Last week our update included the report that Dr. Neil Ferguson, who developed the Imperial College Model predicting the spread of the Wuhan coronavirus, had resigned from his government position.

The reason for his departure was thought to be that he was discovered to be violating quarantine orders to see his mistress. However, it turns out there may be more motivation than a romantic affair.

The Model United Kingdom experts, as well as many others around the world, have largely used to guide their coronavirus policies has been deemed “totally unreliable” by experts. To start with, the Daily Telegraph‘s report on the assessments done by technology professionals is damning.

The model, credited with forcing the Government to make a U-turn and introduce a nationwide lockdown, is a “buggy mess that looks more like a bowl of angel hair pasta than a finely tuned piece of programming”, says David Richards, co-founder of British data technology company WANdisco.

“In our commercial reality, we would fire anyone for developing code like this and any business that relied on it to produce software for sale would likely go bust.”

…The Imperial model works by using code to simulate transport links, population size, social networks and healthcare provisions to predict how coronavirus would spread. However, questions have since emerged over whether the model is accurate, after researchers released the code behind it, which in its original form was “thousands of lines” developed over more than 13 years.

In its initial form, developers claimed the code had been unreadable, with some parts looking “like they were machine translated from Fortran”, an old coding language, according to John Carmack, an American developer, who helped clean up the code before it was published online. Yet, the problems appear to go much deeper than messy coding.

Other scientists have also found troubling problems with the model as well:

Scientists from the University of Edinburgh have further claimed that it is impossible to reproduce the same results from the same data using the model. The team got different results when they used different machines, and even different results from the same machines.

“There appears to be a bug in either the creation or re-use of the network file. If we attempt two completely identical runs, only varying in that the second should use the network file produced by the first, the results are quite different,” the Edinburgh researchers wrote on the Github file.

A fix was provided, but it was the first of many bugs found within the program.

“Models must be capable of passing the basic scientific test of producing the same results given the same initial set of parameters…otherwise, there is simply no way of knowing whether they will be reliable,” said Michael Bonsall, Professor of Mathematical Biology at Oxford University.

It is hard to overstate how important the …