As I have said so many times before, we should not lose sight of who has the burden of proof. Those who brought this intervention have absolute obligation to prove they are both safe and effective to acceptable standards (i.e. at least 95% confidence, 99% in the case of some medical interventions). The fact that we can actually prove the opposite (that they are both unsafe and ineffective), in spite of their feeble attempts to rubbish our analyses, demonstrates how impossible it is for this product to remain on the market for so long, let alone be funded with public money and even mandated in some circumstances. It is blatantly criminal. anyone still buying this BS needs to be in a lunatic asylum or jail.
I used the same CSV file as Uncle John Returns to calculate an age-normalized proportion of the "indication chronic illness" column by vaccine brand. Relative to the proportion among all vaccinated people, my excess proportion was about -26% for people whose first dose had the type "Comirnaty" (Pfizer) but about 55% for the type "SPIKEVAX" (Moderna): sars2.net/czech3.html#People_who_were_eligible_to_be_vaccinated_early_due_to_a_chronic_illness.
When I looked at third doses instead of first doses and I aggregated Omicron and pediatric vaccine types together with the main vaccine type, my excess proportion of the "indication chronic illness" column was about -6% for Pfizer but 38% for Moderna.
When I calculated a Moderna-Pfizer ratio for an age-normalized proportion of the "indication chronic illness" column so that I grouped the ratio by the month when people got the first dose, the ratio remained at a fairly steady level of about 5 to 6 for people who got the first dose in May to October 2021, but the ratio suddenly dropped to about 2.3 in November and it remained around 1 to 1.5 for the next 4 months. So it might also partially explain why the Moderna-Pfizer mortality ratio dropped to around 1.0 in people who were vaccinated in the fourth quarter of 2021 (even though the drop in the mortality ratio was already in October and not November).
Your list at the top says that Pfizer had a lower mortality rate than Moderna for every month of injection. But when I calculated an age-normalized Moderna-Pfizer mortality ratio by the month of the first dose, the ratio was about 0.93 in people who got the first dose in October 2021:
I don't think it's just noise caused by a small sample size either, because there were about 100,000 people who got a first dose from a Pfizer or Moderna vaccine in October 2021.
Imo they're all deadly, some more deadly than others. God help us if this injectable / sprayable / self-replicating / shedding contaminating goopy junk is the future of pharma / politico 'healthcare' for humans and food chain livestock. I hope the wildlife run for the hills (where aerial spraying will get them anyways) 😕
Dr. Clare Craig, any chance you know anything about Dr. John Campbell. He hasn't posted anything in two weeks. A lot of us are concerned. It's not like him. Thanks.
This thread plots the excess deaths and excess chronic illness of Moderna relative to Pfizer across the months of 2021 for various age groups, as well as the absolute numbers of excess deaths and excess chronic illnesses in Moderna relative to Pfizer for the first 12m after the rollout.
This thread also presents the same plots and discussed their implications:
1. The excess deaths track closely with the excess chronic illnesses for each age group.
2. For all age groups, they are heavily concentrated in the first 6 months of 2021, which is when only those with chronic illness even had access to vaccines for the <55yr age groups.
It is VERY clear that chronic illness is a major confounder, and in fact along with age appears to explain a huge proportion of the Moderna "excess deaths" relative to Pfizer.
Of course there are likely even more confounders other than age/chronic illness here, but it is clear that your statement that it is "like a cluster randomized trial" between Moderna and Pfizer (implying no confounding and any difference is causal vaccine harm effect) is patently absurd and completely unsupported by these data.
Dr. Craig, the images above for age bands 40 and up all have 1.000 as the mortality rate ratio, but that must be a glitch, because the actual mortality rates were not equal between Pfizer and Moderna (only equal rates lead to ratio values of 1.000).
