The U.K. Health Security Agency stopped publishing Covid modelling data this January. However, finding alternative labour for the out-of-work modellers only took a month.
The UKHSA’s Chief data scientist Dr. Nick Watkins said the country is living with Covid thanks to vaccines and therapeutics, and the data is “no longer necessary.”
The agency is now turning to models to understand the impact of Influenza H5N1 – Bird Flu – if mammalian transmission is established. Models will estimate the prevalence of the outbreak using different surveillance approaches, reasonable worst-case scenarios and the impact of public health measures, including border measures, on containing an outbreak. Hmmm, sounds familiar.
Epidemiological modelling has been an important tool throughout the pandemic to interpret data to support understanding the situation, and to provide scenarios to develop awareness of the potential impacts of different options for policy choices.
But hold on – it’s not just one model; you need multiple models to generate the truth!
Modelling is considerably more robust when more than one model (ideally a minimum of three) is considered and a consensus is built and agreed across a broad community.
There you have it: consensus is all you need. Evidently, it introduces quality assurance and seemingly lowers the risk of “spurious results”.
Ah, but there are some limitations, as the Technical report informs us:
As the Omicron variant emerged in South Africa in November 2021, it was impossible to tell whether its early apparent decreased severity would be replicated in the U.K.
However, by December 2021, the models were overly pessimistic and far from reality. So on December 15th, we wrote ‘We’re almost certainly overreacting’ in the Telegraph.
The South African data reported fewer patients in intensive care, less-severe diseases and shorter hospital stays. With some medical knowledge, it wasn’t difficult to determine whether the South African data would be applicable elsewhere. Seemingly, the U.K. modellers were the only people who couldn’t understand the generalisability of the data.
The technical report also says that “data will always be lacking in the early phases of an epidemic or wave with a new variant, and this, in particular, was a significant limitation for epidemiological modelling early in the pandemic”.
Despite these limitations, Government machinery relies on models and is fixated on their use – the glean of prophetic insight afforded by fortune-telling is too irresistible for those in power.
But those in the know will recall the track record of modellers’ mistakes and their erroneous predictions: BSE in 2000 and a worst-case scenario of 136,000 vCJD deaths; foot-and-mouth disease in 2002, which saw millions of animals slaughtered based on modelling; 2005 bird flu models that led to the stockpiling of antivirals and then in 2009, swine flu models that predicted the worst case scenario of 65,000 deaths – the actual death toll was less than 500 in the U.K. with an infection fatality ratio one-tenth of that forecast.
However, if the Health Security Agency is modelling bird flu, perhaps it should start by revisiting the 2005 models. In 2005 Neil Ferguson told the Guardian “that up to 200 million people could be killed”. The Department of Health considered anywhere up to 700,000 deaths could occur in the U.K.
As science is cumulative, scientists should accumulate the science and keep non-science out. Therefore, in our next post, we’ll turn to those 2005 bird flu predictions to analyse what they foretold.
Dr. Carl Heneghan is the Oxford Professor of Evidence Based Medicine and Dr. Tom Jefferson is an epidemiologist based in Rome who works with Professor Heneghan on the Cochrane Collaboration. This article was first published on their Substack blog, Trust The Evidence, which you can subscribe to here.
Stop Press: Britain should be stockpiling more antivirals and PPE for bird flu as it is “essential” to start preparing for the worst-case scenario, according to Professor Peter Openshaw, who sat on two SAGE committees during the pandemic.