What is the infection fatality rate (IFR) of Covid 19 now?

originally posted by: Asmodeus3

originally posted by: chr0naut

originally posted by: Asmodeus3
a reply to: chr0naut
Infection fatality rate of Covid-19

pubmed.ncbi.nlm.nih.gov...

Conclusions

All systematic evaluations of seroprevalence data converge that SARS-CoV-2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5-2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries and locations.

Estimates before the rolling out of the vaccines. And made by one of the top epidemiologists in the world, Dr John Ioannidis who is probably the most cited in his field. If not the most cited scientist.

So a fairly mild disease for the vast majority of us given that it mostly affected the elderly with comorbidities and the clinically vulnerable.

And despite the fact that it was initially presented as some sort of the Spanish Flu by the establishment.

IFR of Spanish Flu = 10%
IFR of Covid-19= 0.15%

I have explained why I believe the IFR is a 'rubbery' figure.

And why seroprevalence is not an optimal measure for a primarily respiratory disease.

Yes I know. But your opinion is not correct.
CFR is a poor representation of how deadly a disease is. That's why most research is dedicated in trying to find the actual number of people getting infected which will include those with minor symptoms who never get tested and those who are asymptomatic.

In measuring the CFR then you have a denominator which is a very inaccurate as it represents those who have been tested and confirmed infected with the virus. Those tested and those infected are two very different numbers.

Infection fatality ratio and case fatality ratio of COVID-19. Which showed that out of four studies, there were three in which the IFR of COVID-19 exceeded 10% for some age groups.

And yes, it is the denominator which is the problem. More so for IFR.

Food For Thought - FYI:

Covid-19 was bad enough to shut down most of American Businesses, but not bad enough to close the borders to those who became illegal aliens in 2020 and 2021.

Source: truthsocial.com...

originally posted by: chr0naut

originally posted by: Asmodeus3

originally posted by: chr0naut

originally posted by: Asmodeus3
a reply to: chr0naut
Infection fatality rate of Covid-19

pubmed.ncbi.nlm.nih.gov...

Conclusions

All systematic evaluations of seroprevalence data converge that SARS-CoV-2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5-2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries and locations.

Estimates before the rolling out of the vaccines. And made by one of the top epidemiologists in the world, Dr John Ioannidis who is probably the most cited in his field. If not the most cited scientist.

So a fairly mild disease for the vast majority of us given that it mostly affected the elderly with comorbidities and the clinically vulnerable.

And despite the fact that it was initially presented as some sort of the Spanish Flu by the establishment.

IFR of Spanish Flu = 10%
IFR of Covid-19= 0.15%

I have explained why I believe the IFR is a 'rubbery' figure.

And why seroprevalence is not an optimal measure for a primarily respiratory disease.

Yes I know. But your opinion is not correct.
CFR is a poor representation of how deadly a disease is. That's why most research is dedicated in trying to find the actual number of people getting infected which will include those with minor symptoms who never get tested and those who are asymptomatic.

In measuring the CFR then you have a denominator which is a very inaccurate as it represents those who have been tested and confirmed infected with the virus. Those tested and those infected are two very different numbers.

Infection fatality ratio and case fatality ratio of COVID-19. Which showed that out of four studies, there were three in which the IFR of COVID-19 exceeded 10% for some age groups.

And yes, it is the denominator which is the problem. More so for IFR.

I have linked the same article sometime ago but the global average IFR was always very low.

The global average gives you the best picture of how deadly a disease is, because the IFR for specific age groups varies. For example in the age group 0-19 the IFR was 0.0003% which means 3 deaths per million. Probably something you expect for children and teenagers and young adults.

www.medrxiv.org...

0.0003% at 0-19 years
0.003% at 20-29 years
0.011% at 30-39 years
0.035% at 40-49 years
0.129% at 50-59 years
0.501% at 60-69 years.

*At a global level, pre-vaccination IFR may have been as low as 0.03% and 0.07% for 0-59 and 0-69 year old people, respectively.

