
Epidemiologist behind Imperial College coronavirus model revises model - r6203
https://www.dailywire.com/news/epidemiologist-behind-highly-cited-coronavirus-model-admits-he-was-wrong-drastically-revises-model
======
martingoodson
This is misinformation. This is not a major revision in any sense. Read the
Imperial College paper. The estimates were different between the 'mitigation'
and 'supression' strategy. The UK have now changed strategy to 'supression'.
Hence the different prediction.

~~~
jtbayly
I've read the Imperial College Paper. Transmissibility is a major change [0].
The original paper says we are only just at the beginning of the time we will
have to spend quarantined over the next 12-18 months, off and on. With the new
transmissibility estimate, it would mean that we are a few weeks away from the
peak and then done with this.

If you can show me I'm wrong, please do.

[https://www.newscientist.com/article/2238578-uk-has-
enough-i...](https://www.newscientist.com/article/2238578-uk-has-enough-
intensive-care-units-for-coronavirus-expert-predicts/)

~~~
triceratops
> Transmissibility is a major change [0]

I'm not sure you read your own link correctly.

"New data from the rest of Europe suggests that the outbreak is running faster
than expected, said Ferguson. As a result, epidemiologists have revised their
estimate of the reproduction number (R0) of the virus. This measure of how
many other people a carrier usually infects is now believed to be just over
three, he said, up from 2.5. “That adds more evidence to support the more
intensive social distancing measures,” he said."

~~~
jtbayly
I'm sorry. You are correct. Although Ferguson attributes most of the benefit
to the lockdown, he _does_ acknowledge a change of R0 further revising the
numbers down.

Where I got confused was attributing some of the things said by Gupta (behind
the Oxford model) to Ferguson (behind the Imperial College model).

------
nicois
They claim half the population is already infected. So conduct a random
sample, test 50 people and you would expect 25ish MTO be positive, with most
showing no symptoms. If so, then herd immunity is indeed a thing.

I have my doubts that the numbers would support this claim. And if so, then
virtually everyone in Spain or Italy would already be a carrier.

The fact that cases were linked to known arrivals also is evidence against
this hypothesis : if a high proportion of carriers were unwitting and
asymptomatic you would expect many of those diagnosed to not have a link to
someone previously diagnosed.

~~~
jtbayly
I agree with your doubts, and I can't make sense of 72% of tests in NY being
negative.

However, the test you need to run is an antibody test, since negative tests
don't tell you whether you've already had it.

------
jtbayly
I'd really like to see this discussed here. I've not seen anybody talking
about this in the US. This is the guy behind the "highly-cited Imperial
College London coronavirus model."

And this is a _major_ revision. It drops estimated deaths in the UK from
500,000 to "20,000 or far fewer." It also estimates that the UK will not run
out of ICU beds in the process.

The reason is that the transmissibility estimate has gone up, which implies
that many more people have already had the virus than we realized. This, in
turn, means that a much lower percentage are serious cases. It also means that
we are much nearer to the peak than we thought.

Edited to add: He also credits the lockdown in the UK, but if you look at the
previous model of how this plays out even with a complete lockdown, you see
that the vast majority of the change must come from the change in estimate of
transmissibility.

~~~
jimhefferon
> It also estimates that the UK will not run out of ICU beds in the process.

That'd be wonderful. But, doesn't that conflict with what we saw actually
happen in Italy?

~~~
jtbayly
Not necessarily. If transmissibility is high, you could be seeing close to the
peak.

The data out of NY that makes me most suspicious of this new model is actually
the 72% negative rate on tests. I would expect that to be a lot lower. But
that's just a gut feeling.

~~~
salmon30salmon
Half of those 72% may have had it three weeks ago and are a-ok now. Without
testing for antibodies, all we can say is they do not _currently actively have
an infection._

------
dr_faustus
The theory that the virus has been spreading for months just makes no sense at
all. By all accounts, COVID has a pretty quick progression and serious cases
need to be hospitalized after about one week of symptoms or about two weeks
after contraction. How come that the virus has infected millions and millions
of people in the last months but none of them got seriously sick. And now all
of a sudden, 1000s are dying. Unfortunatly, it seems that even researchers
from reputable institutions are now just pulling numbers from their asses to
grab some headlines.

