Carl I think your hard hitting summary at the end of this podcast should perhaps be where you start when you give evidence. There is no point "beating round the bush".
"It's very clear to me that...... at some point people are going to recognise the poor quality and the limitation [of modeling outbreaks of respiratory infection] and it may come and go a bit like Farr's law would predict. It came with the advent of modern computing and it may disappear just as quick because at the moment I consider it is doing more harm than being helpful."
Then, hopefully you will be asked how modelling the epidemic caused harm, why the quality of modelling evidence is so poor and how Farr's Law is so relevant. But don't make it personal - you might sound that your harbouring a bit of a "chip".
All the very best on Thursday. We all need intelligent, persistent, independent people like you so stand up and be counted in these strange times.
On the subject of dodgy modelling being used to fear-monger and create a massive vaccine market...
In Imperial College Report 9, published in March 2020, Neil Ferguson et al said, "The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic".
I challenged Neil Ferguson about this in my email to him dated 5 August 2021, saying:
This is a very alarming statement, as the US CDC reports the H1N1 virus spread around the world in 1918-1919, resulting in estimated deaths of at least 50 million.[5] This was in a global population of around 1.8 billion at the time.
If the CDC's estimate of H1N1 deaths in 1918-1919 is accurate - with a 2020 global population of 7.8 billion - it's equivalent to 216 million deaths in two years, i.e. the insinuation from your Imperial College Report 9 is that COVID-19 could potentially amount to 216 million deaths in the world in the same time period.
Professor Ferguson, while you inferred COVID-19 represented a public health threat in the same league as the 1918 H1N1 influenza pandemic, a few days after your report was published, Public Health England reported: "As of 19 March 2020, COVID-19 is no longer considered to be a high consequence infectious disease (HCID) in the UK".
According to Public Health England (PHE): "The 4 nations public health HCID group made an interim recommendation in January 2020 to classify COVID-19 as an HCID. This was based on consideration of the UK HCID criteria about the virus and the disease with information available during the early stages of the outbreak. Now that more is known about COVID-19, the public health bodies in the UK have reviewed the most up to date information about COVID-19 against the UK HCID criteria. They have determined that several features have now changed; in particular, more information is available about mortality rates (low overall), and there is now greater clinical awareness and a specific and sensitive laboratory test, the availability of which continues to increase." (My emphasis.)
It was also noted that "The Advisory Committee on Dangerous Pathogens (ACDP) is also of the opinion that COVID-19 should no longer be classified as an HCID". (See attached HCID webpage which was last updated 17 June 2020, to compare with the HCID webpage accessible online today: High consequence infectious diseases (HCID). Last updated 12 May 2021.)
Subsequent PHE HCID reports don't even mention SARS-CoV-2/COVID-19.
This is extremely confusing Professor Ferguson.
Your Imperial College Report 9 insinuated the world could be facing approximately 216 million deaths as a consequence of COVID-19, and that an aggressive suppression strategy would "need to be maintained until a vaccine becomes available (potentially 18 months or more) - given that we predict that transmission will quickly rebound if interventions are relaxed".
Despite the fact COVID-19 was downgraded from a high consequence infectious disease on 19 March 2020, and it was known it had low overall mortality, the mainstream media has maintained very alarming reporting for the past 17 months re the number of 'cases' and deaths attributed to COVID-19.
Professor Ferguson, according to Statista[6], around 4.25 million deaths have been attributed to COVID-19 globally in say the past 17 months, likely mostly in elderly people with comorbidities, this is well below the potentially 216 million deaths inferred by you with your comparison with the 1918 H1N1 influenza pandemic.
The 4.25 million global deaths figure over 17 months attributed to COVID-19 must also be seen in the context of deaths expected in the global population of 7.9 billion during that time, i.e. around 83.9 million deaths over 17 months.[7]
Professor Ferguson, clearly something isn't adding up here...can you please clarify the situation?
How did you come up with data that suggested COVID-19 was on a par with the 1918 H1N1 influenza pandemic, and thereby unleash a grossly disproportionate response to COVID-19?
Additional note: In my email I asked Neil Ferguson if he was the 'modeller' who shared a taxi with Andrew Pollard in mid-January 2020 - I subsequently discovered the modeller in the taxi was John Edmunds, after reading this article on The BMJ: How the Oxford-AstraZeneca covid-19 vaccine was made: https://www.bmj.com/content/bmj/372/bmj.n86.full.pdf
Really good points on terminology and worst case scenarios. As you say, it doesn't really matter that there are technical differences between the definitions of prediction, projection and scenario if no-one understands the terms and if they are all conflated in the minds of people
to mean this is the forecast of what will happen if we don't intervene.
