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Transparent access to VAERS data for informed decision-making. We present the data as-is, with appropriate context and disclaimers.

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Data source: VAERS (Vaccine Adverse Event Reporting System)

Data through 2026 · Updated quarterly

Built by TheDataProject.ai · © 2026 VaccineWatch

Important: VAERS accepts reports of adverse events following vaccination. For any given report, there is no certainty that the reported event was caused by the vaccine. Reports may contain information that is incomplete, inaccurate, coincidental, or unverifiable. Most reports to VAERS are voluntary, which means they are subject to biases. This data cannot be used to determine if vaccines cause or contribute to adverse events.

⚠️

Important: VAERS reports alone cannot determine if a vaccine caused an adverse event. Reports may contain incomplete, inaccurate, or unverified information. Correlation does not equal causation.

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  2. Is VAERS Reliable?
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Is VAERS Reliable?

The short answer: VAERS is reliable for what it's designed to do — detect safety signals. It's unreliable for what many people try to use it for — proving vaccines cause specific harms. Understanding the difference is crucial.

✅ VAERS IS Good For:
  • • Detecting new safety signals early
  • • Identifying unusual patterns
  • • Monitoring known side effects
  • • Generating hypotheses for study
  • • Providing transparency
❌ VAERS Is NOT Good For:
  • • Proving a vaccine caused an event
  • • Calculating actual risk rates
  • • Comparing vaccine safety head-to-head
  • • Making personal medical decisions
  • • Drawing definitive conclusions

What VAERS Was Designed To Do

VAERS was created in 1990 as an early warning system — a "canary in the coal mine" for vaccine safety. Its job is to collect as many reports as possible so that researchers can look for patterns.

Think of VAERS like a suggestion box, not a court of law. It casts a wide net to catch potential signals. The trade-off: it captures noise along with signal, and that's by design.

VAERS has successfully detected real safety signals:

  • Intussusception from RotaShield (1999): VAERS detected this bowel obstruction risk, leading to the vaccine's withdrawal
  • Myocarditis from mRNA COVID vaccines (2021): VAERS data was among the first signals of this rare side effect
  • Thrombosis from J&J vaccine (2021): VAERS reports triggered the investigation that identified TTS
  • Guillain-Barré from flu vaccines: Ongoing monitoring of this rare association

The Strengths of VAERS

1. Anyone Can Report

This is simultaneously a strength and a limitation. The open reporting system means that unusual events get captured even if a healthcare provider wouldn't have thought to report them. It gives patients a voice.

2. Comprehensive Coverage

VAERS covers all vaccines given in the U.S. and has data going back to 1990. This long history allows researchers to identify trends and compare patterns over time.

3. Public Access

Unlike many medical databases, VAERS data is publicly available. This transparency allows independent researchers, journalists, and the public to examine the data.

4. Speed

VAERS can detect signals quickly — within weeks of a vaccine rollout. Active surveillance systems like the VSD take longer to produce results.

The Limitations of VAERS

1. No Causation

This is the most important limitation. A VAERS report means something happenedafter vaccination. It does not mean the vaccine caused it. With millions of vaccinations per year, coincidental events are inevitable.

2. Underreporting

Studies estimate that VAERS captures only 1-10% of actual adverse events(depending on the event type). Minor events like soreness are rarely reported, while serious events are reported more consistently. This means you can't calculate true rates from VAERS data.

3. Stimulated Reporting

Media coverage and public attention can dramatically increase reporting for specific vaccines. COVID-19 vaccine VAERS reports surged partly because of genuine adverse events and partly because of heightened awareness and mandatory reporting requirements.

4. No Verification

VAERS reports are not routinely verified. They may contain inaccurate diagnoses, incomplete information, or even deliberately false reports. While submitting a false report is a federal crime, the system relies primarily on good faith.

5. No Denominator

VAERS tells you how many reports were filed, but not how many people were vaccinated. Without this denominator, you can't calculate actual rates. See our denominator problem analysis.

How VAERS Is Misused

VAERS data is frequently misused in ways that lead to incorrect conclusions:

  • "X deaths reported after vaccination" — implies causation when none is established
  • Raw count comparisons — comparing vaccines without adjusting for doses given or reporting patterns
  • Cherry-picking — highlighting specific scary reports without context
  • Ignoring the disclaimer — every VAERS data download includes a disclaimer about limitations

If someone cites VAERS data to prove a vaccine is dangerous, they're misusing the system. VAERS generates hypotheses; it doesn't test them.

What's Better Than VAERS?

For establishing causation, other systems are more appropriate:

  • Vaccine Safety Datalink (VSD): Active surveillance using electronic health records from 12 million patients
  • Clinical Immunization Safety Assessment (CISA): Expert clinical review of complex cases
  • V-safe: Smartphone-based active surveillance (used for COVID vaccines)
  • Epidemiological studies: Controlled studies comparing vaccinated and unvaccinated populations

These systems complement VAERS. VAERS catches the signal; these systems investigate whether the signal is real.

The Bottom Line

VAERS is a valuable and necessary part of vaccine safety monitoring. It's reliable as an early warning system and for identifying patterns that warrant investigation. It's unreliable as a source of definitive conclusions about vaccine causation or risk.

The best approach: take VAERS data seriously, but interpret it with context. That's exactly what VaccineWatch aims to provide.

Understanding VAERS Better

The Denominator Problem →
Why raw numbers mislead
Reporting Bias →
How bias affects the data
Explore the Database →
See the data for yourself
About VaccineWatch →
Our methodology

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