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Data Experts Attack the Ferguson Covid-19 Model By Brian Simpson

     We recently did an article where one computer expert cited took apart the coding foundation used in the Neil Ferguson model, that predicted doom, unless there was a society-wide lock-down. Now more have begun to attack the model:
  https://www.dailymail.co.uk/news/article-8327641/Coronavirus-modelling-Professor-Neil-Ferguson-branded-mess-experts.html

“Scientists have levelled a flurry of criticism against Professor Neil Ferguson's modelling which warned 500,000 people could die from coronavirus and prompted Britain to go into lockdown. Modelling from Imperial College London epidemiologist Professor Ferguson, who stepped down from the government's Sage group at the start of May, has been described as 'totally unreliable' by other experts. The coding that produced the sobering death figures was impossible to read, and therefore cast doubts on its strength, The Telegraph reported. It is also some 13 years old, it said. When other scientists have tried to replicate the findings using the same model, they have repeatedly failed to do. Prof Ferguson's model is understood to have single-handedly triggered a dramatic change in the Government's handling of the outbreak, as they moved away from herd immunity to a lockdown. Competing scientists' research - whose models produced vastly different results - has been largely discarded, they claim.  David Richards, co-founder of British data technology company WANdisco said the model was a 'buggy mess that looks more like a bowl of angel hair pasta than a finely tuned piece of programming'. He said: '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.'”  

     Yet, it was this modelling that provided a foundation for the lock-downs that are set to deliver economic devastation to the West, and probably mark the decisive point where the West goes down. Don’t blindly trust “experts.”

 

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Sunday, 31 May 2020
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