Revised estimates of types and duration of long COVID symptoms based on claims records from 245 million US patients

COVID-19 has been reported to cause multisystem effects lasting years [Z. Al-Aly, E. Topol, Science 383, 830-832 (2024)]. These findings are primarily based on cohort studies comparing test-positive COVID-19 patients to controls without known COVID-19 infection, tested or untested [M. Cai, Y. Xie, E. J. Topol, Z. Al-Aly, Nat. Med. 30, 1564-1573 (2024)]. However, such comparisons can be biased by the reasons people were tested. Using 14.4 billion insurance claims from 244.7 million US patients, we find that most long-term effects attributed to COVID-19 by unrestricted control designs likely reflect bias due to selective testing of individuals with non-COVID conditions, causing long-term effects of those conditions to be misattributed to COVID-19. We removed this bias by analyzing only tested individuals, comparing test-positive to test-negative patients. Across 614 clinical outcomes followed over 2 y, the test-based design resulted in 83.5% fewer symptoms being attributable to COVID-19 between 30 to 119 d after infection (43 attributable symptoms vs. 262 for the unrestricted control design), a 98.2% reduction at 120 to 359 d (5 vs. 286), and a 100% reduction at 360 to 719 d (0 vs. 369). The unrestricted control design also attributed unrelated outcomes (e.g., firearm injuries) to COVID-19 at a high rate, whereas the testing-based design did not. The test-based control design may modestly underestimate some effects. This study does not indicate that symptoms beyond one year are not genuine but that their attributability to COVID-19 is uncertain.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2026-10-27
DOI
https://doi.org/10.1073/pnas.2604414123
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
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article

Revised estimates of types and duration of long COVID symptoms based on claims records from 245 million US patients

Michael Moor, Julia Reisler, Steven N. Goodman, Stefan Wager et al.
1 links
Proceedings of the National Academy of Sciences
Long-Term Effects of COVID-19
article

Revised estimates of types and duration of long COVID symptoms based on claims records from 245 million US patients

Michael Moor, Julia Reisler, Steven N. Goodman, Stefan Wager, Hamed Nilforoshan, Jure Leskovec, Erfan Jahanparast
article en

Abstract

COVID-19 has been reported to cause multisystem effects lasting years [Z. Al-Aly, E. Topol, Science 383, 830-832 (2024)]. These findings are primarily based on cohort studies comparing test-positive COVID-19 patients to controls without known COVID-19 infection, tested or untested [M. Cai, Y. Xie, E. J. Topol, Z. Al-Aly, Nat. Med. 30, 1564-1573 (2024)]. However, such comparisons can be biased by the reasons people were tested. Using 14.4 billion insurance claims from 244.7 million US patients, we find that most long-term effects attributed to COVID-19 by unrestricted control designs likely reflect bias due to selective testing of individuals with non-COVID conditions, causing long-term effects of those conditions to be misattributed to COVID-19. We removed this bias by analyzing only tested individuals, comparing test-positive to test-negative patients. Across 614 clinical outcomes followed over 2 y, the test-based design resulted in 83.5% fewer symptoms being attributable to COVID-19 between 30 to 119 d after infection (43 attributable symptoms vs. 262 for the unrestricted control design), a 98.2% reduction at 120 to 359 d (5 vs. 286), and a 100% reduction at 360 to 719 d (0 vs. 369). The unrestricted control design also attributed unrelated outcomes (e.g., firearm injuries) to COVID-19 at a high rate, whereas the testing-based design did not. The test-based control design may modestly underestimate some effects. This study does not indicate that symptoms beyond one year are not genuine but that their attributability to COVID-19 is uncertain.

Proceedings of the National Academy of SciencesVol. 123(44)
University of California System (US), ETH Zurich (CH), Stanford University (US)
National Science Foundation, Genentech, Wu Tsai Neurosciences Institute, Stanford University
Good health and well-being
Openalex Percentile: Top 14%
Long-Term Effects of COVID-19
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