While Democrats in the US and progressives in the UK continue to push back against efforts to gradually reopen their respective economies, more evidence is emerging that calls into question the models (what the public often refers to as the “science”) which inspired governments across the world to impose crippling lockdowns on their populations.
Case in point: Since Neil Ferguson and the authors of the Imperial published its modeling for non-pharmaceutical intervention for COVID-19, a number of data scientists have taken a close look and found gaping oversights that seriously undermine the model’s credibility. Of course, this isn’t the first time we have written about Ferguson and his exploits.
n this weekend’s Telegraph, two of these critics, David Richards, the founder and CEO of global big data leader WANdisco which is jointly headquartered in Silicon Valley and Sheffield, and Dr. Konstantin Boudnik, a pioneering big-data engineer, WANdisco’s VP of architecture and author of 17 US patents, published an editorial in which they carefully examined the model’s shortcomings. Keep in mind, the Imperial model is what ultimately inspired PM Boris Johnson to make a U-turn and adopt what has been an economically devastating lockdown – was nothing short of a catastrophe. Millions have been plunged into hardship and poverty unnecessarily, they explained. Johnson himself was infected by the virus and the public is furious with the government over its rollout of a plan to reopen.
Given the influence the model had during the early days of the outbreak, the two men argued that the software issues underpinning the model could be ‘the most devastating software mistake of all time’.
Apparently, the model’s problems are rooted in its most fundamental components. The model was written using a coding language called Fortran which has been in use for decades.