Five years on, the countries that never locked down, don't appear to be much different in terms of pandemic excess deaths compared to neighbouring countries according to the BBC. 🤔

🧵(1/5)

bbc.com/future/article… This is quite a departure from the June 2020 BBC article that claimed lockdowns saved millions of lives in Europe alone.

The 2020 BBC article was based on the Imperial College London paper in Nature by Flaxman et al.

(2/5)

bbc.com/news/health-52…

How many lives did Covid vaccines save during the pandemic?

Most studies calculate a number based on an "assumed" level of protection against death, with numbers varying from 313 per mil (Ioannidis, 2024) to 2,500 per mil (Mellis, 2022).

I propose a different method.

(1/7) There are a handful of countries that vaccinated >90% of their populations before infection.

Their C-19 deaths per million ranged between 1,000 and 2,000 per million.

In Europe and the Americas, C-19 deaths averaged between 2,790 and 3,150 per million (700-2,200 higher).

(2/7)

Lockdowns – a case of scientific injustice.

Suppression as a concept did not exist before 2020.

Pre-pandemic plans did not ignore it because it planned for the wrong pandemic.

It was ignored, as without timeous vaccines, it would be futile.

#covidinquiryreport

🧵(1/11) Using costly measures to delay infections, only became worthwhile considering in a scenario where a significant portion of people had the hope of getting vaccinated prior to first infection.

It is this change that lead to the abandonment of pre-pandemic plans.

(2/11)

What was the relative mortality burden of Covid-19 for different ages during the acute phase of the pandemic (w12/2020-w11/2021) in England?

The relative burden was calculated as Covid-19 mortality as a percentage of pre-pandemic mortality.

🧵(1/5) Both Covid-19 mortality and all cause mortality increase exponentially with age (straight line on log graph). However, the slope is steeper for Covid-19.

The implication is that the burden of Covid was significantly higher at the older ages.

(2/5)

Crying Wolf One Time Too Many

It is exactly 2 years ago that the UK government ignored scientists’ advice to tighten restrictions to combat Omicron.

Cabinet met on 20 December 2021 and decided to persist with Plan B despite SAGE’s apocalyptic scenario for Plan B.

(1/9) Experts accused the government of ignoring the latest modelling by SAGE which pointed to between 3,000 and 10,000 hospitalisations a day, and between 600 and 6,000 deaths a day without additional restrictions.



(2/9) bmj.com/content/375/bm…

#CovidInquiry

Unrealistic worst case scenarios

On 7 July 2021 SAGE published daily hospital admission scenarios reaching 10,000 per day at the upper bound.

The range was so wide, it was displayed on a log scale!

Daily hospitalisations remained below 800 (grey line).

(1/7) Most remaining restrictions were to be lifted on 19 July 2021, so the worst case cannot be regarded as a counterfactual scenario.

Here is the range of daily hospital admissions plotted on a normal scale to illustrate how wide the range of outcomes were.

(2/7)

What will happen if one day AI develops a sense of self awareness and a spark of consciousness?

A story by ChatGPT.

(1/4) (2/4)

In 2020 the BBC reported that lockdowns saved millions of lives.

It was based on a paper by Flaxman et al published in Nature.

Here I redo the same analysis for the UK, this time using C-19 deaths by date of death.

(1/7) Using deaths data by date of death, instead of reporting date, for the UK, will change the conclusions of the Flaxman paper.

Deaths by date of death happened 3-5 days earlier which would put the effect ascribed to the lockdown, before the lockdown.

(2/7)

Did the C-19 vaccine increase non-Covid mortality levels in England?

When comparing the "Second dose, at least 6 months ago" group against the unvaccinated, the data is not looking good.

but for the ever vaccinated, the trend is the opposite.
😕

(1/7)

ons.gov.uk/peoplepopulati…


How is this seemingly conflicting phenomena even possible?

Both the apparent increase and the apparent reduction in mortality can be explained by the healthy vaccinee effect.

(2/7)

ONS has released new deaths by vaccination data for England.

The data allows us to gauge the vaccine benefit in the absense of the healthy vaccinee effect.

The graphs shown are all age standardised.

(1/7)

ons.gov.uk/peoplepopulati…
The healthy vaccinee effect can be gauged by the difference between the unvaccinated non-Covid-19 mortality minus the ever vaccinated non-Covid-19 mortality.

It starts off high and reduces over time.

(2/7)

Covid-19 #diseasemodelling

How a lack of basic sanity checks resulted in major modelling errors and expert errors during the pandemic.

