Jean Fisch Profile picture
Jul 20 18 tweets 6 min read Twitter logo Read on Twitter
I continue to see talks of high unexplained excess deaths in England and Wales in S1 2023

This is NOT confirmed by data by occurrence date and is an artefact resulting from
/ reporting by registration date
/ policy of only registering deaths once cause is assigned

THREAD Image
Just to make my point crystal clear

The S1 2023 deaths by registration date excl covid are POSITIVE and high which signals lots of unexplained deaths

Yet, when using deaths by occurrence date (as one should), the same total is NEGATIVE. So in fact no/few unexplained deaths

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If you think that this effect is just the result of the fact that I used the ONS baseline which is not a proper choice

The same conclusion holds true when using the approach that CMI proposes (ie based on 2019 mortality rates and adjusted for population development)

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Why is this so? Because of TWO main factors

Factor 1: The huge wave at the end of 2022 led to an unusually high amount of 2022 deaths being registered in 2023 (I estimate 7k more than in previous years)

So deaths by registration inflate the true death toll in 2023

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But that's not the end of the story: There is a 2nd more pernicious factor playing here

E+W is unique in that it only registers deaths once cause of death is assigned

Other countries register unclear deaths under a temporary ICD code and correct it once the cause is clear

4/
The weakness of the E+W system is that deaths that require to go through coroners (as is often the case in younger age bands) can take a year or more before they get registered

So the death data by occurrence date takes much longer to be complete

5/
Just to illustrate the magnitude of the issue: I found some data by age and occurrence for England

It shows how, at the end of May 2023

/ the last 18 months of the 15-44 data
/ the last 6-9 months of the 45-64 data

were essentially materially incomplete

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Here another way to show this based for the 15-44 age band

In 2022, ONS shared the same dataset by occurrence for deaths registered up to May 2022

If you compare it with the dataset with deaths registered up to May 2023, you see how the data diverges over the last 18 months

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The registration date for many deaths in younger age bands will be MUCH later (up to 18 months) than death occurrence

This means that the data by registration date will not reflect the timely pattern of the deaths in these age bands (compare blue and black line)

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But as, I explained yesterday, this has other consequences: If, as is likely in a pandemic, there are MORE deaths going through coroners, then X months later, deaths by registration will see a (fake) increase

And this is what I suspect is currently happening in 2023 as well

9/
Unlike previous years, there were much more deaths registered in May-Jun 2023 than occurred

(the deaths occured is the result of an estimate made by ONS which corrects for lag and is quite precise at top level)

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As I show here, this means that almost all the excess mortality seen in the data by registration date in May-Jun 2023 is the result of deaths that occurred before May

11/

It took me quite a while to understand why deaths by registration were so off vs. the actual situation

What happens is that registration-based data is quite robust if one year is like another (as it was pre-pandemic)

12/
However, if, as is the case in a pandemic, there are "one-off" and lots of unusual events, constraints on registration capacity, etc., the data by registration date starts to be driven by noise instead of underlying death occurrences

And this what we are currently seeing

13/
So deaths by registration date are currently not suited for analysing excess mortality in England+Wales as it is affected by

/ much higher than usual spillover from 2022 to 2023

/ likely catch-up of past occurrences only registered now

/ timely noise in younger age bands

END
@AdeleGroyer (by significant, I mean 1-2% which is essentially within band of uncertainty)

That's why I was getting more and more concerned about the difference of message between registration date data and occurrence one

But happy to be proven wrong, as you know! :-)
@AdeleGroyer And of course, just to be clear: no topline excess does not mean no excess: It could well be that there is negative excess in older age bands and more positive in younger ones

Here the data from the 65-84 which is pretty complete up to Mar 23 and there is no excess before covid Image
NB: I put this thread on hold until I clarify seemingly contradictory elements
/ I find the ONS modelled deaths remarkably accurate
/ However, they imply an unrealistic shortening of the death registration lag

More to follow once I understand what's happening Image

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More from @Jean__Fisch

Jun 1
This paper making the rounds at the moment claims that "excess deaths started in Mar 2021 in GER and is unlikely to come from covid but matches vaccines"

It is rigged with issues which basically invalidate its claim

Let me go through the major ones⤵️

cureus.com/articles/14941…
The key issue is that the authors did not take info account that in the absence of flu the winter peak will be displaced