~~~
yters
Maybe they were dying before, but were categorized differently?

------
triceratops
"He said that expected increases in National Health Service capacity and
ongoing restrictions to people’s movements make him “reasonably confident” the
health service can cope when the predicted peak of the epidemic arrives in two
or three weeks. UK deaths from the disease are now unlikely to exceed 20,000,
he said, and could be much lower."[1]

So basically "Scientist revises model based on new conditions". Isn't that
supposed to happen?

A successful prevention is going to feel like failure. It's going to prompt
questions like "was this worth all the panic, and tanking the economy?" Bodies
are easy to count, deaths prevented are invisible.

1\. [https://www.newscientist.com/article/2238578-uk-has-
enough-i...](https://www.newscientist.com/article/2238578-uk-has-enough-
intensive-care-units-for-coronavirus-expert-predicts/#ixzz6HpPqbiEF)

~~~
jtbayly
Not quite. You're claiming that this is all because of the lockdown, when it
is quite clear that the biggest reason for the change is the changed estimate
of R0.

In other words, _if this new R0 estimate is correct_ we were completely
mislead about how big a deal this virus is, and comparisons to it "just" being
like a bad flu year are more or less correct.

~~~
triceratops
But it seems like he's revising the R0 estimate upwards, rather than
downwards. From the same article:

"New data from the rest of Europe suggests that the outbreak is running faster
than expected, said Ferguson. As a result, epidemiologists have revised their
estimate of the reproduction number (R0) of the virus. This measure of how
many other people a carrier usually infects is now believed to be just over
three, he said, up from 2.5. “That adds more evidence to support the more
intensive social distancing measures,” he said."

[https://www.newscientist.com/article/2238578-uk-has-
enough-i...](https://www.newscientist.com/article/2238578-uk-has-enough-
intensive-care-units-for-coronavirus-expert-predicts/#ixzz6HpPqbiEF)

~~~
salmon30salmon
Yeah, revising the R0 upwards is exactly what you would expect to result in a
faster infection rate. This means that more people have already been infected
and were fine, and that we are at the peak before herd immunity starts to
drastically impact the R0 downwards.

------
nicois
I also believe the referenced article does not correctly convey what the
original New Scientist article does: the original epidemiologist does not buy
in completely to the new inferences, by my reading.

------
sunnyP
He tweeted some clarification.

[https://twitter.com/neil_ferguson/status/1243294815200124928](https://twitter.com/neil_ferguson/status/1243294815200124928)

------
guscost
Another model that fits the UK data, even when assuming that half of the
population has already been infected, which would mean that the disease is not
nearly as dangerous as commonly thought:
[https://nymag.com/intelligencer/2020/03/oxford-study-
coronav...](https://nymag.com/intelligencer/2020/03/oxford-study-coronavirus-
may-have-infected-half-of-u-k.html)

By adjusting those two parameters (R0 and IFR) in opposite directions, you can
come up with a whole gamut of scenarios that match the evidence pretty well.

~~~
jsnell
Sure, that model shows that there are multiple ways to fit the model
parameters to account for the first 14 days of fatalities. But we have a lot
more real-world data available that directly contradicts any scenario where
half the population is already infected.

I'm just disgusted that the authors are now saying it was just an abstract
demonstration of different scenarios, and pretending they didn't actually make
the claims about the real world that they did.

~~~
guscost
...is all of that real-world data from Lombardy? If not, does it rely on
circular logic? I’ve seen evidence in both categories, but not much else.

~~~
jsnell
Sure, here's some to start with.

