Natural History of Self-reported Symptoms Following SARS-CoV-2 Infection: A Target Trial Emulation in a Prospective Community-Based Cohort
Shen, Y.; Shahn, Z.; Robertson, M.; Gebo, K.; Nash, D.
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BackgroundThe natural history of symptoms after SARS-CoV-2 infection remains uncertain because many studies are non-representative, ignore background symptom prevalence, lack longitudinal tracking, and omit appropriate controls. Using a prospective, community-based cohort with repeated symptom measures, we estimated post-infection risks of long COVID symptoms versus contemporaneous uninfected controls. MethodsWe analyzed the CHASING COVID Cohort, a U.S. longitudinal study with surveys and serology (March 2020-December 2023). Infection status (January 2021-December 2022) was determined from self-reported PCR/antigen results, serology, or CSTE probable criteria. We emulated 24 monthly target trials comparing individuals newly infected at time zero with those remaining uninfected. Outcomes were new-onset long-COVID symptoms not reported pre-infection, assessed overall and within three clusters (neurological, autonomic, exercise intolerance) at 4-8 and 9-12 months post-infection. Inverse probability of treatment and censoring weights adjusted for confounding and informative loss to follow-up. ResultsThe analysis included 1,055 infected and 52,310 uninfected person-trials. At 4-8 months, the adjusted risk of any long-COVID symptom was 22.6% (95% CI, 20.5-24.8) among infected versus 11.3% (11.1-11.5) among uninfected (adjusted risk difference [aRD], 11.3% [9.2-13.5]; adjusted risk ratio [aRR], 2.01 [1.81-2.20]). At 9-12 months, risks were 19.2% (17.0-21.3) vs 12.4% (12.2-12.7) (aRD, 6.7% [4.6-8.9]; aRR, 1.54 [1.37-1.72]). Across all three clusters, infected participants had consistently higher risks at both intervals. ConclusionsSARS-CoV-2 infection was associated with elevated risk of new-onset long-COVID symptoms persisting up to 12 months. Using a national community-based cohort, contemporaneous uninfected controls, and target-trial emulation clarifies the burden attributable to infection and supports ongoing surveillance and targeted prevention and care.
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