And even though you can say 'this is a worse case scenario and it is unlikely to be that bad', it doesn't really help because you have already anchored that worse case number in the minds of the politicians, but also the SAGE team. So, just like Kahneman talked about the anchoring effect, this would lead to more extreme responses than if no 'extreme but unlikely' scenario was presented. Everyone, from SAGE members to politicians, was under tremendous pressure- people were thinking not only of what was the right thing to do, but also more selfishly, as they didn't want to be blamed and have their careers tarnished. Without the imagined worst case scenarios people might have been a bit more circumspect about taking radical actions which would they knew would have significant harms. It takes a very special kind of person (like Tegnell) to resist the bias to action in such circumstances, especially when the media are starting to push for lockdowns and whip up the public.
Just one thing on Farr's law that I was wondering as I don't think the modellers ever denied that the cases would go up and down in a predictable way, like all infectious disease epidemics. Their argument was that by intervening the peak of the curve would be lower - eventually just as many people would be infected but more spread out so that the health service wasn't overwhelmed. I think Valances graph just showed the exponential bit of the 'prodiction' though he would have known that it wouldn't keep going up like that. In Claire Craig's book she talks about the Gompertz curve and that you can map out the trajectory from what you know about the rate of growth and then rate of slowing of the infection. So you can predict the peak from what you know quite early on. Daft question but if you intervene as the rate of growth is already slowing does it actually make any difference to the peak? I'm guessing it must or why talk of flattening the curve.
Carl I think your hard hitting summary at the end of this podcast should perhaps be where you start when you give evidence. There is no point "beating round the bush".
"It's very clear to me that...... at some point people are going to recognise the poor quality and the limitation [of modeling outbreaks of respiratory infection] and it may come and go a bit like Farr's law would predict. It came with the advent of modern computing and it may disappear just as quick because at the moment I consider it is doing more harm than being helpful."
Then, hopefully you will be asked how modelling the epidemic caused harm, why the quality of modelling evidence is so poor and how Farr's Law is so relevant. But don't make it personal - you might sound that your harbouring a bit of a "chip".
All the very best on Thursday. We all need intelligent, persistent, independent people like you so stand up and be counted in these strange times.
On the subject of dodgy modelling being used to fear-monger and create a massive vaccine market...
In Imperial College Report 9, published in March 2020, Neil Ferguson et al said, "The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic".
I challenged Neil Ferguson about this in my email to him dated 5 August 2021, saying:
This is a very alarming statement, as the US CDC reports the H1N1 virus spread around the world in 1918-1919, resulting in estimated deaths of at least 50 million.[5] This was in a global population of around 1.8 billion at the time.
If the CDC's estimate of H1N1 deaths in 1918-1919 is accurate - with a 2020 global population of 7.8 billion - it's equivalent to 216 million deaths in two years, i.e. the insinuation from your Imperial College Report 9 is that COVID-19 could potentially amount to 216 million deaths in the world in the same time period.
Professor Ferguson, while you inferred COVID-19 represented a public health threat in the same league as the 1918 H1N1 influenza pandemic, a few days after your report was published, Public Health England reported: "As of 19 March 2020, COVID-19 is no longer considered to be a high consequence infectious disease (HCID) in the UK".
According to Public Health England (PHE): "The 4 nations public health HCID group made an interim recommendation in January 2020 to classify COVID-19 as an HCID. This was based on consideration of the UK HCID criteria about the virus and the disease with information available during the early stages of the outbreak. Now that more is known about COVID-19, the public health bodies in the UK have reviewed the most up to date information about COVID-19 against the UK HCID criteria. They have determined that several features have now changed; in particular, more information is available about mortality rates (low overall), and there is now greater clinical awareness and a specific and sensitive laboratory test, the availability of which continues to increase." (My emphasis.)
It was also noted that "The Advisory Committee on Dangerous Pathogens (ACDP) is also of the opinion that COVID-19 should no longer be classified as an HCID". (See attached HCID webpage which was last updated 17 June 2020, to compare with the HCID webpage accessible online today: High consequence infectious diseases (HCID). Last updated 12 May 2021.)