On this page for Czech vaccination statistics, there's 285,232 vaccinated people who have the "indication" of chronic illness (which is identical to the number of rows in the ockovani-profese.csv file where the indikace_chronicke_onemocneni column is true and the dose number is 1): https://ockovani.opendatalab.cz/statistiky_ockovani#ockovani-indikace. However there's another table which shows that there's 273,374 vaccinated people in the "priority group" of chronic illness. I don't know how the priority group and indication group are different. A tooltip for the indication of chronic illness included the following text in Czech: "Chronically ill (hemato-oncological disease, oncological disease (solid tumors), serious acute or long-term heart disease, serious long-term lung disease, diabetes mellitus, obesity, serious long-term kidney disease, serious long-term liver disease, status after transplantation or on the waiting list, hypertension, seriousltip neurological or neuromuscular disease, congenital or acquired cognitive deficit, rare genetic disease, severe weakening of the immune system, other serious diseases)." But the tooltip for the priority group of chronic illness simply said "A person with a chronic illness".
But anyway, one explanation for why there's so few people who have the indication of chronic illness might be if it only includes serious chronic illnesses, even though the list of chronic illnesses in the tooltip also included hypertension, which alone should have a prevalence of more than the total percentage of people with the "indication" of chronic illness. And it wouldn't explain why the "indikace_chronicke_onemocneni" column is true for only about 1% of first doses given to ages 80+ but about 11% of first doses given to ages 65-69.
This PDF describes the "infectious disease information system" that is used in the Czech Republic ("Informační systém infekční nemoci", ISIN): https://vladci.cz/archive/covid/106/UZIS_2022-02_Struktura_NZIS_106.pdf. The PDF includes a list of fields which are contained in a database for COVID-19 cases, which also includes a module for COVID vaccinations. The complete list of the "indications" that are included in the vaccination module includes several professional categories, categories for disease groups, and age categories.
But anyway, I guess another reason why the percentage of people who are indicated as having a chronic illness is so low might be if information about chronic illnesses was not added to the database for all people. It might also be that the data about chronic illnesses was commonly entered for people who were in a priority group for vaccination because of a chronic illness, but it was less common for chronic illnesses to be filled in for other groups of people (which might explain why the number of people who had the indication of a chronic illness was only about 4% higher than the number of people who were in the priority group for a chronic illness).
In the file ockovani-registrace.csv which includes one row for each vaccinated person ("COVID-19: Overview of registrations by vaccination sites in the Czech Republic"), there's a column called "povolani" (profession): https://onemocneni-aktualne.mzcr.cz/api/v2/covid-19. The column also includes a couple of other values besides professions. For about 6 million people, the value of the field is "based on age", for about 1 million "not specified", for about 300,000 "a person with a chronic illness", for about 300,000 "teaching staff", and so on.
Each person has only one value for the field, so maybe if a person qualified to be vaccinated because of their age, then the qualification for chronic illness was not additionally included in the file. And if a similar system was used in the ockovani-profese.csv file, it might explain why the oldest age groups have such a low percentage of people who are indicated to have a chronic illness.
Here's the complete list of translated values of the "profession" column:
Count;Translation
6037598;Based on age
912596;not specified
305888;A person with a chronic illness
275259;Teaching staff/non-teaching staff
79837;Critical infrastructure
70863;Healthcare worker according to §76 and §77 of Act 372/2011 Coll.
39777;Self-paying
30231;A person with a chronic disease - in the care of a specialized center
26026;Employees of the Ministry of Defense
25530;University academic worker
21521;Worker in social services
5486;A person caring for a person in III. or IV. degree of dependence
1813 Non-health care workers involved in the provision of health care and care for COVID-19 positive persons
1602;THP workers in hospitals
So there's 305,888 people who are listed as having a chronic illness along with 30,231 people who are listed as having a chronic illness and being in the care of a specialized center. In the ockovani-profese.csv file there's only 285,232 rows for first doses where the indikace_chronicke_onemocneni field is true (even though maybe there would be more unique people where the field would be true for at least one dose, but it's not possible to tell because the file doesn't have a way to identify which doses belong to the same person).
