Cases following vaccination update. More about Algorithmic Bias used in reporting those cases
You dont need any more evidence to understand what's going on...
[PHAC-1] 'COVID-19 Daily Epidemiology Update', Public Health Agency of Canada: https://health-infobase.canada.ca/covid-19/ (https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html, prior to June 2022)
Data analysis and visualization
Results - as published weekly vs.
Results - as actually observed weekly.
Results - as published weekly:
Results - as observed weekly:
Results - as published weekly:
Do you see the difference?
You dont need any more evidence to make one of the most important conclusions in your life - about what is going on, what is wrong and what is right, and which side of the truth you are on. I made my decision and here’s my story. Now, it’s your turn…
Below are some specific observations that you can use in your communications with doctors, friends, managers and politicians, and some Questions that you can ask them.
Observation 1: Use of Algorithmic Bias to “embellish” results
PHAC reports Percentage of fully vaccinated (later of vaccinated with additional doses) among COVID cases counting cases from 14 December 14, 2020, which is when there were NO fully vaccinated (for many weeks yet) and NO additional doses administered (for many months yet).
This technique, known in Data Science under the term of “Algorithmic Bias”, skews the reported results significantly in favour of fully vaccinated (in reports published before June 2022 - by more than an order of magnitude) and in favour of recently administered doses (in reports published from June 2022 - by more than two orders of magnitude).
This Algorithmic Bias can be removed by computing the delta (difference) in the numbers published in consecutive reports. When it is removed this way, the following is observed.
Observation 2: Very different picture, when reported without algorithmic bias
The population with 1 dose (the results for which are NO LONGER reported by PHAC since June 2022 and which counts for 1.2 million of Canadians) has the smallest relative number of Cases, Cases Deceased and Cases Hospitalized since December 2021.
The largest number of Cases, Cases Deceased and Cases Hospitalized in a week per million is observed in populations with additional doses - in both reports issued before June 2022 and new reports issued since June 2022.
Why do the Governments (not only in Canada, but all over the world) report cases following vaccination statistics using algorithmic biases?..
WHO developed these guidelines (for all countries to report cases following vaccination statistics using algorithmic biases) ?..
Can the use of algorithmic biases be justified?..
Should the results that are obtained using algorithmic biases be called misinformation, or disinformation, or true information?..
What will it take to make the Governments, and Government of Canada in particular, to admit that they manipulated the ‘Cases following vaccinations’ data so that to “embellish” the results, when publishing them in their weekly epidemiology updates?..
When the Government of Canada will finally start publishing ‘Cases following vaccinations’ statistics without algorithmic biases - they way they publish all other deaths and vital statistics (see Open Canada Death Tracker App at www.IVIM.ca/app), i.e. by week, or by month, or by year see, instead of counting cases since the ‘red ribbon cutting” event of administering the first Covid dose to the first Canadian on December 14, 2020?... We are in Summer of 2022 now…
A few more:
Was the Rubicon crossed, and if so when?… Was it in August 2021, when the Government published their first “Cases following Vaccination” data or before that ?
What does it all say about the Nature of Things and where we are going?…
And the last, and the most important, one:
What can You do to resist what you believe is wrong?
Log of all ‘Cases following Vaccination’ data reported by PHAC since Summer 2021
Results Published weekly:
Results Observed weekly:
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