Revised estimates of the types and durations of long Covid symptoms based on claims records from 245 Million US patients

COVID-19 has been shown to cause a range of harmful long-term effects on nearly every organ system1-3. These findings are based on retrospective studies comparing COVID-19 patients to patients with similar medical histories and demographics but no COVID-19 diagnosis4-16. However, concerns have emerged that these comparisons may be biased if COVID-19 patients had unrelated health conditions or other factors not recorded in their medical records17-21. Here, using a massive dataset of 14.4 billion health insurance claims from 244.7 million U.S. patients, we find that the large majority of long-term effects attributed to COVID-19 by methods used in conventional studies are likely due to bias from selective testing. This bias arises because individuals with non-COVID health conditions producing long-term symptoms were more likely to seek care and be tested for COVID-19. As a result, their non-COVID symptoms are attributed to COVID-19. We develop a study design that reduces this bias by only considering individuals who have taken a COVID-19 PCR test, and then comparing similar patients whose first test came back positive vs. negative. This way the COVID-19 patients and control group are more similar and non-COVID factors play less of a role. We examine 614 clinical outcomes over a 2-year followup period and reveal an order of magnitude smaller--but still clinically significant--number of long-term effects attributed to COVID-19 that persist for up to one year after infection. We confirm that the long-term effects of COVID-19 span many organ systems, including respiratory, cardiovascular, musculoskeletal, and integumentary systems, but are significantly narrower in scope and duration than previously believed. Although some symptoms exist more than one year after COVID-19 infection, they occur at similar rates in individuals who tested negative and are therefore not attributable to COVID-19 infection. Our findings pinpoint the specific long-term effects of COVID-19 and show how large-scale data can be used to enable careful evaluation and design of population health studies.