Once you correct for this, excess deaths match covid deaths in 2021

1/

Also the study relies for covid deaths on RKI

As elsewhere, RKI does not cover all deaths involving covid in 2022 (it underestimates them by 30% based on data up to 4/22)

Once corrected,there is no significant excess beyond covid and flu in 2022

2/

Read 7 tweets
Jun 1
Scotland has been reporting continues excess deaths (and this beyond covid) since November, even after corrections for mortality and population trend

However, the data by registration date is a bit misleading and a look at data by occurrence provides better insights ⤵️ Image
Scotland provides data by occurrence by age on a monthly basis which allows one to make a proper assessement against expected deaths from population and mortality trends

And what comes through is that there are TWO periods of excess: "Xmas 22" and "Mar-Apr 23"

1/ Image
Not only does Scotland provide monthly data by occurrence, it also provides it by leading cause

And it is pretty clear to see that there was a spike of respiratory and covid in Mar-Apr 2023 (which, as so often, also pushes up other death categories: heart, Alzheimer, etc.)

2/ Image
Read 8 tweets
May 12
This is actually quite insightful and shows how prior beliefs blurs and distorts the situation

Natural immunity was absolutely not divisive: It's value was clear but no gov was prepared to accept the costs associated with it until vaccines came

1/5
In particular, the impact of an "R0=2.5 / IFR >>0.5%" virus is such that no shielding mecanisms was deemed sufficiently secure to let circulation run high without taking uncalculated risks on the death toll

(here a little check I did a while back)

2/5

Also Sweden started to look at much firmer circulation reduction in Nov 2020, when the second wave hit and it was clear to its governments that IFR was around 0.6% and not 0.1% when defining its approach during the Spring 2020 wave

3/5

Read 6 tweets
May 9
Vaccine harm deserves better than the deplorable show that vaccine sceptics are offering so here an update of fatality from Germany (up to April 2022):

The death rate due to covid vaccination was at roughly 1.8 deaths per million doses administrated in early 2022 Image
Quick add ons to forecome obvious questions

/ No need to remind me that, just as with long covid, fatality is not everything (I know): I could not find hospitalizations or sequels data

/ Unfortunately, the German monthly death data by cause is not split by age
I just realize that in fact, Germany seems to have experienced a 4x higher death rate due to covid 19 vaccine than England up to April 2022

Read 4 tweets
Apr 8
While Dr. Gupta's claim that new Danish data vindicated her low estimation of IFR in Mar '20 is incorrect, I still wondered how this estimate came about

This interview provides answers and highlights once more IFR's key role in a pandemic response ⤵️

From the interview, it is clear that Dr. Gupta’s low IFR estimate back in 2020 came from a set of considerations which reinforced each other

1) Covid-19 is a SARS virus and the world had been exposed to SARS before
-> Some immunity was there possible / likely

1/N
2) Covid showed the classic bell-shaped curve in China and in Italy which one expects from models when a virus comes and goes away
-> It is therefore possible that the going away was the result of reaching high levels of infections (60%? 70%?)

2/N
Read 18 tweets
Apr 5
In this @unherd column, @SunetraGupta asks the Q: "how wrong was I to suggest that average IFR was 0.05-0.10% back in 2020?"

The answer is
- "By a factor of 5-10 for DNK" (per official data)
- "By a factor 5-25 overall" if UK is anything to go by

It's quite simple really ⤵️
@unherd @SunetraGupta @DSTdk official 2020 death toll "FOR COVID" is 1,078

Source: dst.dk/en/Statistik/e…

@SSI_dk studies put covid prevalenced at 4.1% in Dec 2020

Source: pubmed.ncbi.nlm.nih.gov/34420152/

So the IFR in DNK in 2020 was 1,078/5,8m/0.04% = ~0,45%

ie "5-10x higher than 0.05-0.1%"

1/3 Image
So what happened? This person used an average over the pandemic for DNK

The thing is that 80-90% of the infections happened in 2022 in DNK: So average IFR actually means 2022 IFR

As the UK data shows, IFR dropped by almost an order of magnitude in 2022 (with Omicron + vax)

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Read 4 tweets

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