Covid-19 Science

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

How effective are the covid vaccines really?

By Juergen Ude : 3rd June 2021

Governments in 2020 were confident that vaccines are the solution to returning life to normal. This confidence does not seem to have changed with governments pushing for everyone to get vaccinated.

It is natural to ask how effective the vaccines are, especially with the pressure placed on people who have well founded vaccination anxiety, being ‘pushed’ to take ‘experimental’ vaccines.

Covid vaccines are made from synthetic or modified genetic material in record time. Hence, there are risks due to insufficient testing as has already been born out. Current covid vaccines do not inoculate with a virus, like the smallpox vaccinations pioneered by Edward Jenner, which relied on the body’s immune response. Interestingly in Jenner’s time smallpox killed 10 to 20 % of the population but governments did not react the way modern governments have reacted bringing the population to its knees.

There have been several statistics provided on the efficacy. Efficacy is based on clinical trials, not real-world performance. If a vaccine has 70% efficacy a vaccinated person in a clinical trial is 70% less likely to develop the disease in a trial compared to someone who has not received the vaccine. Based on our research efficacy for the various vaccines are quoted as between 70% to 90% depending on the vaccines and whether efficacy is based on mild symptoms are severe complication.

Global leaders and Health Advisers are quoting these numbers as fact, but they are not fact. Indeed, they are unreliable estimators, and we may be in for a rude awakening finding that vaccination is ineffective. Let us hope not.

It is of course unethical to inject the virus into participants to test efficacy. The alternative is to select participants from a group of people where some are known to have the disease. This is a problem because efficacy may depend on the stage of the disease. Another problem is that the case percentages for Covid are low at around 10% of the population and hence estimation errors will be highly significant. In effect thousands of participants are required to obtain a reliable estimate of efficacy. Instead, the numbers are quite low.

The Australian Government’s Heath Department, prior to the covid crisis was very realistic.

Influenza vaccine efficacy, effectiveness and impact explained

“Vaccine Efficacy refers to the reduction in disease, due to vaccination, as shown in research studies carried out under controlled conditions e.g., randomised clinical trials. While this type of study is considered the gold standard to confirm the protective effects of vaccination, there are important limitations. Clinical trials are often performed in healthy populations, and usually exclude people with medical conditions and pregnant women. For vaccines that need multiple doses, people are more likely to follow the vaccine schedule if they are enrolled in a trial than they would in “real life”. Clinical trials usually enrol too few people to see changes in rare but important outcomes, such as hospital admission or death.”

What is more important is effectiveness of vaccines in the real world. This is what the Australian Government used to say.

Influenza vaccine efficacy, effectiveness and impact explained

“Vaccine effectiveness refers to the reduction in clinical outcomes due to vaccination in the “real world” after a program has been implemented. These outcomes may include disease incidence, or other measures such as general practice attendance with disease, or hospital admission with disease. Vaccine effectiveness is often lower than vaccine efficacy, because it includes people in whom the immune responses to vaccines may not be as strong as healthy people in clinical trials, and because adherence to vaccine schedules may not be as good as in clinical trials. Vaccine effectiveness is usually estimated from observational studies.”

A key point is vaccines “may not be as strong as healthy people in clinical trials”. Covid targets mainly frail, elderly people most of whom have co-morbidities. We may thus find that the effectiveness is quite low.

On the 2nd of June 2021, the acting Victorian Premier blamed the Covid outbreak on the national vaccine rollout. This is consistent with the belief that vaccinations are the solution. This may however be false confidence. Until now we have not been able to obtain an effective vaccine for the common cold. Sars-Cov-02 is of the same family of viruses. The flu vaccine has been estimated to be between 40% to 60% effective and that estimate is unreliable. If the covid vaccine has similar effectiveness, then there is no end in sight with lockdowns unless governments accept that we must live with viruses and deaths side by side. One must also ask why those who have been vaccinated must still wear facemasks and participate in lockdowns. It appears that governments are not as confident as they seem.

