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
1/n
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.
3/n
From these, we can compute overall estimates of vaccine/booster effectiveness(VE) in preventing COVID-19 deaths relative to unvaccinated.
These overall VE estimates are VERY low; some might infer from this the vaccines and boosters are NOT protecting vs. COVID-19 deaths. 4/n
But don’t forget Simpson’s Paradox.
We see much lower vaccination/booster rates in the young, who also have MUCH lower rate of COVID-19 death.
This confounding of age might distort the overall VE estimates, so let’s compute separate estiamtes for each age group. 5/n
VE estimates by age are much higher than overall, showing indeed there was a strong Simpson effect.
Before interpreting these results, however, we need to consider one other thing: Do the <60yr data include children and, if so, should we pull them out into their own group? 6/n
Given the total counts for all ages sum to >9.1m, the total Israeli population, it is clear children are among the <60yr group, and we can infer the number <12yr from the MoH data.
They are unvaccinated, and unlikely to comprise any of the 23 COVID-19 deaths. 7/n
Splitting children out dramatically affects the VE estimates for the <60 group as well as overall.
It is CRUCIAL to separate children out when looking at vaccine effectiveness, since they cannot be vaccinated and have the lowest risk of advanced COVID-19 events. 8/n
Now consider the results.
For older group, we see vaccines reduced risk of COVID-19 deaths during this time period without boosters, but boosters clearly increased level of protection.
This is consistent with published papers showing early results from boosting. 9/n
For younger group, we see high protection vs. COVID-19 deaths from vaccines, and in these data no evidence boosters improve protection.
However, given only 7% boosted and not much time passed, it is possible that future data will show a booster benefit for young adults.
10/n
Repeating this analysis on “critical COVID-19 disease”, we see similar results.
The vaccines protect against critical disease, with older adults showing potential waning of efficacy improved by boosters, & younger adults showing strong protection irrespective of booster.
11/n
Two key caveats in these data: 1. It is not clear how this MoH data set counted individuals partially vaccinated with a single dose. 2. Also, MoH did not separate previously infected, who are either unvaccinated or partially vaccinated, which could attenuate VE estimates.
12/n
While informative, this analysis is limited given lack of access to important confounders other than age; Israeli research groups w/ access to more complete data can do more rigorous analyses.
My colleagues and I just published a paper in eClinicalMedicine evaluating effects of vaccination on long COVID risks in children and adolescents during the Delta and early Omicron periods.
These data were from the RECOVER network including 21 pediatric hospital networks from all over the USA, including 112,590 adolescents during the Delta period, and 84,735 adolescents and 188,894 children during the early Omicron period.
Long COVID-19 (post-acute sequelae of SARS-CoV-2, PASC, or multi-system inflammatory syndrom, MIS) was defined using a symptom-based computable phenotype definition based on five body systems.
Our analyses utilized propensity score weighting to adjust for confounding from age, demographics, medical co-morbidities as well as healthcare utilization including past COVID-19 testing practices, and we used proximal analyses with negative control exposures and outcomes to investigate and adjust for potential residual bias from unmeasured confounders.
In adolescents 12-20yrs, we found vaccination resulted in 95.4% reduced risk of long COVID-19 during the Delta period, and 75.1% during the Omicron period.
In children 5-11yrs, we found vaccination resulted in 60.2% reduced risk of long COVID-19 during he Omicron period.
To evaluate how much of this vaccine protection was from reduced risk of infection and how much was reduced risk of long COVID-19 independent of any effect in reducing infection, we performed a causal mediation analysis to split the total vaccine effect into indirect effects, mediated through reducing risk of infection, and direct effects, independent of any reduced risk of infection.
Again, propensity score weighting was used to carefully adjust for potential confounders.
We found that the protective effect of vaccines on long COVID-19 was almost wholly mediated through its reduced risk of infection.
Various sensitivity analyses were done and included in the online supplement along with a detailed description and explanation of all methods and modeling decisions.
These data were from the RECOVER network including 21 pediatric hospital networks from all over the USA, including 112,590 adolescents during the Delta period, and 84,735 adolescents and 188,894 children during the early Omicron period
Our analyses utilized propensity score weighting to adjust for confounding from age, demographics, medical co-morbidities as well as healthcare utilization including past COVID-19 testing practices, and we used proximal analyses with negative control exposures and outcomes to investigate and adjust for potential unmeasured confounders.
Earlier this month, a research group from University of Southern California published a paper studying long term (>1000 days) risk of major adverse cardiac events (MACE, including myocardial infarction, stroke, and all cause mortality) after documented COVID-19 infections from population level data from the UK Biobank.
Confirming many other studies, they found increased risk of MACE after COVID-19, 2.09x higher for all levels of severity and 3.65x higher in hospitalized COVID-19.