1\. Any situation where the testing isn't limited to just the most critically
ill showing much lower infection percentages than this model would predict. A
lot of these are tests of every person in a risky situation, whether they had
symptoms or not:

E.g. the evacuation flights from Iran to China tested every passenger and
showed a 3% infection rate. T The village of Vo testing their entire
population twice soon after starting a Covid quarantine, with a 3% infection
rate.

Others were testing large amounts of people with no particular reason they had
Covid, but still with a skewed sample:

The Swedish sentinel testing of random people with any kind of flu symptoms
(1.5% of people with flu symptoms testing as positive for Covid, vs. 30%
testing positive for Influenza A/B). Iceland testing IIRC a volunteer 1.5% of
their population whether they had symptoms or not, and having something like a
1% infection rate.

The thing all of these have in common is that they happened at a time in their
relative epidemics where this model should have predicted the majority of the
population was currently infected.

In fact, it's basically impossible to explain any testing results, since even
when they're biased to cases where Covid is strongly suspected, the ratio of
positives is so low. If we test the 1000 of people most suspected of having
Covid right now, and get 10% positives, how can it possibly be the case that
half the non-suspicious population are carriers at the time of that test?

2\. If herd immunity kicks in 14 days after the first death as implied by this
model, why haven't any of the epidemics died down by now? Italy is on what,
day 30?

3\. How does a super infectious but low mortality model explain the geographic
clustering of deaths? Sure, the geographic clustering of known cases could be
explained by testing bias. But deaths don't have that bias.

4\. Observed high CFRs in limited populations where we know the infection rate
was high. E.g. Diamond Princess at what 1.4%, and still another 2% in critical
condition. How many top ranking Iranian leaders died in short order of Covid,
and how does that fit in with a mortality rate of 0.01%? Or the cases where
most of the patients of a health care facility or nursing home got infected?

~~~
guscost
1\. Unless I'm mistaken, this (extreme scenario in the) Oxford model does not
say that 50% of the population is infected all at the same time. Until there
are serological surveys that indicate who was infected in the past, the
current tests can't prove what you think. And any false negatives from the PCR
test would add to this problem.

2\. The progress of the disease takes time too, from infection to symptoms to
detection/hospitalization/secondary infection. And efforts to "flatten the
curve" will "slow the spread" too.

3\. I'm not sure about this one, but shouldn't the infectiousness also vary
quite a lot with different contributing factors (population density, air
quality, etc)? The number used in the model is always just an "average" in a
sense.

4\. The cruise ship evidence is pretty significant, but it still has problems.
Any passengers who had already recovered or did not show symptoms could have
been missed. Plus I can name several factors in that situation that might
increase mortality off the top of my head. It's not the best sample for
drawing conclusions about people who are on average less old, not traveling,
and so forth.

Admittedly, the extreme "50% infected" scenario has a risk factor (same as
IFR?) of 0.001%, which my gut feeling says is too optimistic. But as far as I
know none of the scenarios can be conclusively disproven (until they can do
proper serological surveys).

~~~
jsnell
1\. They have the virus go from like 5% infected to 70% in two weeks in that
scenario. Given what we know about the incubation period and they assume about
the infectious period, more than half the population has to be infected (and
probably even infectious) somewhere along that curve.

2\. Their model predicts that the peak of the epidemic in Italy should have
been before March 5th (first death on February 22nd + 14 days, at which point
easily more than half the population is infected). There should have been a
sharp drop in new cases about a week later, as the virus burnt itself down.
But here we are three weeks later, and it's still not entirely clear that the
peak has been found.

Italy did not institute significant nation-wide measures until March 9th, so
the "slowdown from measures" explanation makes no sense.

3\. Agreed. But their entire model is predicated on treating the entire
country as a single unit. That's probably a part of the reason why the results
are so absurd. I don't think it's fair to excuse the model for regional
differences, but require any criticism of the model to take them into account.

4\. The difference between the model's prediction and apparent reality is
likely to be about a factor of 200. Even assuming everybody on the ship was
actually infected, that only cuts it to a factor of 40 difference.

