Dear Public Official,

We are a research team led by Gary Hawkins (Seattle, WA), examining Vaccine Adverse Event Reporting System (VAERS) data to identify critical gaps in adverse event reporting during the COVID mRNA vaccine rollout. Our findings, detailed in Mr. Hawkins' 2023–2024 publications on https://deepdots.substack.com (see Exhibits A–F), reveal serious data omissions by the CDC that risk hiding important vaccine safety issues. These exhibits highlight key examples of our research, and we urgently need your help to strengthen public health policy and hold the VAERS reporting system accountable. Our data comes from Dr. Steven Rubin, a computer scientist with over 40 years of experience, who founded medalerts.org in 2003 and has worked with the National Vaccine Information Center since 2005. He has collected VAERS database snapshots since before COVID vaccines were introduced, forming the basis of our findings.

Our research shows critical flaws in VAERS data management:

• A. Removal of detailed narrative fields in foreign VAERS reports, blocking full analysis (Exhibit A);
• B. Deletion of follow-up reports, including confirmed deaths, underreporting severe outcomes (Exhibit B);
• C. Missing Pfizer and Moderna lot data, preventing tracking of specific batches (Exhibit C);
• D. Underreporting of serious conditions like pulmonary embolisms due to poor tagging (Exhibit D);
• E. Correction of numerous lot code errors, revealing issues in tracking adverse reactions during COVID vaccinations (Exhibit E);
• F. Mislabeling of serious adverse event reports, downplaying their severity (Exhibit F).

We urgently request that you investigate these data gaps, evaluate their impact on vaccine safety oversight, and fix flaws in VAERS data management. Detailed evidence from Mr. Hawkins' work is provided in the attached exhibits.

Thank you for addressing this pressing issue. We are ready to provide further details, data, or assistance.

Sincerely,
VAERS Data Processing Group

Jason Page, Point of Contact: info@vaersdata.org

Exhibits

Exhibit A: Removal of Free-Text Fields

Source: "New VAERS Flat File: Easy Data Mining" (June 12, 2023)
Issue: Free-text fields (e.g., symptom narratives, lab data) for foreign VAERS reports were removed, limiting global adverse event analysis.
Impact: Obscures safety signals by reducing contextual data.

Exhibit B: Deletion of Follow-Up Reports

Source: "Undeleting a Gigabyte of Data Purged" (October 3, 2023)
Issue: Follow-up reports confirming deaths were deleted, with only initial reports retained.
Impact: Underreports fatalities, skewing safety analyses.

Exhibit C: Missing Pfizer & Moderna Lot Data (two articles)

Source 1: "Where are the missing 1,290 lots/batches in the Pfizer FOIA request response?" (August 8, 2023)
Issue: 1,290 Pfizer lot codes, linked to thousands of adverse event reports each, were absent from FOIA data.
Source 2: "Further info on the 958 missing lots/batches from the Moderna FOIA request" (August 15, 2023)
Issue: FOIA Request by ICAN provided a list of Moderna COVID vaccine lot codes and expiration dates. However, 958 lots were absent compared to a comprehensive list of 1,343 known Moderna lot codes. These missing lots are linked to thousands of adverse event reports in the Vaccine Adverse Event Reporting System (VAERS), including 19,659 harm reports tied to 103 lots without expiration dates.
Impact: Hinders tracking of batch-specific adverse events.

Exhibit D: Underreporting Pulmonary Embolisms

Source: "Far More Pulmonary Embolisms in VAERS From Covid Vaccines Than Others Are Reporting" (January 11, 2023)
Issue: 408 pulmonary embolism cases (8% sample of 4,976 reports manually reviewed) were not tagged.
Impact: Systematic underreporting of severe adverse events.

Exhibit E: Correction of Lot Code Typos

Source: "Overview: AI Fixed 150,000 Lot Numbers" (April 2, 2024)
Issue: Approximately 150,000 VAERS reports contained lot code typos (e.g., misspellings, incorrect formats) for COVID vaccines, which were corrected using AI-driven analysis.
Impact: Uncorrected typos could fragment data, leading to underreporting of adverse events associated with specific lots and complicating batch-specific safety analyses.

Exhibit F: Misclassification of Serious Reports

Source: "85% Are Serious in VAERS Reports Not Tagged as Serious" (December 4, 2023)
Issue: 85% of VAERS reports not tagged as “serious” contain symptoms meeting serious criteria (e.g., life-threatening conditions, hospitalizations).
Impact: Misclassification underestimates the severity of adverse events, potentially masking critical safety signals.