A statewide population-based approach to examining Long COVID symptom prevalence and predictors in Michigan.

OBJECTIVE: The current broad definition of Long COVID, and an overreliance on clinical and convenience samples, is leading to a wide array of Long COVID estimates with limited generalizability. Our objective was to examine Long COVID symptoms using a statewide population-based probability sample. METHODS: Among 8000 sampled adults with polymerase-chain-reaction-confirmed SARS-CoV-2 between June 2020 and July 2021 in the Michigan Disease Surveillance System, 2533 completed our survey (response rate 32.2%). Using modified Poisson regression, we examined sociodemographic, behavioral, and clinical predictors of eight Long COVID symptom clusters, defined as at least one applicable symptom lasting 90 or more days post COVID-19 onset. RESULTS: Neuropsychiatric Long COVID symptoms, including brain fog, were most prevalent (23.7%), followed by systemic symptoms (17.1%), including fatigue, musculoskeletal (11.4%), pulmonary (10.4%), dermatologic (6.7%), cardiovascular (6.1%), gastrointestinal (5.4%), and ear, nose, and throat symptoms (5.3%). In adjusted analyses, female sex, a pre-existing psychological condition, and intensive care unit admission were strong predictors of most Long COVID symptom clusters. Older age was not associated with a higher prevalence of all symptoms - cardiovascular and dermatologic symptoms were most prevalent among middle-aged adults and age was not associated with neuropsychiatric or gastrointestinal symptoms. Additionally, there were fewer associations between pre-existing conditions and cardiovascular, neuropsychiatric, and dermatologic symptoms compared to other symptom clusters. CONCLUSIONS: While many predictors of Long COVID symptom clusters were similar, the relationship with age and pre-existing conditions varied across clusters. Cardiovascular, neuropsychiatric, and dermatologic symptoms require further study as potentially distinct from other Long COVID symptoms.

Population-Based Estimates of Post-acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection (PASC) Prevalence and Characteristics.

BACKGROUND: Emerging evidence suggests many people have persistent symptoms after acute coronavirus disease 2019 (COVID-19) illness. Our objective was to estimate the prevalence and correlates of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC). METHODS: We used a population-based probability survey of adults with COVID-19 in Michigan. Living noninstitutionalized adults aged ≥18 in the Michigan Disease Surveillance System with COVID-19 onset through mid-April 2020 were eligible for selection (N = 28 000). Among 2000 selected, 629 completed the survey between June-December 2020. We estimated PASC prevalence, defined as persistent symptoms ≥30 (30-day COVID-19) or ≥60 (60-day COVID-19) days post-COVID-19 onset, overall and by sociodemographic and clinical factors. We used modified Poisson regression to produce adjusted prevalence ratios (aPRs) for potential risk factors. RESULTS: The analytic sample (n = 593) was predominantly female (56.1%), aged ≥45 years (68.2%), and non-Hispanic White (46.3%) or Black (34.8%). Thirty- and 60-day COVID-19 were highly prevalent (52.5% and 35.0%), even among nonhospitalized respondents (43.7% and 26.9%) and respondents reporting mild symptoms (29.2% and 24.5%). Respondents reporting very severe (vs mild) symptoms had 2.25 times higher prevalence of 30-day COVID-19 (aPR, 2.25; 95% CI, 1.46-3.46) and 1.71 times higher prevalence of 60-day COVID-19 (aPR, 1.71; 95% CI: 1.02-2.88). Hospitalized (vs nonhospitalized) respondents had ~40% higher prevalence of both 30-day (aPR, 1.37; 95% CI: 1.12-1.69) and 60-day (aPR, 1.40; 95% CI: 1.02-1.93) COVID-19. CONCLUSIONS: PASC is highly prevalent among cases reporting severe initial symptoms and, to a lesser extent, cases reporting mild and moderate symptoms.