Notably, they found that hospitalization for COVID-19 was a coronary artery disease risk equivalent, such that a person with no history of cardiovascular disease who got hospitalized COVID-19 was higher risk than a person with history of cardiovascular disease without hospitalized infection.
This, of course, validates what has been found in many other studies -- that COVID-19 infected have increased risk of severe cardiovascular events even after recovery, especially if they had severe/hospitalized COVID-19, and explains the increased cardiac risk in the past few years.
BTW, this study covers infections in 2020, before vaccines were available.
The study was quite well designed, using n=10,005 COVID-19 cases between February 1, 2020 and December 31, 2020 in the UK Biobank, compared with population controls (n=217,730) and matched controls (n=-38,660) based on propensity scores including age, sex, ethnicity, education, diabetes, asthma, smoking status, and use of lipid-lowering or antihypertension medication.
The comparison with the propensity score-matched controls is more valid for estimating COVID-19 effects given that it adjusts for confounders.
They found that with >1000 days of followup, the risk of MACE was 3.65x higher in hospitalized COVID-19 group than matched controls.
They computed the hazard ratio of MACE in those with cardiovascular comorbidities and/or hospitalized COVID-19 infections relative to those not infected with COVID-19 and without diabetes, peripheral artery disease, or cardiovascular disease.
They found that among uninfected, diabetes increased risk by 1.88x, peripheral aterial disease by 5.08x, and existing cardiovascular disease by 5.63.
Those with hospitalized COVID-19 but no cardiovascular comorbidities had 7.04x increased risk of MACE, meaning the hospitalized COVID-19 status by itself with no prior cardiovascular comorbidities made one have an even greater risk of MACE than those with cardiovascular comorbidities but no hospitalized COVID-19.
A group of French researchers published a paper in JAMA today assessing long term cardiac outcome with 18 months after vaccine-caused myocarditis after mRNA vaccines and compared with post-covid-19 mycarditis and conventional myocarditis using a large whole-country cohort covering the entire 12-49 year old population of France.
They found 558 cases of post-vaccine myocarditis out of ~64 million doses of vaccine in this age group (376 after 2nd dose), for an incidence of 1 in 115k doses (1 in 64k after 2nd dose), and 298 with post-COVID myocarditis and 3779 with conventional myocarditis.
A total of 18/15/1 of the 558 post-vaccine myocarditis patients were rehospitalized for myocarditis, had other cardiovascular events, or all cause death, versus 12/22/4 of 298 post-covid myocarditis patients and 277/49/17 of 3779 conventional myocarditis patients.
After rigorously adjusting for confounders including age, sex, region, SES, lifestyle habits, comorbidities, vaccination history, and medications using propensity score weighting to calibrate all populatons to the conventional myocarditis group (the comparison group), they statistically compared the post-vaccine and post-covid groups to the conventional myocarditis group with respect to (1) Rehospitalization with myocarditis (2) Cardiac events, including heart failure, heart rhythm and conduction disorders, and cardiomyopathy (3) All cause death (4) Rehospitalization for any reason (5) Composite outcomes (1)-(3) (6) Composite outcomes (1)-(4)
From this comparison, they found the risk of all of these 6 events were all lower after post-vaccine myocarditis than conventional myocarditis by 25%/46%/47%/31%/45%/36%, respectively, while risk after post-covid myocarditis was similar to conventional myocarditis, at the higher levels.
Myocarditis is the key minority harm risk for mRNA vaccines, especially for young men and especially after 2nd dose.
Before this study, there were very little looking at moderate to long term cardiac outcomes of myocarditis, so this paper is an important addition to the literature.
More study of this important question is needed.
In this thread, I discuss a few of the details and strengths and limitations of this study.
SARS-CoV-2 vaccines have been shown by many studies to greatly reduce the morbidity and mortality from COVID-19 during the pandemic, especially during 2021-2022. mRNA vaccines have been the predominate type used in many places around the world, and has consistently shown the highest effectiveness in most studies.
However, within a few months of rollout, a key minority harm risk of myo/pericarditis was discovered to occur in a subset of individuals soon after vaccination, with rates highest in teen boys and young men, especially after 2nd dose given shortly after 1st dose, and with Moderna having the highest rate. It is important to weight this risk against the benefits, especially in young men who have lower risks of severe/fatal COVID-19.
While most cases appeared to be mild and quickly resolved, myocarditis is serious and there is always a risk of cardiovascular sequelae after myocarditis, so long term follow up studies are critical to assess potential long term cardiac damage in those experiencing post-vaccine myocarditis.
This study involves a whole-France 12-49 year old cohort, with all individuals hospitalized for myocarditis between December 27, 2020 and June 30, 2022, with extensive demographic and medical variables for these individuals analyzed in this study.
