Charles Walker, Vice Chair of the 1922 Tory backbench committee in the Commons tells TWTW that he thinks the government knew it intended to “cancel” Christmas on Wednesday or Thursday but waited for Parliament to rise to do it. Says many of his colleagues find this “egregious.”

When put to Walker that Matt Hancock said this morning that wasn’t the case, it was the briefing on Friday which prompted the decision, Walker says: “Hmm yeah...well I’d have to disagree with the SoS on that.” So he’s either saying Hancock isn’t being truthful or is misinformed.
Walker: “Surely at some stage a senior government minister has say I’ve offered my resignation to the Prime Minister and the Prime Minister has to say- very early I’ve had to accept this.”

Reminder- Charles Walker is Vice Chair of the Tory backbench committee.
Walker heavily implies it’s Matt Hancock he wants to see resign: “I’m not asking for the government to collapse. I’m asking for a Secretary of State to take some responsibility.”
The Charles Walker interview is extraordinary in what he is inferring. A senior Conservative MP is essentially accusing his govt and ministers of deceit about what they knew about the new strain and when and by implication the timing of the new lockdown.
Whether it’s true or not, the nature of the accusation and where it’s come from, is extraordinary and a sign of how febrile the relationship between Number 10 and the backbench is right now.
NB this backbench discontent is likely why we’re hearing a ramped up tone from No10 on no deal.
Charles Walker: “The government in my view knew on Thursday, possibly even on Wednesday they were going to pull the plug on Christmas but they waited til Parliament had gone. That on top of everything else is a resigning matter.”
More Tory discontent directed at the Health Sec 👇 https://t.co/7PKm9SRAcg

More from Lewis Goodall

More from Government

The Government is making the same mistakes as it did in the first wave. Except with knowledge.

A thread.


The Government's strategy at the beginning of the pandemic was to 'cocoon' the vulnerable (e.g. those in care homes). This was a 'herd immunity' strategy. This interview is from


This strategy failed. It is impossible to 'cocoon' the vulnerable, as Covid is passed from younger people to older, more vulnerable people.

We can see this playing out through heatmaps. e.g. these heatmaps from the second


The Government then decided to change its strategy to 'preventing a second wave that overwhelms the NHS'. This was announced on 8 June in Parliament.

This is not the same as 'preventing a second wave'.

https://t.co/DPWiJbCKRm


The Academy of Medical Scientists published a report on 14 July 'Preparing for a Challenging Winter' commissioned by the Chief Scientific Adviser that set out what needed to be done in order to prevent a catastrophe over the winter
Which metric is a better predictor of the severity of the fall surge in US states?

1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020

Can you guess which plot is which?


The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.

However, there is a *strong* correlation when using the margin of Biden's victory (right).

Infections % from
https://t.co/WcXlfxv3Ah.


This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.

Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.

But political lean.

One can argue that states that lean Democrat are more likely to implement restrictions/mandates.

This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.

We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).

https://t.co/BxBBKwW6ta


To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.

This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!

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