Vaccine safety “no evidence”.
July 24 2021
kograt at gmail
Vaccine safety “no evidence”
There is the spike of weekly count for unclassified death which is could be predicted with weekly administered vaccine doses.
Vaccines are lost it efficiency for preventing weekly COVID death in mid of Spring 2021.
Note: Drop in weekly death count is due to underreport.
Mortality estimate
Predictor for unclassified death corresponds to 111 death per million administered doses with 9 weeks lag.
Vaccine efficiency
There is no correlation between weekly administered doses and weekly COVID death in April 2021. Vaccination campaign reached it goals in preventing death in mid of Spring 2021.
Vaccines was very efficient in preventing death in the beginning when the eldery was vaccinated
Vaccines are lost it efficiency for preventing weekly COVID death in mid of Spring 2021 especially if to account that between infection and cause of death there is ~3 weeks lag.
Note: Drop in weekly death count is due to underreport.
Request public investigation of cause
Demands:
Appendix
Supporting data.
Vaccine safety “no evidence”
There is the front of the spike of weekly count for unclassified death which is could be predicted with weekly administered vaccine doses.
Vaccines are lost it efficiency for preventing weekly COVID death in mid of Spring 2021.
Note: Drop in weekly death count is due to underreport.
Mortality estimate
Predictor for unclassified death corresponds to 116 death per million administered doses with 12 weeks lag. 9 weeks lag was just start of the front
Vaccine efficiency
There is no correlation between weekly administered doses and weekly COVID death in April 2021. Vaccination campaign reached it goals in preventing death in mid of Spring 2021.
Vaccines was very efficient in preventing death in the beginning when the elderly was vaccinated
Vaccines are lost it efficiency for preventing weekly COVID death in mid of Spring 2021 especially if to account that between infection and cause of death there is ~3 weeks lag.
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate
Legend:
Blue --- weekly administered doses / 8K
Red --- weekly unclassified death - 648 which is mean for 50 weeks 2020
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Legend:
Blue --- weekly administered doses with 12 weeks lag / 8621 (model intercept translated as 1 per 8621 doses)
Red --- weekly unclassified death - 648 which is mean for 50 weeks 2020.
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Scatterplot Unclassified death vs Weekly Administered doses delayed by 12 weeks.
Blue line represent linear model.
Shaded area is 95% confidence interval
Blue curves represent probability density
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Coefficients estimate and residuals
Conclusions
Relationship of weekly administered doses vs weekly unclassified death
Vaccine efficiency estimates
Vaccine doses per COVID death
Plot represent the Weekly administered vaccine doses divided by Weekly COVID underlying cause of death.
It could be seen that from the end of March the proportion is stable.
The assumption could be made than ~7K administered doses weekly correspond to 1 weekly COVID death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses which COVID death relationship
Legend:
Blue --- weekly administered vaccine doses/1000
Red --- weekly COVID underlying cause of death
It could be seen that since end of March there is no relationship between weekly doses and COVID death. Still since end of April COVID death continues to fall. We are have to take into account that cause of death delayed from infection by 3 weeks. ~1 week till symptoms onset and ~2 weeks till death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with COVID death rate change relationship
Legend:
Blue --- weekly administered vaccine doses/10000
Red --- weekly change of COVID underlying cause of death
It could be seen that since end of March there is no relationship between weekly doses and COVID death. Still since end of April COVID death continues to fall. We are have to take into account that cause of death delayed from infection by 3 weeks. ~1 week till symptoms onset and ~2 weeks till death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Legend:
Blue --- weekly administered vaccine doses/2000
Red --- negative weekly change of COVID underlying cause of death shifted left by 3 weeks
We could conclude than till mid of January about 2000 doses administered prevented 1 COVID death per week.
Still since March there is no any relationship with number of doses administered.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Scatterplot till week 3 of 2021: COVID death weekly rate change shifted left by 3 weeks with weekly administered doses.
Model estimate translates like 1600 doses preventing one COVID death per week
.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Scatterplot from week 13 COVID death weekly rate change shifted left by 3 weeks with weekly administered doses.
Shows some relationship probably due to seasonal drop. Even if we are believe vaccines still effective the model coefficient translates like 53191 doses save 1 covid death weekly. 53191 correspond to 6 unclassified death.
.
Note: Drop in weekly death count is due to underreport.
Conclusions
Relationship of weekly administered doses vs weekly COVID death
Vaccination campaign overview
Even if we are triple COVID death and include all death with COVID and all the excess of natural death risk/benefit of continuing the vaccination campaign now is questionable.
Legend:
Note: Drop in weekly death count is due to underreport.