And it's really not just that single case. Consider that infamous Washington
state nursing home. 120 residents, 35 dead from Covid to date. Even if we
assume that every single one of the 120 was infected despite not testing
positive, that still an IFR of 30%. Sure, it's a high-risk segment. But it's
also a large enough segment a 30% IFT for them makes it quite impossible for
the population-wide IFR to be 0.01%.

(Re: your last point, they had two parameters. One for being at risk of
becoming a serious case, and another of dying if serious. The two need to be
multiplied to get their predicted IFR. They assumed that 0.1% of population
were at risk to become severe cases, and 15% of the severe cases died. So
about 0.01%).

~~~
guscost
So on the one hand, I think you're bringing up enough problems for me to agree
that the extreme scenario is not likely to hold up.

On the other, I don't understand how after making so many (often reasonable)
assumptions in your arguments, you can say that it's "quite impossible" for
the total infected to be so high, or the population-wide IFR to be three
orders of magnitude lower than a nursing home or any other special case that
you do not fully understand.

Here are some of those assumptions, which again do not all seem unreasonable
to me:

\- A mild case would likely be detectable by a PCR test for 8+ days

\- The PCR test does not have a high false-negative rate in mild cases (see
[https://www.researchsquare.com/article/rs-17319/v1](https://www.researchsquare.com/article/rs-17319/v1))

\- Italy has not already had a sharp drop in new infections/most new
infections are being identified as cases within two weeks

\- Italy did nothing to slow the rate of infection until the full lockdown was
in effect (but slower spread would mean higher mortality, no matter the
reason)

\- COVID-19 was the only/main thing that contributed to mortality in the
special cases

------
imeron
Bill Gates on the Imperial College model: 'Fortunately it appears the
parameters used in that model were too negative. ... Models are only as good
as the assumptions put into them'
[https://www.reddit.com/r/Coronavirus/comments/fksnbf/im_bill...](https://www.reddit.com/r/Coronavirus/comments/fksnbf/im_bill_gates_cochair_of_the_bill_melinda_gates/fkuojny/)

~~~
guscost
That's just fine and dandy then, _I_ didn't lose my job, and Bill Gates
doesn't need to earn money.

Un-fucking-believable.

------
sathomasga
This is flat out wrong. There is no revision at all. To quote [Neil Ferguson
himself]([https://twitter.com/neil_ferguson/status/1243294815200124928](https://twitter.com/neil_ferguson/status/1243294815200124928)):

I think it would be helpful if I cleared up some confusion that has emerged in
recent days. Some have interpreted my evidence to a UK parliamentary committee
as indicating we have substantially revised our assessments of the potential
mortality impact of COVID-19

This is not the case. Indeed, if anything, our latest estimates suggest that
the virus is slightly more transmissible than we previously thought. Our
lethality estimates remain unchanged.

My evidence to Parliament referred to the deaths we assess might occur in the
UK in the presence of the very intensive social distancing and other public
health interventions now in place.

Without those controls, our assessment remains that the UK would see the scale
of deaths reported in our study (namely, up to approximately 500 thousand).

------
tandr
Made me thinking - Is this the reason behind today's market's rally close to
the end of the day?

------
sunkenvicar
I hope he’s right.

------
wbronitsky
So we are normalizing rightwing propaganda sites on HN now? Seeing an article
from a Ben Shapiro fronted site on the HN front page is frightening. I need a
new place to get my information.

~~~
jtbayly
If you would prefer to ignore the fact that the hugely influential
epidemiologists responsible for the recommendations we are currently following
have changed their recommendations, go for it.

~~~
wbronitsky
We can all get our information directly from the source:
[https://www.newscientist.com/article/2238578-uk-has-
enough-i...](https://www.newscientist.com/article/2238578-uk-has-enough-
intensive-care-units-for-coronavirus-expert-predicts/)