The myocarditis patients were separated into 3 groups: (1) post-vaccine myocarditis (hospitalized within 7 days of a vaccine dose) (2) post-covid mycarditis (hospitalized within 30 days of a documented covid infection, but not within 7 days of a vaccine dose) (3) conventional myocarditis -- not meeting the criteria of (1) or (2).
There were a total of 558 cases of post-vaccine myocarditis out of ~64 million doses of vaccine in this age group (376 after 2nd dose), for an incidence of 1 in 115k doses (1 in 64k after 2nd dose).
There were a total of 298 with post-COVID myocarditis and 3779 with conventional myocarditis.
The post-vaccine myocarditis group was younger, more male, and fewer comorbidities than the post-covid or conventional myocarditis groups.
How can excess deaths be higher in 2021 in 2020 if vaccines had any benefit?
This is a good question I see many ask.
Some conclude from this question that vaccines must have been completely ineffective, or perhaps even have made things worse.
In this thread, I will show that this is not the contradiction that it appears to be.
If you look at the available data and studies and think through the various relevant factors, it is clear that the following are simultaneously true: 1. Excess deaths in the world were higher in 2021 than 2020 2. Vaccines were highly effective in reducing risk of covid death, the primary driver of excess deaths. 3. The excess deaths in 2021 would have been MUCH WORSE had there not been covid vaccines.
The key factors I will highlight in this thread include: 1. Far more people were exposed to COVID-19 in 2021 than 2020 2. In most places, the strict containment measures of 2020 were lifted in 2021 3. The variants emerging in 2021 were demonstrably more transmissible than those in 2020 4. The vast majority of people in the world were unvaccinated for most of 2021 5. Vaccines were highly effective in 2021, but not perfect.
1. Far more people were exposed to COVID-19 in 2021 than 2020
While the pandemic first emerged and was most disruptive in 2020, relatively few people were actually exposed to SARS-CoV-2 in 2020.
Below are plots of confirmed COVID-19 cases over time in the world from OWID
We see that only 1% (10k per 1m) of the world had confirmed COVID-19 cases in 2020, while another 2.5% (25k per 1m) had confirmed COVID-19 cases in 2021.
So we see 2.5x more confirmed COVID-19 cases in 2021 than 2020, with 2021 a full pandemic year and 2020 only a partial pandemic year.
Of course, most SARS-CoV-2 infections are not formally documented as confirmed cases, so more than 1% were exposed to SARS-CoV-2 in 2020.
Serology studies from around the world provide more information about what % were exposed to SARS-CoV-2.
Serology tests measure SARS-CoV-2 antibodies in the blood to measure whether an individual shows evidence of exposure to SARS-CoV-2, whether or not they were ever documented as a confirmed case.
Bobravitz et al. (2021) published a meta-analysis of 968 serology studies with >9 million participants from 74 countries all over the world.
They found that the median seroprevalence ranged from 0.6% in East Asia to 19.5% for Sub-Saharan Africa, with high-income countries including Western Europe and the USA having median seroprevalence 4.1%.
Seroprevalence studies are notoriously difficult to conduct to get unbiased estimates of population exposure, but whatever the precise numbers are, this meta-analysis makes it clear that the VAST MAJORITY of people in the world were not exposed to SARS-CoV-2 in 2020.
Mostert et al. published a paper in BMJ Public Health “Excess Mortality across countries in the Western World since the COVID-19 pandemic: ‘Our World in Data’ estimates of January 2020 to December 2022”
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The paper presents excess death estimates for 47 Western countries from the publicly available “World Mortality Dataset” (Karlinsky and Kobak, 2021) and reports excess deaths from 2020-2022, with 13 countries peaking in 2020, 21 in 2021, and 12 in 2022.
Their conclusion expresses surprise that excess deaths continued from 2020 into 2021 and 2022 “despite the implementation of containment measures and COVID-19 vaccines” claiming “this raises serious concerns.”
They discuss several potential causes of excess deaths, but do not delve into any detail about the evidence or lack thereof for any of them based on existing literature and data.
Their conclusion is that “government leaders and policymakers need to thoroughly investigate the underlying causes of persistent excess mortality”, implying there is not already substantial evidence for what the primary driving factor is, and that studies investigating potential causes of excess deaths are not being done.
Overall, I welcome any call for more studies characterizing how the pandemic affected mortality rates and investigating potential primary and secondary contributing factors. I’m always in favor of more data and studies (and that they are appropriately analyzed using valid statistical approaches).
However, this study does not accurately represent the existing understanding about sources of excess deaths, downplaying the COVID-19 deaths that are clearly the driving factor throughout 2020-2022, as I will show, and implicitly magnifying the potential role of vaccines beyond what is supported by the data.
