Why Raw VAERS Numbers Can Be Misleading

The Missing Number That Changes Everything

VAERS' greatest limitation isn't what it contains — it's what it's missing:denominators. A denominator is the total number of doses administered of each vaccine. Without this crucial number, comparing adverse event rates across vaccines is not just difficult — it's impossible and potentially dangerous.

Consider this example: Vaccine A has 1,000 VAERS reports while Vaccine B has 100. Which is safer? Without knowing how many doses of each were given, you cannot tell. If Vaccine A was given to 10 million people and Vaccine B to 1,000 people, then Vaccine A is actually much safer (0.01% vs 10% adverse event rate).

COVID-19: A Perfect Case Study

COVID-19 vaccines provide the perfect illustration of the denominator problem. They account for roughly 57% of all VAERS reports ever filed — a staggering proportion that, without context, might suggest unusual safety concerns.

But context changes everything. With an estimated 670,000,000+ doses administered in the U.S., COVID-19 vaccines have a VAERS reporting rate of approximately1674 reports per million doses. This rate is actually within the typical range for vaccines in VAERS.

Why Denominators Are So Hard to Get

If denominators are so important, why doesn't VAERS include them? Several challenges make precise denominator data difficult to obtain:

• Fragmented healthcare system: No single source tracks all vaccinations across providers
• Private vs. public data: Pharmacy chains, private clinics, and public health departments all maintain separate records
• Timing mismatches: Dose distribution data may not align with administration data
• Lot-level complexity: Vaccines may be distributed but not immediately administered
• International variations: Some vaccines are used differently in different countries

Examples of Misleading Raw Comparisons

Here are some examples of how raw VAERS numbers can mislead:

Example 1: Seasonal vs. Pandemic Vaccines

Pandemic vaccines often have more VAERS reports than seasonal vaccines — not because they're more dangerous, but because they're administered to more people in shorter timeframes with heightened public attention.

Example 2: Adult vs. Pediatric Vaccines

Adult vaccines may appear to have higher adverse event rates because adults are more likely to report symptoms and have more complex medical histories that can complicate attribution.

Example 3: New vs. Established Vaccines

New vaccines often have higher reporting rates due to increased vigilance, media attention, and healthcare provider awareness — regardless of their actual safety profile.

Death Reports and the Denominator Problem

The denominator problem is especially critical for death reports. COVID-19 vaccines have approximately 0.0 death reports per million doses administered. While each death represents a tragedy and warrants investigation, this rate provides crucial context.

For comparison, the background death rate in the U.S. population is approximately 8.7 deaths per 1,000 people per year. Among elderly populations (who received vaccines first), background death rates are much higher. This context is essential for interpreting death reports.

What Proper Rate Calculations Show

When researchers calculate adverse event rates using proper denominators, they consistently find:

• Most vaccines have similar adverse event rates when adjusted for doses administered
• Apparent "hot" vaccines often have high reporting due to high usage, not high risk
• Background disease rates often explain temporal associations in VAERS
• True safety signals are rare but can be detected through proper statistical analysis

How Regulators Address the Denominator Problem

Regulatory agencies use multiple strategies to address denominator limitations:

• Active surveillance systems: VSD, PRISM, and other systems with known denominator populations
• Manufacturer data: Companies report doses distributed and track safety signals
• Population surveys: CDC conducts surveys to estimate vaccination coverage
• Electronic health records: Large healthcare systems provide denominator data for their populations

The Media and Public Understanding Challenge

Raw VAERS numbers are frequently misused in media coverage and public discourse:

• Headlines focus on absolute numbers rather than rates
• Social media amplifies scary-sounding raw numbers without context
• Advocacy groups selectively cite raw numbers to support predetermined conclusions
• The complexity of rate calculations makes them less "clickable" than raw numbers

Why This Article Matters Most

Understanding the denominator problem is perhaps the most important concept for anyone interpreting VAERS data. It explains:

• Why COVID-19 vaccines don't necessarily have worse safety profiles despite high raw report numbers
• Why comparing raw VAERS numbers across vaccines can be dangerously misleading
• Why proper epidemiological studies always include denominator data
• Why regulatory decisions are based on rates, not raw numbers