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Prof Jeffrey S Morris

@jsm2334.bsky.social
101K followers 50 following 586 posts

George S Pepper Professor of Public Health & Preventative Medicine; Biostats, Stats & Data Science, Lifelong learner & truth seeker; Views my own & not employer’s

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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
Likely — I didn’t address that in this article but if there is evidence that cancer causing HPV infections are necessary precursors of throat or head and neck cancers then the same mediation argument implies causal evidence for protection against those as well.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
A detailed explanation and mathematical proof, along with the required conditions and other nuances, are provided here: x.com/jsm2334/stat...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
The population-level data and observational studies provide further corroboration, consistent with this causal effect, but are not required to establish it. That was already done by the RCTs with necessary-precursor endpoints.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
We can deduce causal evidence through a necessary-precursor mediator — and here we have not one but two separate necessary-precursor mediators providing the strong causal evidence.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
So the claim that "we have no causal evidence that HPV vaccines reduce cervical cancer" simply because we lack a large, long-term RCT with the cancer endpoint is FALSE.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
These two facts form a causal mediation chain that implies causal evidence that HPV vaccines reduce the risk of cervical cancer, even without an RCT providing direct evidence on cervical cancer itself.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
2. Both cancer-causing HPV infection and precancerous lesions are necessary precursors of cervical cancer — virtually every cervical cancer is preceded by them.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
It comes from the fact that: 1. We have strong causal evidence from placebo-controlled RCTs that HPV vaccines reduce the risk of (a) cancer-causing HPV infections and (b) precancerous lesions. And…
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
It doesn’t come from recently discussed population studies showing no cancer deaths or from observational studies comparing vaccinated to unvaccinated which by themselves cannot establish causation
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Prof Jeffrey S Morris @jsm2334.bsky.social · 03/07/2026
Do we already have causal evidence that HPV vaccines reduce risk of cervical cancer? Yes, we do. Details in this article and summarized in this thread x.com/jsm2334/stat...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 18/06/2026
Article on the other platform discussing the evidence showing no increased risk of SIDS after vaccination in response to RFK’s letter putting pressure on the editor in chief who retracted the Miller paper on this topic. x.com/jsm2334/stat...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 23/05/2026
Link to original Miller paper (pmc.ncbi.nlm.nih.gov/articles/PMC82…) and retraction/removal notice (sciencedirect.com/science/articl���) Link to retraction notice for Tsatsakis's own paper (sciencedirect.com/science/articl…), and link to my twitter thread on this paper: (x.com/jsm2334/status…)
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Prof Jeffrey S Morris @jsm2334.bsky.social · 23/05/2026
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Prof Jeffrey S Morris @jsm2334.bsky.social · 11/05/2026
NYTimes article with a few excepts: Kennedy Is Driving a Vast Inquiry Into Vaccines, Despite His Public Silence www.nytimes.com/2026/05/11/h...
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Reposted by Prof Jeffrey S Morris
Dr Susan Oliver (PhD) @drsusanoliver.bsky.social · 07/05/2026
Sorry antiaxxers, a new systematic review of 59 studies showed no association between aluminium adjuvanted vaccines and serious or long term health outcomes, such as asthma, autism spectrum disorders, or other chronic conditions. www.bmj.com/content/393/...
bmj.com
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Prof Jeffrey S Morris @jsm2334.bsky.social · 06/05/2026
F.D.A. Blocked Publication of Research Finding Covid and Shingles Vaccines Were Safe www.nytimes.com/2026/05/05/u...
nytimes.com
F.D.A. Blocked Publication of Research Finding Covid and Shingles Vaccines Were Safe
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Prof Jeffrey S Morris @jsm2334.bsky.social · 02/05/2026
Interesting article discussing GenZ’s attitudes towards and concerns about AI www.theverge.com/ai-artificia...
theverge.com
The more young people use AI, the more they hate it
Caught between fears of job loss and social stigma, Gen Z’s opinions of AI are hitting new lows.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 17/04/2026
www.annenbergpublicpolicycenter.org/new-white-pa...
annenbergpublicpolicycenter.org
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 17/04/2026
The article draws on my white paper on vaccine safety monitoring detailing why this analytical approach is invalid, outlines valid methods for analyzing such data & describes more rigorous follow-up studies that have investigated potential safety signals from VAERS, none which support Sterz’s claims
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Prof Jeffrey S Morris @jsm2334.bsky.social · 17/04/2026
The claim rests on a familiar misuse of passive reporting data: treating every post-vaccination death report as vaccine-caused. This implicitly assumes background death rate of 0, when Germany actually sees ~20k deaths/wk. Sterz compounds error by inflating reports by an arbitrary 30x multiplier.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 17/04/2026
I contributed to this article refuting the claim by German toxicologist Dr. Helmut Sterz — widely amplified by Elon Musk — that COVID vaccines likely killed ~60,000 Germans. www.factcheck.org/2026/04/elon...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 31/03/2026
Giving a Grand Rounds talk at Brown University for "National Public Health Week" next Wednesday at noon "Seeing through epidemiological fallacies: How statistics safeguards scientific communication in a polarized era" Link to register is below if you want to come! events.brown.edu/event/327327...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/12/2025
Here is a link to the full white paper: www.annenbergpublicpolicycenter.org/new-white-pa...
annenbergpublicpolicycenter.org
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/12/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/12/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/12/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/12/2025
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...
undark.org
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 12/12/2025
Here is the link to the paper: www.annenbergpublicpolicycenter.org/wp-content/u...
t.co
https://www.annenbergpublicpolicycenter.org/wp-content/uploads/APPC-Vaccine-Safety-2025-12.pdf
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Prof Jeffrey S Morris @jsm2334.bsky.social · 12/12/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 12/12/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 12/12/2025
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).
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Prof Jeffrey S Morris @jsm2334.bsky.social · 04/12/2025
www.medpagetoday.com/infectiousdi...
medpagetoday.com
ACIP Leadership Shake-Up Before Hep B Vaccine Vote Alarms Experts
New chair has questioned vaccine safety, promoted unproven COVID treatments
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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...
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 14/11/2025
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?...
youtu.be
Seeing Through Epidemiologic Fallacies: How Statistics Safeguards Scientific Communication
YouTube video by AAAS Section U (Statistics)
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Prof Jeffrey S Morris @jsm2334.bsky.social · 02/10/2025
You are correct. But the encephaly also tends to occur very early so likely occurred long before vaccination
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Prof Jeffrey S Morris @jsm2334.bsky.social · 27/09/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
Promise! Tell me how successful I was in my attempts to make it accessible, and (mostly) jargon-free
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
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-...
theconversation.com
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
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.
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Prof Jeffrey S Morris @jsm2334.bsky.social · 26/09/2025
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
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Prof Jeffrey S Morris @jsm2334.bsky.social · 19/09/2025
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.
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