Defining long COVID using a population-based SARS-CoV-2 survey in California

Background: More than four years after the start of the COVID-19 pandemic, understanding of SARS-CoV-2 burden and post-acute sequela of COVID (PASC), or long COVID, continues to evolve. However, prevalence estimates are disparate and uncertain. Leveraging survey responses from a large serosurveillance study, we assess prevalence estimates using five different long COVID definitions among California residents. Methods: The California Department of Public Health (CDPH) conducted a cross-sectional survey that included questions about acute COVID-19 infection and recovery. A random selection of California households was invited to participate in a survey that included demographic information, clinical symptoms, and COVID-19 vaccination history. We assessed prevalence and predictors of long COVID among those previously testing positive for SARS-CoV-2 across different definitions using logistic regression. Findings: A total of 2883 participants were included in this analysis; the majority identified as female (62.5 %), and the median age was 39 years (interquartile range: 17–55 years). We found a significant difference in long COVID prevalence across definitions with the highest prevalence observed when participants were asked about incomplete recovery (20.9 %, 95 % confidence interval [CI]: 19.4–22.5) and the lowest prevalence was associated with severe long COVID affecting an estimated 4.9 % (95 % CI 4.1–5.7) of the participant population. Individuals that completed the primary vaccination series had significantly lower prevalence of long COVID compared to those that did not receive COVID vaccination. Interpretation: There were significant differences in the estimated prevalence of long COVID across different definitions. People who experience a severe initial COVID-19 infection should be considered at a higher probability for developing long COVID. Funding: Centers for Disease Control and Prevention - Epidemiology and Laboratory Capacity.