Dear readers, I am delighted to share with you the fruits of a massive research project I’ve been working on, which is the reason why you haven’t heard from me in a very long time. I quickly realised after I started working on it that I would have to prioritise it at the neglect of posting here. I got so swept up in it that I didn’t even have time to post about my Process 1 vs Process 2 work. I hope you will agree it was worth it.
I will start with the key findings and then try to explain the methodology in plain language. The paper is based on analysis of electronic health records (EHR) from one of Israel’s largest health insurance funds. For those of you who would rather read the paper itself, here’s a PDF.
Key findings
Here are the key findings (as summarised in a post on X).
Women vaccinated in early pregnancy (weeks 8-13) had a higher-than-expected number of foetal losses:
- Dose 1 = 3.9 more per 100 women [43% higher than expected: 13 vs 9]
- Dose 3 = 1.9 more per 100 women [19% higher than expected: 12 vs 10]
Late pregnancy losses were a big part of the signal.
Among all women, 1.1% lost their pregnancy after week 24, compared to 2.7% of women who received dose 1 in early weeks, and 1.8% of women who received dose 3 in early weeks.
In fact, most of the excess losses occurred later in pregnancy, including nearly half after week 24.
In Israel, abortions after week 24 are very rare and must be medically justified. This strongly suggests biological, not behavioural, mechanisms are involved.
Influenza Vaccination
In stark contrast, women vaccinated for influenza in the same weeks (8-13) saw fewer foetal losses than expected, about five per 100 women vaccinated.
What’s the significance of that? Comparing both types of vaccines helps control for bias in who chooses to get vaccinated.
For example, if women vaccinate in early pregnancy because they have health problems, the elevated foetal loss risk for COVID-19 vaccines could simply be due to that bias.
But people who get vaccinated are usually healthier and more health conscious to begin with. This is called healthy vaccinee bias and can make vaccines look safer than they really are. It’s a known – but often ignored – issue in vaccine safety research based on real-world data.
Influenza vaccination during pregnancy showed lower-than-expected foetal losses — likely due to healthy vaccine bias. So it’s even more striking that mRNA COVID-19 vaccination in early pregnancy showed higher-than-expected foetal losses, despite healthy vaccinee bias.
The problem with biases like this is that they can be difficult to control for even with a rich dataset. They can be due to unmeasured factors or characteristics, which can be stable or transient. But if we assume that women who vaccinated for Covid and influenza in early pregnancy are similar, then comparing them is a way of checking that our findings are not due to these (unmeasured) characteristics.
If that assumption is correct, it means that the number of foetal losses per 100 women vaccinated for COVID in weeks 8-13 should be compared to the number among women vaccinated for influenza. That would make the observed-to-expected number closer to nine per 100.
Previous Research
So why have previous studies missed this? There are several possible reasons. First, few other studies have looked at vaccination in early pregnancy. Second, other studies tend to separate early vs late foetal losses based on faulty assumptions, meaning they are more likely to miss the signal. Finally, almost all other studies compare vaccinated vs unvaccinated women during vaccination campaigns. That approach is vulnerable to bias — especially if healthier women are more likely to vaccinate (a.k.a. ‘healthy vaccinee bias’).
Our approach was different. We used detailed medical records to estimate expected foetal loss rates for each vaccinated woman — based on her individual risk factors and pregnancy timing — using data from pre-Covid years. What this means is that we used data from 2016-2018 to develop a statistical model predicting a woman’s chances of experiencing foetal loss given her (measured) individual characteristics and gestational week. We then applied the results from that model to women in the 2020-2022 to predict their chances of foetal loss based on their characteristics and gestational week. This is how we come up with the expected number of foetal losses.
The model does a very good job of predicting foetal losses for the population overall, and also for unvaccinated women and women vaccinated before pregnancy. But when we look at women vaccinated during pregnancy, our predictions fall apart: women vaccinated for Covid in early pregnancy were much more likely to have a foetal loss compared to what was predicted and women vaccinated for influenza were much less likely. In the paper’s conclusions, we discuss why this is lower-than-expected rate for influenza is likely to be due to the healthy vaccinee effect.
ODDS AND ENDS
Research Team
The research team was incredible. First off, I worked hand-in-glove with Professor Retsef Levi of MIT, who was recently appointed to the US Advisory Council on Immunisation Practices (ACIP). We previously worked together to expose the Process 1 vs Process 2 bait-and-switch. Retsef is a data hawk who is incredibly sharp. I couldn’t think of a better person to sit on the committee and assess the data in a sober and balanced way.
We were also joined by several tremendous clinicians and researchers from Maccabi Health Services, the insurance fund from which our data originate: Tal Patalon, Sivan Gazit and Yaakov Segal (the latter of whom is the had of OBGYN services at Maccabi). And rounding out our team are two clinician researchers, Tracy Beth Hoeg and Joseph Fraiman. Tracy has co-authored many important studies casting a critical light on many pandemic measures (like masking children) and now has a position at the FDA. Joseph was the lead author of the reanalysis of the mRNA covid vaccine trial safety data that found an alarmingly high number of adverse events.
None of the co-authors (me included) would agree to put their name on such a controversial paper without being extremely confident that the results are rock solid. And they are: we did our absolute best to make them go away or think of alternative explanations, but everything we did just made them stronger.
86% Miscarriage Rate
One statistic that is often thrown about is that there was an 86% or 82% abortion rate. This is nonsense. One of the things we note in the conclusion of the paper is how easy it was to miss the safety signal, in part because relatively few women are vaccinated in early pregnancy and the calamitous results of that were spread out over the entire pregnancy, encompassing both miscarriages and stillbirths. But a miscarriage rate of 80% would have been impossible to miss.
Arkmedic has addressed why these numbers are wrong in a very clear and thorough post.
I addressed the 82% rate from the ‘Pfizer papers’ in point number 3 of my takedown of Stupiders’ Died Suddenly. (This post has been substantially revised. For the unrevised version see here.)
If you keep repeating those numbers after reading those posts, then you are intentionally misleading people.
The Jewish Question
Our analysis draws on data from Israel. The effects we find mainly involved Jewish Israeli women. But there are still far too many people who think that the Covid vaccines are some kind of Jewish depopulation conspiracy and that Israeli Jews were given a placebo. If you still think that after reading this paper, I don’t know what to tell you.
Israel was one of the very first countries to vaccinate the population. Israelis were also among the first to document the manifold harms caused by these vaccines. One of the bravest and loudest voices was Avital Livny, who put her life on hold to document these harms, including the chilling account from a woman who experienced a bloody miscarriage. Her documentary was released in 2021 and was far ahead of the curve. You can watch it here for free.
Dr Josh Guetzkow is Senior Lecturer in Criminology and Sociology at the Hebrew University of Jerusalem. This article first appeared on his Substack page, which you can subscribe to here.
To join in with the discussion please make a donation to The Daily Sceptic.
Profanity and abuse will be removed and may lead to a permanent ban.