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Throughout the coronavirus crisis, one name has popped up several times, that of Prof Michael Levitt, biophysicist and professor of structural biology at Stanford University in California.

In 2013, Prof Levitt was a joint winner of a Nobel Prize in Chemistry, along with Martin Karplus and Arieh Warshel, for ‘the development of multiscale models for complex chemical systems’.

Levitt, 73, was born in Pretoria, South Africa, and is currently a citizen of the United Kingdom, Israel and the United States.

He holds degrees from King’s College London and the University of Cambridge.

He has had a stellar career, receiving several distinguished scientific awards and scientific advisory board appointments in addition to his university professorships over the years.

He has had much to say about coronavirus.

On Monday, March 23, 2020, he gave an interview to the Los Angeles Times, with a prediction: ‘Coronavirus outbreak may be over sooner than you think’.

The LAT said that he had been adopting a measured approach throughout the pandemic since January, refuting the wild and inaccurate overestimates from the likes of Prof Neil Ferguson of Imperial College London (emphases mine):

Michael Levitt, a Nobel laureate and Stanford biophysicist, began analyzing the number of COVID-19 cases worldwide in January and correctly calculated that China would get through the worst of its coronavirus outbreak long before many health experts had predicted.

Now he foresees a similar outcome in the United States and the rest of the world.

While many epidemiologists are warning of months, or even years, of massive social disruption and millions of deaths, Levitt says the data simply don’t support such a dire scenario — especially in areas where reasonable social distancing measures are in place.

“What we need is to control the panic,” he said. In the grand scheme, “we’re going to be fine.”

This is what he discovered about China’s experience of the pandemic:

On Jan. 31, the country had 46 new deaths due to the novel coronavirus, compared with 42 new deaths the day before.

Although the number of daily deaths had increased, the rate of that increase had begun to ease off. In his view, the fact that new cases were being identified at a slower rate was more telling than the number of new cases itself. It was an early sign that the trajectory of the outbreak had shifted.

Think of the outbreak as a car racing down an open highway, he said. Although the car is still gaining speed, it’s not accelerating as rapidly as before.

“This suggests that the rate of increase in the number of deaths will slow down even more over the next week,” Levitt wrote in a report he sent to friends Feb. 1 that was widely shared on Chinese social media. And soon, he predicted, the number of deaths would be decreasing every day.

Three weeks later, Levitt told the China Daily News that the virus’ rate of growth had peaked. He predicted that the total number of confirmed COVID-19 cases in China would end up around 80,000, with about 3,250 deaths.

This forecast turned out to be remarkably accurate: As of March 16, China had counted a total of 80,298 cases and 3,245 deaths — in a nation of nearly 1.4 billion people where roughly 10 million die every year. The number of newly diagnosed patients has dropped to around 25 a day, with no cases of community spread reported since Wednesday.

At that point, he moved on from China:

He analyzed data from 78 countries that reported more than 50 new cases of COVID-19 every day and sees “signs of recovery” in many of them. He’s not focusing on the total number of cases in a country, but on the number of new cases identified every day — and, especially, on the change in that number from one day to the next.

“Numbers are still noisy, but there are clear signs of slowed growth.”

On Tuesday, March 24, The Independent picked up on the article and had found another interview he had done for an Israeli financial newsletter on coronavirus modelling, in which he stated that he disagreed with the exponential growth formulae used in predictions, e.g. Ferguson’s, although he mentioned no names:

In an interview with Calcalist, an Israeli financial newsletter, Mr Levitt explained why he didn’t agree with models of exponential growth that many organisations were using as the basis of their predictions.

“In exponential growth models, you assume that new people can be infected every day, because you keep meeting new people. But, if you consider your own social circle, you basically meet the same people every day,” he said. “You can meet new people on public transportation, for example; but even on the bus, after sometime most passengers will either be infected or immune.”

He also thought that social distancing was a good idea:

Mr Levitt said that social distancing measures have been helpful in reducing the virus’ ability to spread rapidly.

At this point, he was studying Italy’s coronavirus numbers:

He suggested that the higher percentage of elderly people in Italy paired with the country’s vibrant social culture resulted in the explosion of cases in that country.

“Furthermore, Italian culture is very warm and Italians have a very rich social life. For these reasons, it is important to keep people apart and prevent sick people from coming into contact with healthy people,” he said.

He was rightly concerned with overloading health systems, including that of the United States:

“Currently, I am most worried about the US. It must isolate as many people as possible to buy time for preparations. Otherwise, it can end up in a situation where 20,000 infected people will descend on the nearest hospital at the same time and the healthcare system will collapse,” he said.

However, while he recommended a brief lockdown as a stop-gap measure to flatten the sombrero, as it were, he also believed that the nations’ populations were developing a natural, or herd, immunity to coronavirus:

Mr Levitt said that while isolating was an important step to fighting viral spread, he also believes a certain segment of the population may be naturally immune to the disease.

