Posted on 03/25/2020 6:11:48 AM PDT by Mount Athos
Government policy and guidance crafted in an effort to “flatten the curve” of coronavirus-related deaths has largely been based upon an Imperial College London model headed by Professor Neil Ferguson.
The terrifying model shows that as many as 2.2 million Americans could perish from the virus if no action is taken, peaking in June.
However, that model is likely highly flawed, Oxford epidemiologist Sunetra Gupta argues.
Professor Gupta lead a team of researchers at Oxford University in a modeling study which suggests that the virus has been invisibly spreading for at least a month earlier than suspected, concluding that as many as half of the people in the United Kingdom have already been infected by COVID-19.
If this is the case, fewer than one in a thousand who’ve been infected with COVID-19 become sick enough to need hospitalization, leaving the vast majority with mild cases or free of symptoms.
With so many in the U.K. (and potentially the United States) presumably infected, so-called “herd immunity” could kick into effect, dramatically limiting the number of deaths modeled by Ferguson and company.
“The Oxford study is based on a what is known as a ‘susceptibility-infected-recovered model’ of Covid-19, built up from case and death reports from the UK and Italy,” the Financial Times explains. “The researchers made what they regard as the most plausible assumptions about the behaviour of the virus.”
The report continues: “The modelling brings back into focus ‘herd immunity’, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected.”
While the notion of “herd immunity” has been essentially dropped in U.K. policy making, “the Oxford results would mean the country had already acquired substantial herd immunity through the unrecognised spread of Covid-19 over more than two months.”
The Financial Times emphasized: “If the findings are confirmed by testing, then the current restrictions could be removed much sooner than ministers have indicated.”
“I am surprised that there has been such unqualified acceptance of the Imperial model,” Gupta criticized.
Of course, the epidemiologist encouraged caution and suggested changes to policy and guidance only be made after more evidence can be presented.
The Oxford group is working with researchers at the Universities of Cambridge and Kent to begin antibody testing on the general U.K. population later this week by using specialised “neutralisation assays which provide reliable readout of protective immunity,” Gupta explained.
“We need immediately to begin large-scale serological surveys — antibody testing — to assess what stage of the epidemic we are in now,” the professor said.
Other respected medical professionals have offered a more optimistic look on the coming weeks and months with COVID-19, too.
For example, Stanford biophysicist and Nobel laureate Michael Levitt said this week, “The real situation is not as nearly as terrible as they make it out to be.”
Last week, Levitt emphasized: “[Y]ou need to think of corona like a severe flu. It is four to eight times as strong as a common flu, and yet, most people will remain healthy and humanity will survive.”
If half of Brits have/had it, then there would be antibodies still in everyone’s system. Isolate what that antibody is, test people for its presence in a detailed controlled study. Prove this right or wrong.
That whining Cuomo may be stuck with thousands of ventilators and warehouses full of swabs and face shields.
As I have said a number of times - a total testing of the general population in say a zip code near one of the hot spots is needed to get an idea of how many in the “Herd” are walking around with it.
At US taxpayer expense.
Once upon a time, I used to model real-time systems to engineer software. I know a thing or two about modeling and I can tell you without a doubt some very intuitive things. 1.) All models lack detail from what they are modeling. They are an abstraction. If they had the detail of the thing they are modeling, it would be the real thing. 2.) You need more than one model to come close to modeling with any accuracy. The more than one model has to be a different type of model. Not the same basic model with different variables or a tweek here or there. 3.) Complex systems always have unknowns, and only multiple iterations of prototyping/developing of the solution do you discover the unknowns that could be used to correct the model. 4.) As for modeling the ChiCom Flu, weather, the Climate and other highly complex things, the complexity is so great that models never come close in long range predicting, e.g., weather more than a week. See, number 3, as you are closer to the real thing in time, you can adjust the model to be correct, but you won't be close to the real thing six months from now, until six months from now. By that time, you no longer need the model, because you have the real thing.
Is modeling useful? Yes, it is a tool and as a tool it needs to be used properly and its results need to be interrupted correctly.
Such nonsense!
I had to model a system that was required to track geosynchronous satellites which actually describe a small pattern in the sky that nearly repeats every sidereal day. Rain fades are a problem. "Nearly" is the key because you don't actually know whether the diminution of signal is due to atmospheric problems or satellite drift.
The software to control the tracking had to be subjected to more difficult conditions more often than might occur in the real world.
Sometimes models work. Sometimes they don't. The problems arise when someone is trying to model a system with too many variables and/or too many unknowns. The existence or planetariums proves that a model and the real thing can be pretty damn close.
ML/NJ
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... modeling study which suggests that the virus has been invisibly spreading for at least a month earlier than suspected,...
When did it start? Facebook is "fact checking" posts that suggest it was in the U.S. in late fall 2019. I think it may very well have been here. Just my gut, no data...
I keep wondering if they’re looking in the wrong places.
Why do some people get the virus then recover....and others exposed to it don’t succumb?
THEORY It’s a paradox of public health that being too clean can lead to disease.
The onslaught of polio lead to determining it was a Clean Disease.
BACKSTORY For centuries, infants were routinely exposed to the polio-virus due to living in unsanitary living conditions.
For this reason, researches found that polio rarely causes paralysis in infants, partly because of the maternal antibodies still present in their systems.
Shingles thrives in sterile environments. ....many people contract the disease while in the hospital.
I think we are saying the same thing. Complex systems are complex because they have too many variables and/or many unknowns. The detail in which I speak are the variables and knowns. If you have complete detail you could be the real thing. Think of scientific experiments where you try to simulate the real world in a closed environment. That is sort of a model isn't it? Make it closer to the real world by adding more details. It's still a model, but closer to the real thing. Keep doing that to infinity, and you have the real thing, hypothetically. That of course is not feasible, particularly in complex systems so we settle, as you put it, "nearly" enough. Which is also correct.
Bottom line at the moment, people don't know enough about the ChiCom flu, thus you have unknowns. It is also a complex system that is being dealt with - humans and their environment.
You are right to say, models work sometimes and other times they don't. I agree.
Excellent. Thanks.
This attitude reminds me of the forest fires in this country and Australia,
It starts with the we only have it 20% contained.
After the fires burn for weeks or months and destroy the forests , homes and towns and there is not much left to burn we say it is 100% contained. Another victory for man over nature
.(I am in no way being critical of the heroic firefighers who fight these fires)
After this covid-19 runs its course as flus do. I guess we will say we have it under control. Another victory.
WE know enough about this virus so Let's get back to work, and figure out how many beds and ventilators and medical staff and supplies we will need for the next epidemic.
And if we feel like it; do something about anticipating another type of epidemic, or get back to business as usual. (Like wondering how Tom Brady will fare as the new quarterback of the Tampa Bay Buccaneers.) -Tom
very interesting. I’ve always thought the overuse of bacterial soap/purel is very dangerous for our health
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