From the financial times article

A combination of high levels of immunity and the reduced severity of the Omicron variant has rendered Covid-19 less lethal than influenza for the vast majority of people in England, according to a Financial Times analysis of official data

originally posted by: carewemust
Food For Thought - FYI:

Covid-19 was bad enough to shut down most of American Businesses, but not bad enough to close the borders to those who became illegal aliens in 2020 and 2021.

Source: truthsocial.com...

Didn't Trump already close that border before, and during the COVID lockdowns?

originally posted by: chr0naut

And yes, it is the denominator which is the problem. More so for IFR.

Yup, it's inferred modelling of multi-variate calculus with a lot of assumptions, boundary conditions, optimisation, human behavioural modelling etc...which is why results are/should be given with max(worst case), min (best case), saddle point (likely case).

Co-variate bias and Uncertainty Intervals are innescapable with the method and should always be stated and broken down for age groups, health, co-morbidities, lifestyles etc...It's not meant to be a singular figure, more an educated guess that comes with inherrent innacuracy/uncertainty.

There's a more detailed model/more acurate result for IFR derived in this paper - Link

originally posted by: bastion

originally posted by: chr0naut

And yes, it is the denominator which is the problem. More so for IFR.

Yup, it's inferred modelling of multi-variate calculus with a lot of assumptions, boundary conditions, optimisation, human behavioural modelling etc...which is why results are/should be given with max(worst case), min (best case), saddle point (likely case).

Co-variate bias and Uncertainty Intervals are innescapable with the method and should always be stated and broken down for age groups, health, co-morbidities, lifestyles etc...It's not meant to be a singular figure, more an educated guess that comes with inherrent innacuracy/uncertainty.

There's a more detailed model/more acurate result for IFR derived in this paper - Link

Your claim here that IFR is not meant to be a singular figure is just an assertion of yours which is made for the purpose of presenting Covid-19 as a more pathogenic disease than it is, so to support the various absurd restrictions and lockdowns and the various politics and ideologies associated with these measures.

The IFR has been estimated long time ago by one of the top epidemiologists in the world if not the top one. His papers are the most cited if not the most cited and when you try to search about IFR that what comes at the top of your search.

The IFR of Covid-19 was 0.15% (before any vaccines were available)

The IFR of the Spanish Flu was 10%

Now the IFR of Covid-19 is probably lower than that of the flu if you have a look at the link above.


And yes, to break down your analysis to different age groups and populations helps quite a lot in determining who is most at risk but how deadly a disease is found by dividing the actual number of deaths over the estimated number of total infections. There are excellent epidemiologists such as Dr Ioannidis and his team at Stanford that have provided really good estimations.

The only thing you haven't incorporated in your 'analysis' above is the possible use of fluid dynamics and general relativity in determining the IFR.... What are these boundary conditions??

a reply to: Asmodeus3

No I just have a dergree in Applied Maths, worked with professors exposing lying with numbers in pharmacology and taught med students how to read/analyse papers.

It's how the mathematics of inferred modelling works - both papers you posted are inferred models where the author doesn't provide a singular figure, clearly states the assumptions and presumptions he made, the WHO ones he did was a proper model with proper data - the other with the 0.15% answer is a qualitative not a quantative analysis that makes a lot of good criticisms of others but fails to provide key info of CI/UI, the logic/bias of his co-variates.

Either you've not read them or failed to understand them (likely latter due to repeatedly misquoting and misunderstanding his papers) as he clearly states it's a rough approximation and the ~0.15% 'paper' is meant as a back of a fag packet calculation instead of ultimate model.

A boundary condition is very basic maths to get the max, min values and optimisation equations - both papers you posted use boundary conditions to infer IFR; If you'd read or understood them, you would know this.

As I said, best to learn the difference between ~ and = before learning the maths of inferred IFR modelling so you can criique or appraise papers as at the moment you're just doing a major disservice to his paper and calculation by making it seem as if he doesn't know basic maths or how IFR is estimated.

originally posted by: bastion
a reply to: Asmodeus3

No I just have a dergree in Applied Maths, worked with professors exposing lying with numbers in pharmacology and taught med students how to read/analyse papers.