Vaccination campaign overview
Weekly unclassified death exceed weekly COVID as underlying condition death and continues to rise. Drop at the end due to CDC underreport.
Legend:
Note: Drop in weekly death count is due to underreport.
Conclusions
Relationship of weekly administered doses vs weekly COVID death vs Unclassified death
CDC COVID mortality estimates by age group for Year 2020
Mortality rate is given per 100K of population
VAERS data for COVID vaccination campaign
VAERS gives us some idea about age distribution of vaccine related death still we are have to take in to account that this data is skewed because of the vaccination was started for elderly and only recently for youth. So I am not going to apply this age/mortality distribution to data above.
Anyway even this numbers especially applied to number of unspecified age reports should question the vaccine EUA for youth.
August
Personal opinion
In industry I working for first slide of this presentation alone would cause Fortune 500 company will set a team of first class engineers for months of full time work to make complete investigation of cause and explain what caused this spike of unclassified failures, with all the amount of bullet proof facts why it should not be attributed to production of their company. And if it is they will provide solution how to mitigate it and will consider to stop production till the errors are fixed. I do not see any effort to do the same not from the vaccine producers not from the regulative agencies.
I had seen how regulator and vaccine producer investigated the vaccine injury during the trials. It unacceptable even in industry I working for. Any failure during the reliability tests investigated for months and till there is complete proof it not caused by the quality issues or otherwise the whole amount of costly effort done to mitigate any issues found. It is not true for this vaccines.
Speculations
Explanation of 9 weeks, way to go, no model at least to the next weekend.
There is explanation of 9 weeks: it’s accumulated defects. In Reliability Theory there is the common curve is bathtub. For Human as for mechanical device it the same. We are also have child mortality and death due to wear in old ages. z(t) is the failure rate. Same thing applied to human or device under stress. In our hypothesis this excess related to vaccine injection. Vaccine causes continuous stress. Some cases failure is immediate like shock, some cases it just accumulation of defects. The estimate for child mortality we could take it some proportion of mortality in first week. Or we could do another CDC based data calculation between the previous week and the first week of campaign.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 9 weeks, way to go, no model at least to the next weekend.
This estimate should be deducted from each week of campaign as early failure rate. We are need to find relationship between the early failure rate and amount of doses administered. And make the model. Because we are based on same data it’s linear (age distribution and first goes old ages?). It’s explains all the underestimate of our current model. This mortality should be deducted from total before the defects model applies. We could assume that some amount of people received something which is causes accumulation of defects with the time. So we are have to add time to new model when the early mortality already deducted.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 9 weeks, way to go, no model at least to the next weekend.
What we are probably observed with this 9 weeks it is the mode of the mortality after the stress. I could not conclude anything about time now. In my opinion needed to normalize doses in time then adjust the model to continuous same magnitude stress. We are do not have the ability to perform it in real world, but could try to do math. Please be clear our model is not single device/human failure it is the sample which continuously and not stable grows. MTTF it is the mean time to failure.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 9 weeks, way to go, no model at least to the next weekend.
So, defects are accumulating till some point (specific for each object) when it cause failure. The easiest way I see to assume any vaccinated could get randomly some (fixed but in real life random) amount of thing which causes defects accumulation. Defects could grow by any function of time, which is needed to be estimated for sample and it cause rise of defects to threshold which is not compatible with object life. The straightforward way is to apply some score and set some limit like mean (mode) has to be in this amount of time and find out the estimate of defects growth to failure. I am sorry I am no capable to do it right away. If smarter people do and share I would be glad. Otherwise I have to try.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 12 weeks, way to go, no model at least for next few weeks.
9 weeks was underestimate and just front of unclassified death. 12 weeks updates estimate to 116 per million with linear relationships.
Red --- Unclassified death - 2020 mean divided by Weekly Administered vaccine doses
Blue --- Weekly Administered doses scaled down 3.5e-11
Green fitted (roughly) Weibull distributions. I did not check goodness of fit or anything.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 12 weeks, way to go, no model
Red -- estimate of Unclassified death within the week of the dose received. Early failure rate.
Orange -- Unclassified death with deducted EFR. EFR is overestimated so we are have negative values for number of weeks
Blue weekly administered doses minus ones which caused early failure divided by 8K
We could believe that EFR roughly correspond to VAERS data, it need to be analysed but roughly could be expected.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 12 weeks, way to go, no model
Unclassified death minus estimated death within the week of dose vs Administered doses with 12 weeks lag minus ones which caused death within the week of dose.
For adjusted unclassified death model intercept is 135 per million.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 12 weeks, way to go, no model
For first 8 weeks we had mostly Unclassified death within the week of dose.
