Did Cleveland Clinic study on the flu vaccine show those vaccinated caught more flu
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Executive summary
A large Cleveland Clinic preprint of ~53,400 employees found higher laboratory‑confirmed influenza rates in vaccinated working‑age adults and reported a calculated vaccine effectiveness of −26.9%, meaning vaccinated people in that cohort had more infections during the 2024–25 season [1] [2]. The paper is a non–peer‑reviewed preprint that its authors and outside experts say shows an association, not proof the vaccine caused more infections; multiple critics and fact‑checkers flagged methodological concerns and potential biases in interpretation [3] [4] [5].
1. What the Cleveland Clinic study actually reported
The study followed 53,402 Cleveland Clinic employees from Oct. 1, 2024, through the respiratory season and found 82.1% received a seasonal influenza vaccine; overall only about 2.02% tested positive for influenza, but vaccinated people accumulated infections more quickly, producing a negative vaccine‑effectiveness estimate of −26.9% for working‑age adults [1] [2].
2. Association versus causation — how authors and spokespeople framed it
The paper’s language and the Cleveland Clinic’s public comments emphasize an association: vaccinated employees had higher observed influenza incidence in this season, and the authors concluded they were “unable to find a protective influence” of the vaccine in this cohort—not that vaccination caused people to get sick [2] [3]. The Cleveland Clinic told reporters the results “do not suggest that vaccination increases the risk of flu” [4] [3].
3. Why headlines spread the “vaccine increases flu” message
Preprints attract rapid media and social‑media amplification before peer review. Outlets and posts leapt from a reported association to causal claims (“get the shot, get the disease”), amplifying the most sensational reading of the negative effectiveness number [6] [7] [8]. Fact‑checkers cautioned that such causal headlines misstate the study’s conclusion [3].
4. What experts and reviewers flagged about the study
Independent clinicians and commentators pointed to likely biases and methodological issues — especially testing bias (vaccinated people more likely to seek testing), occupational exposure differences, and the limits of a single‑center, observational preprint — and argued the paper’s design does not support the strong causal claim that the shot increases risk [4] [5] [9]. MedPage Today called the work “flawed” and said the authors missed key design problems [5].
5. How public‑health groups and communicators responded
Public‑health communicators noted the study hadn’t been peer reviewed and warned against changing vaccine policy based on a single preprint. They urged continued emphasis on vaccination as the best available protection against severe influenza, and warned that anti‑vaccine actors were using the preprint to amplify misinformation [1] [9].
6. What the numbers mean in context
Only about 2% of the cohort tested positive for influenza, so absolute differences were small even as relative metrics produced a negative effectiveness estimate; the study found the difference emerged when influenza activity was high, not uniformly across the season [1] [2]. That pattern, and the low overall case count, make interpretation sensitive to bias and confounders [1] [5].
7. Competing research and Cleveland Clinic’s other influenza work
Cleveland Clinic researchers have published other vaccine and immunology studies during 2024–25, including work on B‑cell exhaustion and vaccine formulation tailored by age, which present a broader research agenda to improve vaccine design rather than endorse a narrative that vaccines are harmful [10] [11].
8. Bottom line for readers and policymakers
The preprint found an association of vaccination with higher observed influenza cases in this specific employee cohort and season, but it does not prove the vaccine caused more infections; multiple experts, fact‑checkers and the Cleveland Clinic itself warned against causal leaps and against changing public‑health recommendations based on the preprint alone [2] [3] [4]. Peer review, replication in other populations, and careful adjustment for testing and exposure biases are needed before policy or personal choices should be altered [5] [1].
Limitations and transparency: this analysis relies solely on the preprint and the reporting, commentary and fact checks listed above; available sources do not mention any subsequent peer‑reviewed publication or definitive causal evidence beyond the preprint [2] [3].