There are just 164 lots (or batches) associated with deaths in broadest possible terms. The data seems to be intentionally obfuscated to hide this. Once the resolution is reduced to these just 164 batches, the picture becomes clear. We can also combine the picture with other official data from the Czech republic to get glimpse into what batches are hidden in the dataset. https://shlomokafka.substack.com/p/the-czech-data-seems-to-be-intentionally
There's also a chicken-egg scenario. Did the shots cause co-morbidities prior to death?
For example, lets say Person A gets a Pfizer shot, and due to blood clots, has to have an arm amputated (not unreasonable: there are cases of quadruple amputees, supposedly 'from COVID' that happen after the shots are taken). The person later dies - would this be counted as a 'co-morbidity'?
I think the burden of proof lies on the individuals making the claim co-morbidities existed as the sole or main factor, rather than the burden on disproving it (by default, we must assume individuals are healthy unless otherwise proven: being old does not necessarily automatically mean they're unwell or ill or disabled).
They would need to establish:
1) Co-morbidities existed prior to the taking of SARS-CoV-2 shots
2) Co-morbidities were not likely caused by some other vaccine (E.G. narcolepsy caused by the 2009 Swine Flu shot), and
3) Co-morbidities were majority or solely responsible for death
Per my previous private messages, I have also noted anomalies in the dataset but performed an analysis, you may wish to review it:
The mortality rate in the vaccinated vs unvaccinated is too low and can only be explained by the dying deciding not be vaccinated or misclassification.
It ruins the unvaccinated as a control group which is why we're comparing brands instead.
Well, we know in the UK you were classed as unvaccinated up to 14 days after every single shot, irrespective of how many you had previously had. No doubt other countries used a similar classification system.
But vaccinated die at lower rates in the first 14 days due to HVE, so again this wouldn't increase all-cause unvaxxed deaths. It would make them look BETTER.
Plus, someone close to death wouldn't get vaccinated anyway.
Which has been part of my point elsewhere about doing an analysis by place of death.
For starters, you would remove everyone who died in a hospice facility. Moreover, I'm not sure that care home residents should automatically be counted in such an analysis.
I'm no fan of the COVID shot for multiple reasons, but that doesn't mean analysis shouldn't be rigorous.
In the Czech data you are vaccinated the day you got your first dose. It's record level data with date of first dose.
The 14 day nonsense actually hurts the unvaccinated as the vaccinated have a lower all-cause mortality rate initially because of temporal HVE.
So if people are considered unvaxxed for 14 days that would actually artificially HELP unvaccinated when looking at all-cause.
Actual data shows that there's a reduced number of deaths in the first couple of weeks after vaccination for the vaccinated, like Barry Young's NZ data, the ONS data, the NZ OIA data, Kirsch's Medicare data, Kirsch's Maldives data, and the Israeli MoH data.
What makes you think that has any relevance for these Czech data?
The data set if you look at it has actual death date and actual details of every vaccine dose -- date, brand, batch, etc., so there is absolutely no "misclassification" as you can verify for yourself by looking at the publicly shared data set.
As I have said so many times before, we should not lose sight of who has the burden of proof. Those who brought this intervention have absolute obligation to prove they are both safe and effective to acceptable standards (i.e. at least 95% confidence, 99% in the case of some medical interventions). The fact that we can actually prove the opposite (that they are both unsafe and ineffective), in spite of their feeble attempts to rubbish our analyses, demonstrates how impossible it is for this product to remain on the market for so long, let alone be funded with public money and even mandated in some circumstances. It is blatantly criminal. anyone still buying this BS needs to be in a lunatic asylum or jail.
Love it. GREAT POINT.
LOL
https://x.com/jsm2334/status/1815411926211383738
I used the same CSV file as Uncle John Returns to calculate an age-normalized proportion of the "indication chronic illness" column by vaccine brand. Relative to the proportion among all vaccinated people, my excess proportion was about -26% for people whose first dose had the type "Comirnaty" (Pfizer) but about 55% for the type "SPIKEVAX" (Moderna): sars2.net/czech3.html#People_who_were_eligible_to_be_vaccinated_early_due_to_a_chronic_illness.