To obtain an insight into the effectiveness of the vaccinations we analysed data for the UK. At this stage we can only obtain an insight because vaccination has not yet been completed.

The analysis uses a new curve fitting machine learning based algorithm to better fit a complex curve to the data.

Referring to Figure 1 Cases dropped at almost the same time vaccination started. It is unrealistic to conclude that vaccination caused the effect. A handful of vaccinations could not possibly have started the downward trend.

When cases approached the tail ends only half of the UK had been vaccinated. We cannot thus assume that the cases and deaths came down because of vaccination. 50% is too low. If this were true then there is no need to coerce the whole population to vaccinate

One would expect a threshold where number of people vaccinated will show an effect on cases. There is none. The downward slope continued in the same pattern without ‘disturbance’.

BIS.Net Analyst Change Analysis used in Covid-19 analysis
Figure 1 UK cases, deaths and people vaccinated

Similar conclusions were obtained for ISRAEL and the USA. At this stage there is no evidence, based on the data that vaccinations are the solution. When our government tells us if we want no more lockdowns then we must all vaccinate then we can expect to be disappointed. Unless the virus soon 'dies' or mutates to a harmless version lockdowns will remain even if everyone vaccinates because the effectiveness is not 100% and more likely at flu levels. The only way lockdowns may disappear is for governements to become real again and stop thinking academically and be willing to let real-world experts investigate whether humans many have contributed to the many deaths.

Additional Off-Topic Comments

If not due to the vaccine, it is natural to ask if the drop was due to lockdowns. There have been 3 lockdowns in England. There is no sound evidence that the cases and deaths came down due to the lockdowns either. Instead, there are many instances where cases came down by themselves, just as with the common cold and seasonal flu.

The large third wave has been blamed on the Kent variant but most of the increase in cases was due to increased testing numbers, which captured more cases. After factoring in test numbers, the first wave was far more infectious and the third only a little more infectious than the second wave as shown in Figure 2. It seems that wrong conclusions were drawn by scientists. It is acknowledged that the high positivity of the first wave may be due to biased ‘sampling’ where those with symptoms were targeted for testing. Hence the difference may not be so pronounced.

BIS.Net Analyst Change Analysis used in Covid-19 analysis
Figure 2 Case positivity

Referring to Figure 2 the slightly higher last wave blamed on the Kent Virus is not unexpected. There is a known seasonal effect of deaths due to respiratory diseases and the peak corresponds to the seasonal effect. Breathing on cold days is known to result in vapour being exhaled which can help better transmit the virus. In Australia we are currently being told we have a rocket propelled variant, but we also have cold weather where breathing out condensate may be the cause for what is said to be a superfast transmitting virus (Interesting the number of cases don’t confirm a hypersonic fast transmitter).

Of interest is that there is no evidence that the dreaded Indian variant has increased cases or deaths in the UK.

Of greater interest is the lag between cases and deaths. We would expect the peaks to lag by around 30 days because it takes time for death to occur after cases have been detected. For the first wave there was no lag and the last the lag was around 10 days. The implication is that deaths were caused by panic! Panic would have manifested itself in many ways. One is patients leaving check in too late to avoid confronting the reality that they have the virus. Another is panic transferring to Doctors who may have overreacted with ventilators which are known to cause deaths even amongst healthy people. Some patients refused to go on ventilators.

Disturbing is the fact that the first wave had a zero lag between case and death peaks, but that would be expected. Panic would have been highest at that time of the pandemic. Supporting the panic theory is the fact that countries that did not report unusual excess deaths, had expected lags of over 21 days. Countries that had excess deaths had small lags. Hence not the virus but human beings may have caused the high excess deaths with irresponsible fear generation by the media and government propaganda. Let us hope not. Time will reveal the truth.

Covid-19 Analysis Report

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ABOUT THE AUTHOR

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.