What the US cancer mortality data can and cannot show about mRNA vaccination
Year: 2026
Type: preprint
Abstract: A methodological response to Catanzaro and colleagues (doi:10.5281/zenodo.22282111). A 2026 preprint reports 154,330 excess US cancer deaths following the week of peak mRNA vaccine uptake, with its own query of federal files bracketing 119,000-197,000. This response re-analyses the same CDC WONDER mortality files. The source estimate is reproduced: +50,071 underlying-cause deaths above a linear 2014-2019 count trend between April 2021 and August 2026, against 47,012 reported. The same observed deaths yield +50,071, +71,556 or -219,279 under three counterfactual baselines, a span of 290,835 deaths with no observation altered. Between 2019 and 2024 observed deaths at ages one and over rose 3.38%, while the age-adjusted rate fell 4.67% on NCHS published denominators and 6.76% on Census vintage-2025 denominators; the officially published rate fell 4.65% over the same interval. The certificate-coding gap from which the source derives a 72,118-death addition was 24.0% wider in January-November 2020 than in the same months of 2019, before any vaccination, peaks with successive COVID-19 waves, and has receded since 2022. These data do not establish that mRNA vaccination caused excess cancer deaths. The reported excess is highly sensitive to baseline specification, the underlying age-adjusted rate fell between 2019 and 2024 on every denominator basis examined, and the largest component of the published total describes a shift that began before vaccination. This analysis does not claim to have explained the residual, and a pooled population-level series cannot establish or exclude individual-level causation in either direction. The deposit includes the manuscript and a replication package containing all preserved inputs, an offline analysis script enforcing nineteen validation assertions, regenerated results, and review notes documenting remaining limitations.
Author: Boland, Greg
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225394315