This article was originally published by Rhoda Wilson at The Daily Exposé.
The UK and Imperial College London were the intellectual nerve center of the global covid pandemic response. As you will recall, it was Neil Ferguson, a physicist at Imperial College, who developed the main epidemiology model behind the justification to shut down economies.
However, Ferguson’s model was undocumented 13-year-old code that needed to be “cleaned up” and his assumptions were garbage. This is been known since at least March 2020, around the same time that the UK government implemented its first shutdown of the economy spuriously called “lockdowns.”
The American Institute for Economic Research (“AEIR”) noted in April 2021, “Ferguson predicted catastrophic death tolls back on 16 March 2020 unless governments around the world adopted his preferred suite of non-pharmaceutical interventions (“NPIs”) to ward off the pandemic. Most countries followed his advice, particularly after the United Kingdom and United States governments explicitly invoked his report as a justification for lockdowns.”
Yet Ferguson’s model was written using some 13-year-old undocumented code which then needed to be “cleaned up” with the help of Microsoft to make it reusable by anyone else. That isn’t even the worst of it – key assumptions forming the inputs to the model were garbage, Jonathan Engler writes introducing an article written by Mike Hearn in March 2020.
By Jonathan Engler, 22 June 2024
As the years march on, it is easy to forget how egregiously wrong every single assumption around “the pandemic” was.
This piece (see below for link) from 31 Mar 2020 – which I highly recommend – lays bare the shortcomings of using GIGO1 modeling as a driver of public policy, something which we see across many domains, most notably the “climate” agenda but also many other fields.
In fact, I would characterize the age in which
The remainder of this article is available in its entirety at SHTF Plan