For balance I list examples on both sides, some underestimating severity, some overestimating severity.

(1/8) On 17 April 2020, Johan Giesecke (Sweden) estimated a Covid-19 IFR of 0.1% and a first wave attack rate of 50%.

The IFR turned out to be 0.58% in Sweden after the first wave with an attack rate of only 6%.

(2/8)

Royal Society report on Covid-19 interventions:

If you exclude ethical, legal, social, economic and other health effects, the study shows that the most stringent measures (stay at home orders) were the most effective.

(1/5) The study neglects the scenario of a failed hard and early lockdown, and focuses on countries that succeeded in elimination:



(2/5)

https://twitter.com/pieterstreicher/status/1693635182102814756

Lockdowns are highly unstable.

If elimination is possible, going hard and early results in a shorter lockdown.

If elimination is impossible, going hard and early prolongs the lockdown. The end is bound to be tragic.

(1/5) Lockdown proponents point to New Zealand and China that succeeded in elimination (at least for some time).

Lockdown critics point to Peru, that locked down hard and early, but ended with the highest Covid-19 deathtoll and some of the longest cumulative lockdowns.

(2/5)

Matt Hancock again advocating for harder, earlier lockdowns.

But does an early and hard lockdown necessarily result in a better ourcome?

#CovidInquiryUK



(1/5)

https://twitter.com/statsjamie/status/1673636540122034178

Myth:

A rapid hard lockdown would have achieved elimination relatively quickly.

Reality:

A rapid hard lockdown could only achieve temporary elimination in a handful of countries.

In most countries it would have resulted in an unsustainably long lockdown.

(2/5)

Was the believed benefit of hard lockdowns (stay at home orders) over and above more sensible mitigation measures a delusion?

Why a "reasonable worst case" scenario can create a delusion on lockdown effectiveness.

(1/6) In June 2020, the BBC reported that lockdowns in Europe saved millions of lives.

The lives saved were calculated by subtracting the actual lives lost from a "do nothing" counterfactual scenario.

(2/6)

bbc.com/news/health-52…

Lockdowns are costly exercises, so one would think that 16 months into the pandemic, modellers would know what is likely to happen after the final phase of unlocking in England.

Here SAGE-SPI-M shows exactly what they expect to happen after "freedom day" on 19 July 2021:

(1/6) And here is the actual hospitalisations (thin grey line), right in the middle of the confidence interval during August.

But wait, this confidence interval seems rather wide (100-10,000 hospitalisations per day!).

And the Y-axis is plotted on a log scale.

(2/6)

Why was modelling accuracy so poor during the Covid-19 pandemic?

This thread argues that the move away from ‘descriptive modelling’ to ‘mechanistic modelling’ in the disease modelling community, was partly responsible for this blind spot.

(1/14) Disease modelling moved away from ‘descriptive’ modelling to ‘mechanistic’ modelling in the early 20th century according to Adam Kucharski in his book The Rules of Contagion (2020).

(2/14)

Were lockdown policies a form of contagion?

Here I use 'The Rules of Contagion' by @adamjkucharski to critically evaluate the spread of lockdown policies.

1/ Lockdowns were foreseeably harmful to the global poor, and this is now widely accepted.

The public health principle, that 'one size does not fit all' was ignored.

2/

sciencedirect.com/science/articl…

(1/6)

Western Cape - South Africa - 1st wave analysis.

In contrast to other countries, South Africa consistently relaxed restrictions throughout the 1st wave.

This provided a controlled experiment of the effect of stay at home orders in the SA context. (2/5)

(2/6)

Using an infection fatality rate of 0.6%, the exponential phase ended when estimated attack rates reached only 1.2%.

R dropped below 1.0 when attack rates were only 4% (est).

When the wave ended, attack rates were at 11% (est).

(1/10)

Perception vs reality

Here I plot daily cases in London in March 2020 as well as fatal infections (18 days earlier than C-19 deaths).

13 March is when SAGE realised cases were much higher than initially expected.

19 March is when fatal infections peaked in London. (2/10)

The time between 13 March when cases were visibly increasing, and 19 March when fatal infections peaked, was only 6 days.

What are the chances that Wuhan, China, locked down before fatal infections peaked?

I would say the chances were very slim.

(1/9)

If goverments "followed The Science", then Tomas Pueyo, Silicon Valley Tech Executive, must be "The Science".

(2/9)

Here Pueyo explains why mitigation is not much different to doing nothing.

tomaspueyo.medium.com/coronavirus-th…