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Seven Peer-Reviewed Studies That Agree: Lockdowns Do Not Suppress the Coronavirus – Lockdown Sceptics

There have been at least seven peer-reviewed studies which look at the question of lockdowns from a data point of view, and all of them come to the same basic conclusion: lockdowns do not have a statistically significant relationship with Covid cases or deaths. Here is a list of them with a key quote for ease of reference.

https://lockdownsceptics.org/2021/04/15/seven-peer-reviewed-studies-that-agree-lockdowns-do-not-suppress-the-coronavirus/

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Opinion

PCR-based COVID testing has failed and is not a proper basis to lockdown the nation, let alone decide on tiers for restrictions – Mike Yeadon, Lockdown Sceptics

Briefing paper for MPs authored by:

  • Clare Craig BM BCh FRCPath
  • Jonathan Engler MBChB LLB
  • Mike Yeadon BSc Hons (Biochem-tox) PhD (Pharmacol)
  • Christian McNeill LL.B and Dip LP

Stop mass-testing using PCR in the UK and replace with Lateral Flow Tests where required. If we are correct, this single measure alone will cause a sudden drop in “cases” (as seen in Liverpool) and allow the UK to return to normal life within weeks.

Other recommendations as detailed later in this document. It should be noted that legal cases and technical challenges to PC

https://lockdownsceptics.org/wp-content/uploads/2020/11/MP-briefing-26-Nov-2020.pdf

Categories
Opinion

Code Review of Ferguson’s Model

All papers based on this code should be retracted immediately. Imperial’s modelling efforts should be reset with a new team that isn’t under Professor Ferguson, and which has a commitment to replicable results with published code from day one. 

On a personal level, I’d go further and suggest that all academic epidemiology be defunded. This sort of work is best done by the insurance sector. Insurers employ modellers and data scientists, but also employ managers whose job is to decide whether a model is accurate enough for real world usage and professional software engineers to ensure model software is properly tested, understandable and so on. Academic efforts don’t have these people, and the results speak for themselves.