Also, many popular media articles about this study, including the Telegraph article () entitled “Covid vaccines may have helped fuel rise in excess deaths”, blatantly misrepresent the content of the paper.
They make it sound as if the paper was primarily about vaccines, which it is not, or provides evidence for vaccines being a potential driving factor, which it does not.
This misrepresentation is so egregious that BMJ felt the need to post a statement about it() and, who knows, may be considering retraction of the article.
First, I am not sure why this article is classified as “original research” and not a “narrative review” or “commentary”.
There is no primary data collection or original data analysis in this paper.
The study design and text and equations for the methods are almost verbatim from the public repository for the World Mortality Data set (WMD, Karlinsky and Kobak 2021 ) which is also where they got their data. The authors cite the paper, but it is highly unusual in an “original research” article to have such large sections match so closely with an existing publication and with nothing new added.
Their results are simply the publicly available excess deaths from Karlinsky and Kobak’s WMD for 47 countries, aggregating by month and year to get total excess counts in 2020, 2021, and 2022, with the results simply showing that there were excess deaths in 2020, 2021, and 2022, which has been well known for a long time.
I have no idea how BMJ Public Health considered this manuscript sufficiently novel for publication as an “original article”.
The remainder of the paper consists of a narrative-driven review of various aspects of the pandemic and a commentary suggesting further investigation of causes of excess deaths, following the format of a “narrative review” or “commentary”, not an original research article.elifesciences.org/articles/69336
Outside of the fact that the work is not original, there is nothing wrong with presenting excess deaths data by 2020, 2021, and 2022.
While the paper closely tracks with Karlinsky and Kobak’s work in many ways, it ignores one of the primary points made in Karlinsky and Kobak’s article: the fact that the excess deaths track so closely with covid deaths.
Below I plot the WMD excess death data from Karlinsky and Kobak (black) overlaid with covid-attributed deaths (red) and vaccines given (blue) for 100 countries from all over the world, including most of the 47 Western nations in this paper plus many others (and these plots go all the way through the end of 2023).
It is clear from looking at these data that: 1. High excess deaths predominately occur in spikes. 2. These spikes precisely correspond to spikes in COVID-attributed deaths 3. These spikes are during times of local COVID-19 waves
This close correspondence makes it clear that these “COVID-attributed deaths” are the primary drivers of excess deaths not just in 2020, but throughout 2021 and 2022, as well.
Failure to acknowledge this is a glaring omission in this paper.
In this thread I will make some comments on the recently published paper in Cureus entitled "Increased age-adjusted cancer mortality after the third mRNA lipid nanoparticle vaccine dose during the covid-19 pandemic"
The title is extremely misleading, given their data do not show an increase in age adjusted cancer mortality, and the paper provides no evidence relating the cancer mortality trends to the 3rd doses of mRNA vaccines given in the country outside of simple post hoc arguments based on the fact they were given in 2022.
Their paper shows that the age-adjusted cancer mortality remains stable and in fact slightly decreases, but it decreases at a slower rate than predicted by linearly extrapolating pre-pandemic decreases in cancer mortality from 2010-2019.
They don't provide any evidence that the vaccinated or those receiving 3rd dose boosters are at any higher risk of cancer death than those of similar age/co-morbidity status who didn't, or otherwise provide any evidence that vaccination is responsible for the arrest of the pre-pandemic decreasing trend and not any one of the many other factors greatly impacting life in Japan during the pandemic.
While the paper summarizes a large and important data set and does some nice things (like compute age-adjusted rates), the general conclusions they make, and certainly the conclusions that people are representing about the paper on social media, are not supported by the data.
This paper analyzes a large data set of population-level cancer death rates in a large country, Japan, and this type of large data set is valuable for assessing trends during the pandemic.
The authors duly recognize that changing age distributions over time impact the cancer incidence and death rates, so compute age-adjusted cancer mortality estimates which is the right approach to assess changes over time.
They also looked at subgroup analyses by cancer type and age, which provide useful breakdowns in smaller groups that can shed light on the trends.
However, the paper does not show a total increase in age-adjusted cancer death rate in Japan during the pandemic, and certainly not from 2021 to 2022 when "3rd doses" were given, in spite of what its title implies.
As can be seen in their own data, the age-adjusted rates were actually stable throughout the pandemic from 2020 to 2021 when the first 2 vaccine doses were given and 2022 when the 3rd doses were given to some, and in fact the age-adjusted cancer death rate actually decreased from 2021 to 2022.
They do show "excess deaths" increased from 2020 to 2021 and then 2022.
So where do these excess cancer deaths come from if not from increasing cancer death rates?