What are the strengths and limitations of VAERS for detecting vaccine adverse events?
Executive summary
VAERS is the United States’ national, passive vaccine safety surveillance system co-managed by CDC and FDA that accepts any report of an adverse event after vaccination and is designed as an early‑warning, hypothesis‑generating tool rather than proof of causation [1] [2] [3]. Its strengths are national scope, timeliness, public accessibility and usefulness for detecting unexpected patterns; its limitations include underreporting, variable and unverified data quality, inability to determine causality, and susceptibility to misuse and misinterpretation of raw data [4] [5] [6].
1. A national, open funnel for signals — why VAERS exists and what it does well
VAERS was created as part of post‑licensure surveillance to capture reports of any health problem that happens after vaccination and to detect unusual or unexpected patterns that could indicate safety problems, giving regulators an early signal to investigate further [1] [7] [5]. Because it accepts reports from anyone—healthcare providers, manufacturers, patients, and state programs—and makes data publicly available, VAERS provides near real‑time visibility into post‑market events across the whole country and has historically flagged rare events that warranted follow‑up [1] [4] [5].
2. Passive by design — the structural strengths and tradeoffs of openness
VAERS is a passive or spontaneous reporting system, meaning it relies on voluntary submissions rather than active surveillance of defined populations; that openness enables rapid, broad capture of anecdotal events but also brings variability in completeness and quality of reports and no independent verification for every entry [8] [4] [5]. The system’s design deliberately prioritizes sensitivity—catching as many potential signals as possible—over specificity, so it is a hypothesis generator that feeds more rigorous systems rather than a standalone evidentiary database [8] [3].
3. Why VAERS can’t prove causation — a persistent misconception exploited politically
VAERS data generally cannot be used to determine if a vaccine caused an adverse event because reports document temporal associations that may be coincidental, and the database lacks reliable denominators and controlled comparators needed to estimate rates or causal risk [1] [5] [6]. Public release of raw VAERS records without context has repeatedly been used to make misleading claims about vaccine safety, a problem noted by public health experts and documented in discussions of misinformation [6] [9].
4. Underreporting, duplicates, and data noise — concrete limits on interpretation
Like other spontaneous systems, VAERS suffers from underreporting and inconsistent reporting quality, and some entries are incomplete, inaccurate, or secondary reports related to earlier submissions; these factors mean counts alone cannot be translated into incidence or risk without follow‑up study [6] [5] [4]. For serious reports, VAERS requests additional records to evaluate the case, but it does not obtain follow‑up for every submission, which limits resolution of individual reports [5].
5. How VAERS fits into a broader safety ecosystem — the path from signal to answer
When VAERS detects a potential signal, CDC and FDA do not act on VAERS alone; they use linked electronic health record systems and epidemiologic studies—such as the Vaccine Safety Datalink (VSD), the CISA clinical project, and FDA’s BEST network—to test hypotheses, quantify risk, and assess causality, because those systems have different designs that overcome many passive‑reporting weaknesses [1] [3] [5]. VAERS’ role is therefore necessary but insufficient: it initiates investigation rather than closes it [8] [3].
6. Practical implications and transparency tradeoffs — balancing public trust and misuse
VAERS’ public data and low barrier to reporting support transparency and can maintain public confidence when used responsibly, but the same openness invites selective citation and misinterpretation by actors with agendas, meaning journalists, clinicians and researchers must explain limitations whenever VAERS numbers are discussed [4] [6] [10]. Evaluations of VAERS across decades reaffirm its usefulness for signal detection while stressing that correct interpretation requires follow‑up in more robust data systems [11] [10].