When I looked at third doses instead of first doses and I aggregated Omicron and pediatric vaccine types together with the main vaccine type, my excess proportion of the "indication chronic illness" column was about -6% for Pfizer but 38% for Moderna.
When I calculated a Moderna-Pfizer ratio for an age-normalized proportion of the "indication chronic illness" column so that I grouped the ratio by the month when people got the first dose, the ratio remained at a fairly steady level of about 5 to 6 for people who got the first dose in May to October 2021, but the ratio suddenly dropped to about 2.3 in November and it remained around 1 to 1.5 for the next 4 months. So it might also partially explain why the Moderna-Pfizer mortality ratio dropped to around 1.0 in people who were vaccinated in the fourth quarter of 2021 (even though the drop in the mortality ratio was already in October and not November).
Your list at the top says that Pfizer had a lower mortality rate than Moderna for every month of injection. But when I calculated an age-normalized Moderna-Pfizer mortality ratio by the month of the first dose, the ratio was about 0.93 in people who got the first dose in October 2021:
library(data.table)
b=fread("http://sars2.net/f/czbucketskeep.csv.gz")[dose<=1][,age:=pmin(age,95)]
d=b[,.(dead=sum(dead),alive=sum(as.double(alive))),.(type,vaxmonth,age)]
d=merge(d,d[,.(base=sum(dead)/sum(alive)),age])[,base:=base*alive]
a=d[,.(rat=sum(dead)/sum(base)),.(type,vaxmonth)]
m=a[,tapply(rat,.(vaxmonth,type),c)]
round(m[,"Moderna"]/m[,"Pfizer"],2)
I don't think it's just noise caused by a small sample size either, because there were about 100,000 people who got a first dose from a Pfizer or Moderna vaccine in October 2021.
This triangle plot shows the Moderna-Pfizer ratio by both month of vaccination and month of death: sars2.net/czech2.html#Triangle_plot_of_Moderna_Pfizer_ratio.
Imo they're all deadly, some more deadly than others. God help us if this injectable / sprayable / self-replicating / shedding contaminating goopy junk is the future of pharma / politico 'healthcare' for humans and food chain livestock. I hope the wildlife run for the hills (where aerial spraying will get them anyways) 😕
Dr. Clare Craig, any chance you know anything about Dr. John Campbell. He hasn't posted anything in two weeks. A lot of us are concerned. It's not like him. Thanks.
Clare: you really need to check the analysis done in this thread: https://x.com/UncleJo46902375/status/1815376086877773965
This thread plots the excess deaths and excess chronic illness of Moderna relative to Pfizer across the months of 2021 for various age groups, as well as the absolute numbers of excess deaths and excess chronic illnesses in Moderna relative to Pfizer for the first 12m after the rollout.
This thread also presents the same plots and discussed their implications:
https://x.com/jsm2334/status/1815411926211383738
These clearly show that:
1. The excess deaths track closely with the excess chronic illnesses for each age group.
2. For all age groups, they are heavily concentrated in the first 6 months of 2021, which is when only those with chronic illness even had access to vaccines for the <55yr age groups.
It is VERY clear that chronic illness is a major confounder, and in fact along with age appears to explain a huge proportion of the Moderna "excess deaths" relative to Pfizer.
Of course there are likely even more confounders other than age/chronic illness here, but it is clear that your statement that it is "like a cluster randomized trial" between Moderna and Pfizer (implying no confounding and any difference is causal vaccine harm effect) is patently absurd and completely unsupported by these data.
You have time to look at this article from Mr.Geoff (thank you) https://open.substack.com/pub/geoffpain/p/czechia-pfizer-covid19-jabs-and-harms?r=ykqw5&utm_medium=ios
🇦🇺💉On the GMO case in Australia, ARR, the fast tracked approval process and more. Video is 23 minutes long. https://open.substack.com/pub/ianbrighthope/p/covid-lessons-for-our-leaders?r=20pd6j&utm_medium=ios
Dr. Craig, the images above for age bands 40 and up all have 1.000 as the mortality rate ratio, but that must be a glitch, because the actual mortality rates were not equal between Pfizer and Moderna (only equal rates lead to ratio values of 1.000).
