Lancet paper based on >3.4m USA patients found Pfizer vaccine effectiveness (VE) vs. infection decreased from 88% 1m after vaccination to 47% after 5m, but that VE vs. hospitalization remained strong at 93% through 6m.
This paper followed >3.4m patients >12yr old in the Kaiser Permanente Southern California (KPSC) system between 12/20 and 7/21 using a retrospective cohort design.
All patients needed to have >1yr of previous data to establish comorbidities.
Their primary analysis computed relative risk of PCR+ infection, comparing unvaccinated with fully vaccinated individuals for each calendar day.
They adjusted for age, sex, race, previous SARS-CoV-2 infection, SES, previous health-care utilization, & various co-morbidities.
Their results validate what has been seen in Israel, UK and elsewhere: that Pfizer VE vs. infection wanes over time, down near 50% after 5m.
It does not go to zero, so there is still protection vs. infection, it is just not as strong as it was closer to time of vaccination.
They sequenced the positive samples to evaluate the variants. We can see the shift in variants in this region, dominated by Epsilon in the winter, Alpha in the spring, and Delta in the summer.
There is some concern of confounding with variant since Delta emerged more recently the longest after vaccination.
But they looked at waning VE separately by variant, & found that the waning was not an artifact of Delta, & waning effect is seen across all variants.
Looking at VE vs. hospitalization (with PCR+ test 14 days before to 3 days after admission), we see VE of 93% that does not show evidence of any waning over time.
Taken together, this paper validates other data showing:
(1) VE vs infection wanes down to ~50% after 6m (2) VE vs hospitalization remains >90% after 6m.
Pfizer was involved in this study, so I encourage critical assessment, but conclusions are strongly supported by the data.
Large contact tracing study in UK shows Pfizer vaccine reduces transmission by 82% vs alpha and 65% vs delta and AstraZeneca by 63% and 36%, respectively. medrxiv.org/content/10.110…
The study uses the national contacting tracing registry and compares testing positivity of contacts across vaccinated and unvaccinated, stratify information by vaccine type and number of doses
The modeling accounts for key potential confounding variables in the tested individual so as not to be driven by demographic factors.
When you are senior editor of a journal and handle your own paper, it is not peer review, it is an editorial:
I’ve now read the paper in detail
It is a science based commentary projecting authors’ viewpoints including 1. <<35k have actually died from covid 2. yet 225k-1.4m have already died from vaccines 3. With most of the paper describing why they think it is the tip of the iceberg
Their methodology for estimating vaccine caused death is hopelessly flawed, driven by an assumption that vaers death reporting is the same in the day or two after inoculation as it is months later.
This thread explores how time confouding can artificially inflate vaccine effectiveness (VE) estimates from observational data & make them misleading.
This may explain some reports earlier this year reporting 97-98%+ VE numbers, too high to be believable.
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The basic idea is: 1. Vaccination rates were very low in early 2021 2. COVID-19 infection/death rates were very high in early 2021 from winter surge
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3. Vaccination rates strongly increased moving from winter into spring/early summer 2021 4. COVID infection/death rates decreased moving from winter into spring/early summer coming off the winter surge and into the pre-Delta lull.
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Data presented below show nearly 33% of unvaccinated adult Israeli residents were previously infected.
Why is this important & has this contributed to misinterpretation of Israeli data?
This thread wll explore these questions.
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Israeli MoH releases periodic vaccination reports on its Telegram site. This table breaks down vaccination status by age groups as of September 14, 2021 listing total population and number given 1/2/3 doses plus those unvaccinated but recovered from previous infection 2/n
From these data, I constructed this table with % of population unvaccinated, given 1 dose, 2 doses, & 3 doses, & proportion of unvaccinated are previously infected.
Note that >30% of total unvaccinated Israelis were previously infected, & >1/3 for all age groups in 20-59yr 3/n
For older group, CFR for vaccinated (1.81%) is 3.3-fold LOWER than CFR for unvaccinated (5.96%)
For younger group, CFR for vaccinated (0.05%) is 1.5-fold higher than CFR for unvaccinated (0.03%), but there are only 13 deaths. 2/4
Another case of Simpson's paradox, since a confounding factor (age) is STRONGLY associated with both outcome (death) and exposure (vaccination status) given risk of death in old >>> young and vaccination rate old >>> young.
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How well are vaccines and boosters really protecting against COVID-19 deaths?
Israel MoH publicly posted daily COVID-19 death data split by unvaccinated, boosted, and vaccinated-not-boosted from Aug10-Sept8
Here are results of my analysis of these data
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Summing over all days, it is not promising to see so many COVID-19 deaths in vaccinated/boosted groups.
But by now we know better than to draw conclusions from raw counts, right? 2/n
The Israeli MoH dashboard provides enough information to infer total proportion of population unvaccinated, boosted, or vaccinated-by-not-boosted, so we can compute normalized COVID-19 death rates in these groups.