Modelling used to make wild claim
Imperial College now have a global reputation for making provable wrong claims based on modelling and they appear to want to bolster that reputation. Previous harm caused by Imperial include Neil Ferguson’s models in 2001 that led to the culling of 6 million cattle and sheep allegedly to prevent spread of foot and mouth disease which cost the UK economy £10bn. Subsequent predictions have included 50,000-150,000 deaths in humans in 2002 due to CJD because of the BSE outbreak (there were 177 deaths), 200 million deaths from bird flu in 2005 worldwide (there were 78); 65,000 deaths from Swine flu in UK in 2009 (there were 457).
Although this was not Neil Ferguson’s work, this latest model from Imperial college is also out by orders of magnitude. Modelling is nothing by glorified guessing based on extrapolating from assumptions of the authors’ choosing. The assumptions were so wild in the latest attempt that they reached the absurd fantasy of 20 million lives having been saved. It is almost not worth wasting time on it but given the coverage it has had on mainstream media, it needs to be addressed.
Let’s take a look at what that would mean.
First of all, here is a graph showing how the total number of deaths with covid worldwide grew over time. The arrival of vaccinations did not appear to reduce this trajectory (figure 1).
Now let’s add in another line to show what Imperial claim would have happened without vaccination such that 19.8 million people would be dead (figure 2). Their claim only works on the basis of a massive acceleration in the death rate.
To get to 19 million lives saved they included a claim that 500,000 lives were saved in the UK.
That’s a familiar number.
Neil Ferguson and his team claimed in spring 2020 that if we did not intervene there would be 500,000 lives lost to covid. They reached that number by assuming that 85% of us would catch it in the first wave and 1% of us would die. 500k must be Imperial’s favourite number because that is the number of lives they now claim the vaccine saved despite the 200,000 people having since died with covid.
How do we know they are wrong?
If vaccination had saved lives we could look to see a difference between countries with different vaccination rates. For example, Eastern European countries have markedly different vaccination rates from 30% to 66%, yet it is impossible to predict the covid mortality numbers based on which countries had more vaccinations.
South East Asia also tells an important story. These countries are heavily vaccinated and yet with the latest Omicron wave they have experienced mortality amounting to 300, 400 or even more per million. This is the same order of magnitude as Europe experienced in Spring 2020, with the original variant and before vaccination. The claim that vaccinations prevent 80%+ of covid deaths does not fit with what is happening in the real world.
These modellers have picked on occasional small studies of mortality in vaccinated and unvaccinated, which have their own biases, but produce a result the modellers like. From these they extrapolate to produce predictions that bear no relation to the real world.
Imperial’s models have never been proven to be right. Lessons never seem to be learnt. The assumptions Imperial used to create this model have no bearing to the real world.
They are living in Cloud-Covid-Land. The public need to realise that institutions such as Imperial receive considerable funding from the pharmaceutical industry and this colours how evidence is presented. The mainstream media are claiming such evidence is “science” when it is not much more than marketing for the pharmaceutical industry. The chasm between reality and the mainstream narrative is widening and the public need to realise that sources they have trusted in the past cannot be trusted on this topic any longer.