I also reported on your summary numbers for age 40-70 here [ https://deepd1ve.substack.com/p/maimed ]
On this page for Czech vaccination statistics, there's 285,232 vaccinated people who have the "indication" of chronic illness (which is identical to the number of rows in the ockovani-profese.csv file where the indikace_chronicke_onemocneni column is true and the dose number is 1): https://ockovani.opendatalab.cz/statistiky_ockovani#ockovani-indikace. However there's another table which shows that there's 273,374 vaccinated people in the "priority group" of chronic illness. I don't know how the priority group and indication group are different. A tooltip for the indication of chronic illness included the following text in Czech: "Chronically ill (hemato-oncological disease, oncological disease (solid tumors), serious acute or long-term heart disease, serious long-term lung disease, diabetes mellitus, obesity, serious long-term kidney disease, serious long-term liver disease, status after transplantation or on the waiting list, hypertension, seriousltip neurological or neuromuscular disease, congenital or acquired cognitive deficit, rare genetic disease, severe weakening of the immune system, other serious diseases)." But the tooltip for the priority group of chronic illness simply said "A person with a chronic illness".
But anyway, one explanation for why there's so few people who have the indication of chronic illness might be if it only includes serious chronic illnesses, even though the list of chronic illnesses in the tooltip also included hypertension, which alone should have a prevalence of more than the total percentage of people with the "indication" of chronic illness. And it wouldn't explain why the "indikace_chronicke_onemocneni" column is true for only about 1% of first doses given to ages 80+ but about 11% of first doses given to ages 65-69.
This PDF describes the "infectious disease information system" that is used in the Czech Republic ("Informační systém infekční nemoci", ISIN): https://vladci.cz/archive/covid/106/UZIS_2022-02_Struktura_NZIS_106.pdf. The PDF includes a list of fields which are contained in a database for COVID-19 cases, which also includes a module for COVID vaccinations. The complete list of the "indications" that are included in the vaccination module includes several professional categories, categories for disease groups, and age categories.
But anyway, I guess another reason why the percentage of people who are indicated as having a chronic illness is so low might be if information about chronic illnesses was not added to the database for all people. It might also be that the data about chronic illnesses was commonly entered for people who were in a priority group for vaccination because of a chronic illness, but it was less common for chronic illnesses to be filled in for other groups of people (which might explain why the number of people who had the indication of a chronic illness was only about 4% higher than the number of people who were in the priority group for a chronic illness).
In the file ockovani-registrace.csv which includes one row for each vaccinated person ("COVID-19: Overview of registrations by vaccination sites in the Czech Republic"), there's a column called "povolani" (profession): https://onemocneni-aktualne.mzcr.cz/api/v2/covid-19. The column also includes a couple of other values besides professions. For about 6 million people, the value of the field is "based on age", for about 1 million "not specified", for about 300,000 "a person with a chronic illness", for about 300,000 "teaching staff", and so on.
Each person has only one value for the field, so maybe if a person qualified to be vaccinated because of their age, then the qualification for chronic illness was not additionally included in the file. And if a similar system was used in the ockovani-profese.csv file, it might explain why the oldest age groups have such a low percentage of people who are indicated to have a chronic illness.
Here's the complete list of translated values of the "profession" column:
Count;Translation
6037598;Based on age
912596;not specified
305888;A person with a chronic illness
275259;Teaching staff/non-teaching staff
79837;Critical infrastructure
70863;Healthcare worker according to §76 and §77 of Act 372/2011 Coll.
39777;Self-paying
30231;A person with a chronic disease - in the care of a specialized center
26026;Employees of the Ministry of Defense
25530;University academic worker
21521;Worker in social services
5486;A person caring for a person in III. or IV. degree of dependence
1813 Non-health care workers involved in the provision of health care and care for COVID-19 positive persons
1602;THP workers in hospitals
So there's 305,888 people who are listed as having a chronic illness along with 30,231 people who are listed as having a chronic illness and being in the care of a specialized center. In the ockovani-profese.csv file there's only 285,232 rows for first doses where the indikace_chronicke_onemocneni field is true (even though maybe there would be more unique people where the field would be true for at least one dose, but it's not possible to tell because the file doesn't have a way to identify which doses belong to the same person).