Estimate 25 per million doses.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
Explanation of 12 weeks, way to go, no model
Using this two Weibull fits for early and for delayed failures we are could try to estimate quality of it. And use it for prediction. Right way is to use survival package fit the model analyse the goodness of fit but even this way it gives some reasonable result against of real data.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
This looks scary
We are got 116 per million doses with 12 weeks lag
26 per million doses for first 8 weeks
And 20 per million minimum from real data.
Together it is at least 136 per million doses.
Worst thing that the campaign slowdown but Unclassified death continues to rise.
It could be mostly healthy people otherwise why unclassified.
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
Speculations
This looks scary
From our rough estimates we could believe:
Please if you want to continue DO NOT TAKE distribution of death per days from injection from VAERS. It is another reporting system we are should base on the exact same one.
July 2021 version
Unclassified death and weekly vaccination rate
Legend:
Blue --- weekly administered doses / 10K
Red --- weekly unclassified death - 782 which is model intercept and overestimate of mean of unclassified death for previous years
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Legend:
Blue --- weekly administered doses with 9 weeks lag / 10K
Red --- weekly unclassified death - 782 which is model intercept and overestimate of mean of unclassified death for previous years.
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Scatterplot Unclassified death vs Weekly Administered doses delayed by 9 weeks.
Blue line represent linear model.
Shaded area is 95% confidence interval
Blue curves represent probability density
Note: Drop in weekly death count is due to underreport.
Unclassified death and weekly vaccination rate relationship
Coefficients estimate and residuals
Conclusions
Relationship of weekly administered doses vs weekly unclassified death
Vaccine efficiency estimates
Vaccine doses per COVID death
Plot represent the Weekly administered vaccine doses divided by Weekly COVID underlying cause of death.
It could be seen that from the end of March the proportion is stable.
The assumption could be made than ~7K administered doses weekly correspond to 1 weekly COVID death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses which COVID death relationship
Legend:
Blue --- weekly administered vaccine doses/1000
Red --- weekly COVID underlying cause of death
It could be seen that since end of March there is no relationship between weekly doses and COVID death. Still since end of April COVID death continues to fall. We are have to take into account that cause of death delayed from infection by 3 weeks. ~1 week till symptoms onset and ~2 weeks till death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with COVID death rate change relationship
Legend:
Blue --- weekly administered vaccine doses/10000
Red --- weekly change of COVID underlying cause of death
It could be seen that since end of March there is no relationship between weekly doses and COVID death. Still since end of April COVID death continues to fall. We are have to take into account that cause of death delayed from infection by 3 weeks. ~1 week till symptoms onset and ~2 weeks till death.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Legend:
Blue --- weekly administered vaccine doses/2000
Red --- negative weekly change of COVID underlying cause of death shifted left by 3 weeks
We could conclude than till mid of January about 2000 doses administered prevented 1 COVID death per week.
Still since March there is no any relationship with number of doses administered.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Scatterplot till week 3 of 2021: COVID death weekly rate change shifted left by 3 weeks with weekly administered doses.
Model estimate translates like 1600 doses preventing one COVID death per week
.
Note: Drop in weekly death count is due to underreport.
Vaccine efficiency estimates
Weekly vaccine doses with infection caused death relationship
Scatterplot from week 13 COVID death weekly rate change shifted left by 3 weeks with weekly administered doses.
Shows no relationship
.
Note: Drop in weekly death count is due to underreport.
Conclusions
Relationship of weekly administered doses vs weekly COVID death
Vaccination campaign overview
Even if we are triple COVID death and include all death with COVID and all the excess of natural death risk/benefit of continuing the vaccination campaign now is questionable.
Legend:
Note: Drop in weekly death count is due to underreport.
Vaccination campaign overview
Weekly unclassified death exceed weekly COVID as underlying condition death and continues to rise. Drop at the end due to CDC underreport.
Legend:
Note: Drop in weekly death count is due to underreport.
Conclusions
Relationship of weekly administered doses vs weekly COVID death vs Unclassified death
Data sources
https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scenarios.htm
https://www.openvaers.com/covid-data/mortality
lhttps://data.cdc.gov/NCHS/Weekly-Provisional-Counts-of-Deaths-by-State-and-S/muzy-jte6/data
https://data.cdc.gov/Vaccinations/COVID-19-Vaccinations-in-the-United-States-Jurisdi/unsk-b7fc
https://www.cdc.gov/mmwr/volumes/70/wr/mm7014e1.htm
https://www.ntnu.edu/documents/624876/1277590549/chapt2-1.pdf
Possible major public safety issue discovered.