Subsequent PHE HCID reports don't even mention SARS-CoV-2/COVID-19.
This is extremely confusing Professor Ferguson.
Your Imperial College Report 9 insinuated the world could be facing approximately 216 million deaths as a consequence of COVID-19, and that an aggressive suppression strategy would "need to be maintained until a vaccine becomes available (potentially 18 months or more) - given that we predict that transmission will quickly rebound if interventions are relaxed".
Despite the fact COVID-19 was downgraded from a high consequence infectious disease on 19 March 2020, and it was known it had low overall mortality, the mainstream media has maintained very alarming reporting for the past 17 months re the number of 'cases' and deaths attributed to COVID-19.
Professor Ferguson, according to Statista[6], around 4.25 million deaths have been attributed to COVID-19 globally in say the past 17 months, likely mostly in elderly people with comorbidities, this is well below the potentially 216 million deaths inferred by you with your comparison with the 1918 H1N1 influenza pandemic.
The 4.25 million global deaths figure over 17 months attributed to COVID-19 must also be seen in the context of deaths expected in the global population of 7.9 billion during that time, i.e. around 83.9 million deaths over 17 months.[7]
Professor Ferguson, clearly something isn't adding up here...can you please clarify the situation?
How did you come up with data that suggested COVID-19 was on a par with the 1918 H1N1 influenza pandemic, and thereby unleash a grossly disproportionate response to COVID-19?
I didn't receive a response from Neil Ferguson...
Here's the link to my email: https://vaccinationispolitical.files.wordpress.com/2021/08/neil-ferguson-and-andrew-pollard-sharing-a-taxi...-1.pdf
Additional note: In my email I asked Neil Ferguson if he was the 'modeller' who shared a taxi with Andrew Pollard in mid-January 2020 - I subsequently discovered the modeller in the taxi was John Edmunds, after reading this article on The BMJ: How the Oxford-AstraZeneca covid-19 vaccine was made: https://www.bmj.com/content/bmj/372/bmj.n86.full.pdf
Really good points on terminology and worst case scenarios. As you say, it doesn't really matter that there are technical differences between the definitions of prediction, projection and scenario if no-one understands the terms and if they are all conflated in the minds of people
to mean this is the forecast of what will happen if we don't intervene.
And even though you can say 'this is a worse case scenario and it is unlikely to be that bad', it doesn't really help because you have already anchored that worse case number in the minds of the politicians, but also the SAGE team. So, just like Kahneman talked about the anchoring effect, this would lead to more extreme responses than if no 'extreme but unlikely' scenario was presented. Everyone, from SAGE members to politicians, was under tremendous pressure- people were thinking not only of what was the right thing to do, but also more selfishly, as they didn't want to be blamed and have their careers tarnished. Without the imagined worst case scenarios people might have been a bit more circumspect about taking radical actions which would they knew would have significant harms. It takes a very special kind of person (like Tegnell) to resist the bias to action in such circumstances, especially when the media are starting to push for lockdowns and whip up the public.
Just one thing on Farr's law that I was wondering as I don't think the modellers ever denied that the cases would go up and down in a predictable way, like all infectious disease epidemics. Their argument was that by intervening the peak of the curve would be lower - eventually just as many people would be infected but more spread out so that the health service wasn't overwhelmed. I think Valances graph just showed the exponential bit of the 'prodiction' though he would have known that it wouldn't keep going up like that. In Claire Craig's book she talks about the Gompertz curve and that you can map out the trajectory from what you know about the rate of growth and then rate of slowing of the infection. So you can predict the peak from what you know quite early on. Daft question but if you intervene as the rate of growth is already slowing does it actually make any difference to the peak? I'm guessing it must or why talk of flattening the curve.
Thank you for sharing this.
I have one comment and I am probably kicking in an open door.
I have the impression the inquiry audience is very mixed with eminent scientists, politicians, lay persons, journalists?
Maybe a good idea to make sure your evidence has a high impact to use the ‘sandwich’ method?
First say what you intend to say
Then say it, providing the evidence
Lastly repeat what you were going to say.
Maybe that way people will at least remember the key message in your answer.
I admit I have never stood for an inquiry and have not had any media training.
Good luck tomorrow!
Actually you don’t need luck, just people to start listening.
(Could you also give a transcript of the audio?)
Good podcast: clearly presented and informative. Good luck tomorrow.