There are just 164 lots (or batches) associated with deaths in broadest possible terms. The data seems to be intentionally obfuscated to hide this. Once the resolution is reduced to these just 164 batches, the picture becomes clear. We can also combine the picture with other official data from the Czech republic to get glimpse into what batches are hidden in the dataset. https://shlomokafka.substack.com/p/the-czech-data-seems-to-be-intentionally
Do you have the data by place/setting of death?
There's also a chicken-egg scenario. Did the shots cause co-morbidities prior to death?
For example, lets say Person A gets a Pfizer shot, and due to blood clots, has to have an arm amputated (not unreasonable: there are cases of quadruple amputees, supposedly 'from COVID' that happen after the shots are taken). The person later dies - would this be counted as a 'co-morbidity'?
I think the burden of proof lies on the individuals making the claim co-morbidities existed as the sole or main factor, rather than the burden on disproving it (by default, we must assume individuals are healthy unless otherwise proven: being old does not necessarily automatically mean they're unwell or ill or disabled).
They would need to establish:
1) Co-morbidities existed prior to the taking of SARS-CoV-2 shots
2) Co-morbidities were not likely caused by some other vaccine (E.G. narcolepsy caused by the 2009 Swine Flu shot), and
3) Co-morbidities were majority or solely responsible for death
Per my previous private messages, I have also noted anomalies in the dataset but performed an analysis, you may wish to review it:
https://thedailybeagle.substack.com/p/deep-dive-of-the-deaths-dataset
Joel Smalley was able to show that misclassification could account for the difference, though that was a highly unlikely reason, but not impossible.
He is right.
The mortality rate in the vaccinated vs unvaccinated is too low and can only be explained by the dying deciding not be vaccinated or misclassification.
It ruins the unvaccinated as a control group which is why we're comparing brands instead.
"can only be explained by the dying deciding not be vaccinated or misclassification."
No, that can't be the only reason for the difference and certainly isn't the only reason.
Well, we know in the UK you were classed as unvaccinated up to 14 days after every single shot, irrespective of how many you had previously had. No doubt other countries used a similar classification system.
It was the same in the US
And it's why "unvaccinated" deaths are so high - they're not unvaccinated at all, but within the 14 day post jab period.
But vaccinated die at lower rates in the first 14 days due to HVE, so again this wouldn't increase all-cause unvaxxed deaths. It would make them look BETTER.
We don't know that.
Plus, someone close to death wouldn't get vaccinated anyway.
Which has been part of my point elsewhere about doing an analysis by place of death.
For starters, you would remove everyone who died in a hospice facility. Moreover, I'm not sure that care home residents should automatically be counted in such an analysis.
I'm no fan of the COVID shot for multiple reasons, but that doesn't mean analysis shouldn't be rigorous.
100% false. In the UK for all-cause/Covid mortality you are considered vaccinated the day you got your first dose.
https://x.com/Sarah__Caul/status/1634184181541478401
In the Czech data you are vaccinated the day you got your first dose. It's record level data with date of first dose.
The 14 day nonsense actually hurts the unvaccinated as the vaccinated have a lower all-cause mortality rate initially because of temporal HVE.
So if people are considered unvaxxed for 14 days that would actually artificially HELP unvaccinated when looking at all-cause.
Actual data shows that there's a reduced number of deaths in the first couple of weeks after vaccination for the vaccinated, like Barry Young's NZ data, the ONS data, the NZ OIA data, Kirsch's Medicare data, Kirsch's Maldives data, and the Israeli MoH data.
https://x.com/henjin256/status/1766616346945614219
What makes you think that has any relevance for these Czech data?
The data set if you look at it has actual death date and actual details of every vaccine dose -- date, brand, batch, etc., so there is absolutely no "misclassification" as you can verify for yourself by looking at the publicly shared data set.