It's how the mathematics of inferred modelling works - both papers you posted are inferred models where the author clearly states the assumptions and presumptions he made, the WHO ones he did was a proper model with proper data - the other with the 0.15% answer is a qualitative not a quantative analysis that makes a lot of good criticisms of others but fails to provide key info of CI/UI, the logic/bias of his co-variates.

Either you've not read them or failed to understand them (likely case given the repeated misquoting the author.

A boundary condition is very basic maths to get the max, min values and optimisation equations - both papers you posted use boundary conditions to infer IFR; If you'd read or understood them, you would know this.

I have understood well the statistics involved when estimating the IFR. There is no need for a lecture and the number estimated by Dr Ioannidis stands

The IFR of Covid-19 was 0.15%

Now it is much lower. Probably lower then the flu as the FT Article stated above.

If you have worked with Professors exposing lies in Pharmacology then I am sure they could expose the absurd Covid campaign and their absurd claims trying to portray Covid-19 as the Spanish Flu.

Dr Ioannidis is probably the most cited author when it comes to estimations of the IFR . In particular one if his publications that stands in the Bulletin of the WHO has 529 citations. I don't think you can find a paper with more than that. It is a reflection of the quality of the work which is pretty much recognised by everyone as another 529 of researchers in his field have recognised how valuable his work is. That one uses the median value of IFR which is around 0.23%


In a few words the IFR of Covid-19 was always very low and has become even lower with the immunity that has been build up in the population.

If you have concerns then you could direct them to those who tried to terrorise entire populations over a disease that does nothing to most of us. Given that most of us if not all have been exposed to the virus at least once.

a reply to: bastion


I don't need lectures in mathematics by the way and we all understand that these are estimates we are discussing. But very good estimates given by top scientists.

Let me repeat this for you

Conclusions

All systematic evaluations of seroprevalence data converge that SARS-CoV-2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5-2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries and locations.

There is no disservice to his work as you said in an absurd manner. He is the most recognised figure because of this work. And it is clear what he says above.

a reply to: bastion

No I just have a dergree in Applied Maths, worked with professors exposing lying with numbers in pharmacology and taught med students how to read/analyse papers.

Then I am sure you can see where the lies are coming from...

Unless you want engage in vaccine apologetics and denialism of reality just as other members are doing as well as defending the pharmaceuticals. But do you??

So what courses can did you take in your applied maths degree that helped you understand what is going on here.

originally posted by: Asmodeus3

originally posted by: bastion
a reply to: Asmodeus3

No I just have a dergree in Applied Maths, worked with professors exposing lying with numbers in pharmacology and taught med students how to read/analyse papers.

It's how the mathematics of inferred modelling works - both papers you posted are inferred models where the author clearly states the assumptions and presumptions he made, the WHO ones he did was a proper model with proper data - the other with the 0.15% answer is a qualitative not a quantative analysis that makes a lot of good criticisms of others but fails to provide key info of CI/UI, the logic/bias of his co-variates.

Either you've not read them or failed to understand them (likely case given the repeated misquoting the author.

A boundary condition is very basic maths to get the max, min values and optimisation equations - both papers you posted use boundary conditions to infer IFR; If you'd read or understood them, you would know this.

I have understood well the statistics involved when estimating the IFR. There is no need for a lecture and the number estimated by Dr Ioannidis stands

You clearly haven't as you're unaware of what boundary conditions are or relevance of any of the maths involved when they're central to infection modelling.

Dr Ioannidis uses these in his inferred model, data synthesis, his adjusted results and aknowleges them in his limitations of the model.

I am struggling to understand why so many have a vested interest in this virus being more deadly than it is.

If I had to guess, I would say it's more than likely because if it was admitted that it really wasn't that deadly, they have to admit they were fooled.

Anyone wish to address this?

originally posted by: bastion

originally posted by: Asmodeus3

originally posted by: bastion
a reply to: Asmodeus3

No I just have a dergree in Applied Maths, worked with professors exposing lying with numbers in pharmacology and taught med students how to read/analyse papers.

It's how the mathematics of inferred modelling works - both papers you posted are inferred models where the author clearly states the assumptions and presumptions he made, the WHO ones he did was a proper model with proper data - the other with the 0.15% answer is a qualitative not a quantative analysis that makes a lot of good criticisms of others but fails to provide key info of CI/UI, the logic/bias of his co-variates.

