Analysis of Official Data Related to COVID-19 Vaccine Efficacy and Safety:
Three sources, three algorithmic biases, some significant, all in favour of vaccination

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This page provides independent analysis of the three main Government of Canada sources that report statistics related to COVID-19 Vaccine Efficacy and Safety.  It is observed that all three of these sources contain algorithmic biases in the way statistics are computed and reported. Some are likely unintentional, some are possibly intentional. Some not significant, some significant. All of them skew the presented results in the favour of vaccination. 

Use interactive data visualization tools below to learn more about the phenomenon and how one can mitigate the biases by reverse-engineering the computational algorithms so that one can report statistics without or with less bias.


The following "Concern" was submitted to the Office of the Auditor General of Canada:

"In https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html, PHAC reports ‘Percentage of Fully vaccinated among COVID Deaths' counting cases from December 2020  when there were NO fully vaccinated. I.e.  PHAC used algorithm bias (advantage) to misinform public about Percentage of Fully vaccinated among COVID Deaths, reporting numbers that are significantly lower than actually weekly observed.  This misinformation must be corrected. More details: www.ivim.ca/bias.htm"

Below is the Acknowledgement of the receipt.

Data Spreadsheet is here

This Spreadsheet integrates  and displays empirical post-marketing data that were collected by the Government of Canada since August 2021* related to COVID-19 vaccine safety and efficacy.  Note that it was only in August 2021 when such data have become available.

Data Sources:

  1. Source #1: [PHAC-1] Cases following vaccination, COVID-19 Daily Epidemiology Update, Public Health Agency of Canada,
    https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html#9 .
    Archived reports: web.archive.org, www.ivim.ca/data/phac1
    • Table 2. Characteristics and severe outcomes among unvaccinated, partially vaccinated, fully vaccinated, and fully vaccinated with additional dose confirmed cases reported to PHAC 
    • Figure 7. Age and gender distribution of COVID-19 cases 
  2. Source #2: [PHAC-2] Reported side effects following COVID-19 vaccination in Canada, Canadian COVID-19 vaccination safety report, Public Health Agency of Canada, https://health-infobase.canada.ca/covid-19/vaccine-safety/
    • Figure 1. Weekly number of COVID-19 vaccine adverse event reports 
    • Table 1. Count of reported adverse events of special interest  
  3. Source #3: [StatsCan1] Statistics Canada, Canadian Vital Statistics - Death database. Provisional weekly death counts, by selected grouped causes of death, https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310081001,


Source #1: [PHAC-1] "Cases following vaccination, COVID-19 Daily Epidemiology Update”, Public Health Agency of Canada

Click here to open/close full analysis and graphics 


  • Algorithmic bias is observed in the way PHAC reports 'Cases by Vaccination Status' statistics. - Instead of reporting weekly statistics, as done elsewhere (e.g. in reporting 'Deaths by Causes' statistics, or  'Vaccine Side Effects' statistics), PHAC reports total statistics, that aggregates all cases from December 14, 2020 (the day when vaccination started),  knowing that in early months of vaccination there was negligible percent of Fully vaccinated and that it was exactly then when most COVID-19 deaths happened. 

    Because of this algorithmic bias, the results reported by PHAC are skewed significantly (by order of magnitude) in favour of Fully vaccinated. The skew was most noticeable at early stages of reporting these statistics (July - September) when, instead of weekly observed  9%-35% deaths among Fully vaccinated, PHAC reported only 1%-4% of them.

This is what is reported (mis-information):

  • “Fully vaccinated individuals diagnosed with COVID-19 were significantly protected from severe outcomes” 
  • "...even with high vaccine effectiveness, a small* percentage of people who are vaccinated against COVID-19 will still get sick and some may be hospitalized or die..."  (It is noted that, starting December 2021, the word "small" was removed from PHAC reports.)

This is what is observed:

  • Since the very first 'Cases following vaccination' report produced by PHAC on August 30, 2021, the data did not show that Fully vaccinated had considerably less weekly severe outcomes than unvaccinated individuals.
  • At the same time (according  to [PHAC-2]), a  percentage of vaccinated people do suffer from severe COVID-19 vaccine reactions,  the number of which is comparable in scale to the number of severe outcomes from COVID-19 (see Source #2)

Additional observations:

  • Vast majority (82%) of all COVID-19 deaths happened among elderly (70+), less than 1% among young people (<40) and only 0.1% among children (<20).
  • In contrast to deaths and hospitalizations from COVID-19, the distribution of severe adverse reactions from COVID-19 vaccines is approximately the same among different age groups (see Source 2). This means that younger population, especially children, will more likely have severe adverse reactions from COVID-19 vaccine (including deaths and vital organ failures)  than have severe outcome from COVID-19 infection.

Source #2: [PHAC-2] Reported side effects following COVID-19 vaccination in Canada, Canadian COVID-19 vaccination safety report, Public Health Agency of Canada

Click here to open/close full analysis and graphics 


  • Over half of severe adverse reactions (SAR) are reported with three-six months delay. This creates another algorithmic bias in favour of vaccination when comparing latest adverse reactions statistics to latest COVID-19 cases statistics, which are reported without delay. This bias is estimated to be at least of the factor of two.

    Example: In June 2021, PHAC reported only 363 severe adverse reactions for the month of May. Six months later (in February 2022) for the same period, PHAC reported  almost twice as many (683)  severe adverse reactions, including deaths, and organ failures. For comparison, in the same period, there number of COVID-19 deaths was only 27.

Source #3: [StatsCan-1] Statistics Canada, Canadian Vital Statistics - Death database. Provisional weekly death counts, by selected grouped causes of death

Click here to open/close full analysis and graphics 


  • The number of all non-COVID causes started to decrease since the start of the pandemic, including those that have a trend to go up.  Additionally,  there is no “first wave” observed in West provinces, in contrast to East provinces. This is indication that it was likely the change in the way deaths causes were reported in the "first" wave versus, how they were reported after"first wave": If "COVID death" includes other Deaths with COVID positive test is in a death certificate, then the actual number of deaths from COVID is smaller than reported number. In other words,  an algorithmic bias  is also observed in how "COVID deaths" are reported.
  • Based  on linear regression analysis of Canadian Deaths Statistics prior to pandemic and after the pandemic, and the official data from  UK, the bias is estimated to be of the factor 2-10 , meaning that of all reported "COVID deaths"  1/10 - 1/2 happened because of COVID, the rest happened from other causes.

Other observations (combined with observations from UK and US)

  • Average age of death from COVID-19 is statistically equal (within standard deviation) to the average life expectancy. The total number of deaths - from all causes combined - during the pandemic is within the expected trend-line. Throughout the pandemic, the  number of COVID deaths is much smaller than that of leading causes of death such as cancer and heart problems.
  • It is common to publish COVID-19 deaths and COVID-19 cases in terms of Totals - aggregated since the start of pandemic, instead of publishing their weekly counts, which creates an impression of increasingly growing health problem, even when the problem is not growing or is considerably less than other health problems. 
  • The number of  unexplained or unreporported causes of deaths increased significantly since the start of mass vaccination;
  • The delay in reporting deaths statistics increased from one month (in November 2021) to three months (in March 2022)

Additional information related to the presented analysis:

Comments/Questions: opencanadadataanalysis @ ivim.ca
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Updated: March 2, 2022

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