Prof Jeffrey S Morris

New White Paper Analyzes U.S. Vaccine Safety Monitoring System and Suggests Improvements | The Annenberg Public Policy Center of the University of Pennsylvania In a white paper, Penn biostatistician Jeffrey Morris analyzes the U.S. vaccine safety monitoring system and offers ways to improve VAERS and other components.

Here is a link to the full white paper:

www.annenbergpublicpolicycenter.org/new-white-pa...

4. Net benefit of vaccination after rollout in 2021
5. Factors to evaluate the case report based analysis of VAERs deaths that the FDA has performed and whose details are expected at the end of this month

2. discussing SARS-CoV-2 mRNA vaccines and myocarditis, the initial approval of vaccines for 12-15yr old population, and the Korean population level myocarditis study
3. One of my suggestions for improving analysis of Vaers.

The article only includes some excerpts from the full interview, which include:
1. discussing some of the ways these data are sometimes misinterpreted or misrepresented

Interview: How the U.S. Government Monitors Vaccine Safety Biostatistician Jeffrey Morris discusses his analysis of the vaccine monitoring system — and how it could be improved.

MIT’s UnDark published this interview with me discussing a few points from my new white paper on the U.S. vaccine safety monitoring system, and follow up points related to myocarditis, childhood vaccine rollouts, and the new Vaers report coming from the fda

undark.org/2025/12/19/i...

Here is the link to the paper:
www.annenbergpublicpolicycenter.org/wp-content/u...

The goal is to stimulate better public explanation, constructive debate on enhancements, and help improve the system to arrive at a robust safety infrastructure that earns public confidence and protects patient safety.

This article reviews each component's role, strengths, limitations, & analytical considerations, explains how they are intended to function together, & proposes component-level & system-wide improvements to strengthen detection and evaluation of vaccine-related risks and transparent communication.

My paper summarizing the multi-component US vaccine safety monitoring system has just posted online.

The key components of the system include:
1. pre-licensure clinical trials
2. passive monitoring (VAERs)
3. active monitoring (VSD, PRISM)
4. clinical analysis (CISA).

ACIP Leadership Shake-Up Before Hep B Vaccine Vote Alarms Experts New chair has questioned vaccine safety, promoted unproven COVID treatments

www.medpagetoday.com/infectiousdi...

5. Why apparent vaccine–cancer links can arise from screening patterns rather than biology.

I argue for greater engagement of statistical scientists and epidemiologists in high-stakes science communication.

4. How misaligned case/control periods (e.g., a series of nine studies by RFK appointee David Geier) can manufacture spurious associations between vaccination and chronic disease.

3. How policy shifts confound before/after claims (e.g., zero-COVID contexts such as Singapore), and how Hong Kong’s age-structured coverage can serve as a counterfactual lens to catch a glimpse of what might have occurred worldwide in 2021 if not for COVID-19 vaccines.

Illustrative examples include:
1. Why a high share of hospitalized patients can be vaccinated even when vaccines remain highly effective.
2. Why higher crude death rates in some vaccinated cohorts do not imply vaccines cause deaths.

This talk uses concrete COVID-19 and vaccine-safety case studies to highlight foundational pitfalls: base-rate fallacy, Simpson’s paradox, post-hoc/time confounding, mismatched risk windows, differential follow-up, and biases driven by surveillance and health-care utilization.

Abstract:
Observational data underpin many biomedical and public-health decisions, yet they are easy to misread, sometimes inadvertently, sometimes deliberately, especially in fast-moving, polarized environments during and after the pandemic...

I finish with concrete advice re: science communication in our polarized world

I mention a paper I've just written explaining the multi-component USA vaccine safety monitoring system, how it is often misinterpreted/misrepresented and concrete suggestions for how the current system can be improved

It discusses my science communication work during/since the pandemic, using concrete COVID-19/vaccine safety case studies to illustrate epidemiological fallacies causing misinterpretations of observational data feeding false claims highlighting importance of critical scientific evaluation of claims

YouTube video by AAAS Section U (Statistics) Seeing Through Epidemiologic Fallacies: How Statistics Safeguards Scientific Communication

Last month I gave a webinar for AAAS (publisher of the journal Science) entitled:

"Seeing Through Epidemiologic Fallacies: How Statistics Safeguards Scientific Communication in a Polarized Era"

AAAS posted the webinar on their YouTube page -- link is below.
youtu.be/GQtA9N_Dwog?...

You are correct.

But the encephaly also tends to occur very early so likely occurred long before vaccination

You can ask but since they are medical records data and they did not even want this paper getting out, I wouldn’t be optimistic

Promise! Tell me how successful I was in my attempts to make it accessible, and (mostly) jargon-free

Why a study claiming vaccines cause chronic illness is severely flawed – a biostatistician explains the biases and unsupported conclusions The main comparisons in the unpublished report are skewed, and it is being presented as stronger evidence than its design really allows.

My article is aimed at the general public, so it explains these three statistical issues in accessible language while showing why they matter for interpreting the study’s conclusions.

The link to my full article follows:
theconversation.com/why-a-study-...

3. Unadjusted confounders: key factors like urban/rural setting, socioeconomic status/insurance, and air/water pollution weren’t accounted for. These influence both vaccination likelihood and disease risk, as well as how often families use Henry Ford clinics, shaping what shows up in the records

2. Detection bias – vaccinated children had far more interactions with the Henry Ford health system, giving them more chances to have conditions diagnosed and recorded.

In short, the study suffers from:

1. Surveillance bias – most children, especially the unvaccinated, weren’t followed long enough to reach the ages when chronic diseases are usually diagnosed.

I’ve written an article for The Conversation about the so-called “Inconvenient Study,” described as a landmark study demonstrating vaccines cause chronic health conditions in children, highlighting its major design flaws and statistical problems that prevent it from showing what its promoters claim

Yes.

It just eliminated the choice of getting them together.

Doesn't make much of a difference, but then that begs the question why they spent half a day on it.

Performative, not substantive.

They noticed the logical inconsistency of their vote yesterday and redid the vote to remove the choice of a single combination shot for ALL children less than 4 years for parents who want them, not just an arbitrary subset of them.

Outside of that, other children are covered by private insurance, CHIP Medicaid, Indian health service, tricare, and other programs

With ACIP recommending against combined shot for <4yrs, these programs are not guaranteed to cover it anymore.

But they voted to keep covering it for VFC kids only.