Either you've not read them or failed to understand them (likely case given the repeated misquoting the author.

A boundary condition is very basic maths to get the max, min values and optimisation equations - both papers you posted use boundary conditions to infer IFR; If you'd read or understood them, you would know this.

I have understood well the statistics involved when estimating the IFR. There is no need for a lecture and the number estimated by Dr Ioannidis stands

You clearly haven't as you're unaware of what boundary conditions are or relevance of any of the maths involved when they're central to infection modelling

Dr Ioannidis uses these in his inferred model, data synthesis his results and aknowleges them in his limitations of the model.

.

What are they? Since you have mentioned them. I want to see whether you have read the paper or papers before arguing that others haven't read his papers.

And you are mistaken in your assertions if you think that everyone here is a layman or when you post earlier that we should know the difference difference between ~ and =

In which University did you go by the way and what courses did they take?

All models have limitations but still the IFR of Covid-19 was around 0.15% and not as high as the IFR of the Spanish Flu which was around 10%

originally posted by: MaxxAction
I am struggling to understand why so many have a vested interest in this virus being more deadly than it is.

If I had to guess, I would say it's more than likely because if it was admitted that it really wasn't that deadly, they have to admit they were fooled.

Anyone wish to address this?

Because the member above is trying in a foolish way to present Covid-19 as more deadly than it was so to justify his ideologies and beliefs in lockdowns, restrictions, mass vaccinations and all other absurd measures taken. Endless nonsensical claims when in reality they cannot admit that Covid-19 was a very mild disease for most of us.

a reply to: Asmodeus3

He uses the lower boundary 0 and upper bound 1 week after midpoint of study.

I went to UCLan (we do data and stats for NASA/ESA), worked there and UCL creating automated adjustments for the impact agenda, taught modelling and stats at UCL.

So did you read his papers? Do you have any relevant qualifications or work history in this field? If so where? Or is it only me/other people who have to answerr questions.

originally posted by: bastion
a reply to: Asmodeus3

He uses the lower boundary 0 and upper bound 1 week after midpoint of study.

I went to UCLan (we do data and stats for NASA/ESA), worked there and UCL creating automated adjustments for the impact agenda, taught modelling and stats at UCL.

So did you read his papers? Do you have any relevant qualifications or work history in this field? If so where? Or is it only me/other people who have to answerr questions.

You mean UCL in London and not UCLA in California? I suppose UCLan is something different. But don't worry it doesn't make any difference.

First of all I don't think you have answered any questions. You have asserted that we don't know or I don't know the difference between ~ and =
I think your attempt here has failed.

I was the one to mention his papers and you won't see many others linking either pre-prints or peer reviewed papers apart from a few cases.

I can tell you that I am not a layman. It is strange that you come out of nowhere trying to 'lecture' us when another member here was failing to push his messages.

'He uses the lower boundary 0 and upper bound 1 week after midpoint of study'

In which study? And where in the paper?

I find it very strange that you have appeared in the conversation out of nowhere trying to lecture us on nothing other than ~ and = when another member has failed to get his points through... You know what I mean I suppose.

a reply to: Asmodeus3

I find it very strange that you have appeared in the conversation out of nowhere trying to lecture us on nothing other than ~ and = when another member has failed to get his points through... You know what I mean I suppose.

This might be a long shot but is possible more than one person has a different opinion than you?

originally posted by: MaxxAction
I am struggling to understand why so many have a vested interest in this virus being more deadly than it is.

If I had to guess, I would say it's more than likely because if it was admitted that it really wasn't that deadly, they have to admit they were fooled.

Anyone wish to address this?

Why do so many have a vested interest in this virus bring less deadly than it is?

If I had to guess I would say they its more thsn likely they don't want to admit how foolish they were believing really stupid conspiracy theories.

a reply to: ScepticScot

Alternative opinions are all "absurd and ludicrous", apparently.

originally posted by: Oldcarpy2
a reply to: ScepticScot

Alternative opinions are all "absurd and ludicrous", apparently.

If I agree with you does that mean we are the same person or something?