Covid-19 Science

The science behind the global response to the Covid-19 pandemic

A lesson from Quality Control and Assurance applicable to Vaccination

By Juergen Ude : 17th March 2021

This is a sensitive topic because world leaders are banking on successful use of vaccination. Our objective is not to advise for or against vaccination. Instead it is to provide a scientific insight into the statistical side so that better informed decisions can be made by decision makers.

Beverage manufacturers need to control carbonation and brix (‘sugar’). When a beverage manufacturer produces millions of cans the amount of carbonation and brix will vary, hopefully little if the process is in control. There are many sources for the variation. One is the natural variation of the process when run in perfect control. There is variation due to different product brands, poor process control, malfunctioning processes, setup variation, batch to batch variation. All sources of variation can only be minimized, not eliminated.

The same goes for human beings, the only difference is that the variation is far greater. Consider the immune system. This will vary from person to person. Every person has different DNA. There is variation due to age, gender, race, ethnicity, the environment, state of health, state of mind and much more.

Quality Engineers have long learned about interactions. To control and improve processes adjustments may need to be made to various process setting. That is not simple. The effect a change in the setting of one switch will depend on the setting of another switch, which in turn depends on the setting of another switch.

Interactions are relevant to treatment and vaccination. To expect treatments to work across the board is un-realistic. What works for some people may not work for others. One combination of pharmaceuticals that work on one group of people may work not work on another.

For vaccination we do not just have the complexity of the human body, but the complexity of the production process and logistics of the vaccines themselves. We cannot assume perfectly controlled processes and perfect distribution and perfect storage and perfect administration of vaccines.

All the above interactions are applicable to the effectiveness and side-effects of vaccination.

Side-effects must be expected if we are realistic. All medicines have side effects, some known and some unknown.

More important from a statistical perspective is understanding the risks. There are three obvious risks. One is the risk of an adverse side effect, that can cause death or a permanent disability. The other is the risk of death caused by the corona virus if we do not take the vaccine. The third is reliance on vaccines causing our immune systems to become lazy.

To balance risks, we need to know what the risks are. With all the interaction effects, a vast amount of testing is required to determine what the risks are. We do not know what testing has been done. Because of this uncertainty by not knowing the extent of vaccine testing and other reasons, a group of highly qualified European doctors and scientists have written an open letter to the Executive Director European Medicines Agency. This letter can be viewed here:

What is the risk of death if we do not take the vaccine?

Our own analysis has confirmed deaths are reducing overseas, probably because of herd immunity. Unfortunately, in Australia because we have decided on a zero-cases and gone into long lockdowns we are unlikely to have herd immunity and are reliant on vaccines.

Based on 2017 data, the risk of dying in a year in the world is 0.7 in 100. In 2020 if we add reported covid deaths the risk of dying has become .74 in 100 in a year. When using excess deaths in the UK the risk of dying is 1 in 100 in a year and .0027 on a given day. Countries like the UK already have a higher risk than the global average. If we add the covid excess deaths the risk is 1.1 in 100 in a year.

Experts will say that without lockdown there would have been far more deaths. That is not what the experts said last year. Last year the experts said that lockdown was only meant to spread the curve so hospitals can cope. Spreading the curve does not reduce infections, and hence deaths, only prolong them at manageable levels (whilst giving the virus more time to mutate). We may have saved some lives due to reduced overwhelming, but a better option would have been temporarily increasing capacity.

The risk of death for Sweden in 2020 during the period it had no lockdown, is 0.86 per 100 in a year. If we add excess deaths caused by covid then the risk is 0.94 in 100.

For Australia at the peak before lockdown, there was no excess risk based on abs data.

As with everything outside the ‘academic test tube’ world things are not so simple. These deaths will have been inflated by various factors, such hospital management bungling, incompetent treatments, and possibly fear induced deaths. SAGE in the UK believes that deaths due to our responses are twice as much as due to the virus itself. We estimate 3 times as much. The risks are also not so simple. The estimates are overall risks, but when stratified by age, country, health status, mental state there will be considerable variability. According to the most reliable death statistic, registered deaths, there are little if any risks for those below 40—50 without comorbidities.

We often hear that there is no risk according to our experts and we have the best experts in the world. Unfortunately everything about the virus is soft science, including statistics. There is no certainty, just possibilities. There are possibilities of wrong decisions supporting the democratic, approach of giving everyone a choice and not force vaccination, directly or indirectly.

Covid-19 Analysis Report

Download the 40,000+ word analysis report on the science behind the response to the pandemic. AND/OR download the Open Letter attentioned to the world leaders.

* The information is dependent on the reliability of the information sources. Links have been given throughout for the reader to verify the contents. There has been no use of models made to prove points. Readers can download data from and perform the analysis independently. Many charts use our own technology to display underlying trends and scatter. More information on our technology please visit


Dr Juergen Ude has a certificate in applied chemistry, a degree in applied science majoring in statistics and operations research as top student, a masters in economics with high distinctions in every subject, and a PhD in computer modelling and algorithms. He has lectured at Monash University on subjects of data analysis, computer modelling, and quality & reliability.

Prior to founding his own company (Qtech International Pty Ltd), Dr Ude worked as a statistician and operations researcher for 18 years in management roles having saved employers millions of dollars through his AI and ML algorithms. Through Qtech International, Dr Ude has developed data analysis solutions in over 40 countries for leading corporations such as Alcoa, Black and Decker, Coca-Cola Amatil, US Vision and many more. Additionally he has developed campaign analysis software for politicians.