPR 2.2, 95% CI 1.5‐3.3) clusters. ConclusionsResearchers and clinicians should consider acute COVID-19 symptom profiles when evaluating subsequent risk of long COVID, including potential mechanistic pathways in a research context, and proactively screen high-risk patients during the provision of clinical care.