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How do we think about the UK lockdown debate?
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Death rate predictions are rooted in lies

Guttenberg Institute Professor Sucharit Bhakdi leads this charge, pointing to the vast cleavages between predicted and realised corona death rates. Underlying this position is the point that lockdown is based on phoney data and bad science.
Coronavirus Death

The Argument

Dr. Bhakdi says that, besides the outbreaks in China and Northern Italy, no other part of the world has seen the fatality rate that was estimated with Covid-19.[1] A great deal of the deaths in Italy and China are believed to be the result of other factors, such as respiratory illness or disease, caused by the poor air quality in both regions. Dr. Bhakdi says the mortality rates in China and Italy are "apparent" mortality rates because he says the countries are blaming Covid-19 for the deaths of patients who have Covid-19 in tandem with other diseases. According to Bhakdi, this is a dangerous medical tactic and stokes unneeded fear. In the UK, Peter Hitchin writes that figures coming from Public Health England (PHE) are incredibly skewed. The agency, he says, marks that someone has died from Covid-19 as long as they have tested positive for the virus beforehand.[2] He alleges there is little research done at PHE to determine if Covid-19 was the cause of the deaths, but that instead someone could test positive for the virus, fully recover, and then be hit by a bus and PHE would still count their death as a Covid-19 fatality.

Counter arguments

Reopening the country and taking the chance that Covid-related death counts are rooted in falsehoods or mishandlings of data could result in worse real death rates and horrendous loss of life for the country.

Proponents

Premises

Rejecting the premises

References

  1. https://www.youtube.com/watch?v=JBB9bA-gXL4&ab_channel=Prof.Dr.med.SucharitBhakdi
  2. https://www.dailymail.co.uk/debate/article-8537489/PETER-HITCHENS-Face-masks-turn-voiceless-submissives.html
This page was last edited on Monday, 26 Oct 2020 at 14:46 UTC

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