The Implausible Modelling Behind the Claims in the UKHSA Fake-Vaccine Surveillance Reports

One of the more amusing sections in the UKHSA Vaccine Surveillance Report was the small section tucked in at the end describing the vast numbers of hospitalisations averted and lives that had been saved by the vaccines. These continued to become ever more outrageous until September of last year, when the report claimed almost 25 million infections, 250,000 hospitalisations and 130,000 deaths had been prevented by the vaccines. The claim for the ‘infections prevented’ was particularly ludicrous; up until September 2021 there had only been around 6 million infections in total. We’re now at the point where the large majority of the population have had at least one Covid infection and many have had multiple infections. I’m sure that many people praised the gods of Pfizer and AstraZeneca after reading this particular section, even though the numbers offered were the results of enthusiastic computer models based on only the flimsiest of experimental data.

I’m sure that something happened in September 2021, as from that point the claims were frozen in time, with each weekly report stubbornly clinging onto the claims of the impact of the vaccines on the population but only up to September 2021. Then, surprisingly, in February 2022 the section was updated, with new enthusiastic claims for the number of hospitalisations averted during the Omicron wave. Eventually this update too was neutered; the real-world data clearly showed vast numbers infected with Omicron variant, with the vaccines offering very little impact on hospitalisations considering the infection numbers.

The section ended with a whimper in August, with only the following explanation as to why:

This analysis is not currently being updated due to the effect of the spring booster programme appearing increasingly in uptake data for three doses or more. This makes it difficult to assess the impact of initial booster on hospitalisations separately from the effects of the latest campaign.

I’m not entirely sure why this is relevant. Then again, they clearly wanted to get out of this obligation, as reality was embarrassingly different to their models’ predictions. I suppose their explanation was superior to stating that their dog had eaten the raw data.

But perhaps it shouldn’t be surprising that these incredible predictions of the power of the vaccines were being made – the misuse of biomathematical modelling has been a hallmark of this Covid epidemic. In the U.K. the outbreak started with dire predictions made by Imperial College’s modellers, with doom laden scenarios presented to the public in support of the stringent imposition of lockdowns. Much later, the authors of these predictions felt the need to make clear that they were only the worst-case predictions and claim that actually their models had performed well – but the authors nevertheless failed in their duty to explain the science to the public, and instead kept quiet while our politicians invented new laws to restrict behaviours and quash dissent. These models also, strangely, included assumptions of the powers of lockdowns, face-masks and other non-pharmaceutical interventions at slowing the spread of infection, when prior to 2020 the evidence had always suggested that they’d offer little if no benefit for a highly contagious respiratory virus (albeit most models were focused on the risks of influenza – similar enough, though).

The sorry tale of mathematical modelling and Covid is a shame, because mathematical models can provide valuable insight into how problems might occur and what could be done in mitigation – but our experiences of the last 30-plus months ably demonstrate how models are very sensitive to their input parameters, and how they can be misused by politicians keen to promote one particular ideology.

It is also important to note that these enthusiastic predictions, along with the other propaganda in the Vaccine Surveillance Report and elsewhere, could well have an impact far beyond even the disaster of the Covid lockdowns and other restrictions. We are now seeing signs of the population starting to distrust other vaccines and protective healthcare in general – this could end up with many people suffering serious illness or even death from the scourges of humanity’s past, such as measles, diphtheria and polio. Not that the current fetish amongst some ultra-wealthy individuals to banish all of the world’s diseases through vaccination is necessarily a good idea – vaccination can protect against some diseases, but by no means all of them, and the full impact of vaccination needs to be considered, particularly where the disease only rarely causes serious outcomes.

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