“We know China was under almost complete quarantine, people only left home to do crucial shopping and avoided contact with others. In Wuhan, which had the highest number of infection cases in the Hubei province, everyone had a chance of getting infected, but only 3 percent caught it,” he said. “Even on the Diamond Princess [the quarantined cruise ship] the infection rate did not top 20 percent.”

He said those numbers suggest that some people simply are immune or especially resistant to the virus.

It’s quite possible that some of us can build up immunity to COVID-19, because the common cold is a type of coronavirus. I’m not equating the two by any means, just highlighting that the principle could well be the same. We might not need an expensive drug — or a vaccine with who knows what in it.

On May 2, Prof Levitt gave an interview to Britain’s online magazine UnHerd, which is an excellent site. Freddie Sayers, the site’s executive editor, conducted the interview, which is just under 35 minutes long, available below and at the accompanying article:

The aforementioned article explains Levitt’s nuanced view of coronavirus. Lockdowns should be only short-term, or focussed on vulnerable groups, such as the elderly. Social distancing is important, but, even then, after a while people will ignore it. Therefore, some prior immunity or asymptomatic cases must factor in somewhere. Neil Ferguson’s Imperial College numbers are misguided, because this is not about exponential growth.

An excerpt from the article follows:

His observation is a simple one: that in outbreak after outbreak of this disease, a similar mathematical pattern is observable regardless of government interventions. After around a two week exponential growth of cases (and, subsequently, deaths) some kind of break kicks in, and growth starts slowing down. The curve quickly becomes “sub-exponential”.

This may seem like a technical distinction, but its implications are profound. The ‘unmitigated’ scenarios modelled by (among others) Imperial College, and which tilted governments across the world into drastic action, relied on a presumption of continued exponential growth — that with a consistent R number of significantly above 1 and a consistent death rate, very quickly the majority of the population would be infected and huge numbers of deaths would be recorded. But Professor Levitt’s point is that that hasn’t actually happened anywhere, even in countries that have been relatively lax in their responses.

He takes specific issue with the Neil Ferguson paper. “In a footnote to a table it said, assuming exponential growth of 15% for six days. Now I had looked at China and had never seen exponential growth that wasn’t decaying rapidly.”

The explanation for this flattening that we are used to is that social distancing and lockdowns have slowed the curve, but he is unconvinced. As he put it to me, in the subsequent examples to China of South Korea, Iran and Italy, “the beginning of the epidemics showed a slowing down and it was very hard for me to believe that those three countries could practise social distancing as well as China.” He believes that both some degree of prior immunity and large numbers of asymptomatic cases are important factors.

He also observes that the total number of deaths we are seeing, in places as diverse as New York City, parts of England, parts of France and Northern Italy, all seem to level out at a very similar fraction of the total population. “Are they all practising equally good social distancing? I don’t think so.” He disagrees with Sir David Spiegelhalter’s calculations that the totem is around one additional year of excess deaths, while (by adjusting to match the effects seen on the quarantined Diamond Princess cruise ship) he calculates that it is more like one month of excess death that is need before the virus peters out.

More generally, he complains that epidemiologists only seem to be called wrong if they underestimate deaths, and so there is an intrinsic bias towards caution. “They see their role as scaring people into doing something, and I understand that… but in my work, if I say a number is too small and I’m wrong, or too big and I’m wrong, both of those errors are the same.

He believes the much-discussed R0 is a faulty number, as it is meaningless without the time infectious alongside.

On May 23, the Telegraph had an article about Levitt: ‘Lockdown saved no lives and may have cost them, Nobel Prize winner believes’.

Levitt had been in touch with Ferguson to tell him his numbers were (once again, as the British know) woefully out of whack:

Michael Levitt, a Stanford University professor who correctly predicted the initial trajectory of the pandemic, sent messages to Professor Neil Ferguson in March telling the influential government advisor he had over-estimated the potential death toll by “10 or 12 times”.

The Imperial College professor’s modelling, a major factor in the Government’s apparent abandoning of a so-called herd-immunity policy, was part of an unnecessary “panic virus” which spread among global political leaders, Prof Levitt now tells the Telegraph.

Levitt told the Telegraph that he was no fan of a prolonged lockdown:

“I think lockdown saved no lives,” said the scientist, who added that the Government should have encouraged Britons to wear masks and adhere to other forms of social distancing.

“I think it may have cost lives. It will have saved a few road accident lives – things like that – but social damage – domestic abuse, divorces, alcoholism – has been extreme. And then you have those who were not treated for other conditions.”

Levitt nails it with his next observation. Politicians were terrified at the prospect of a high death toll if they did not implement lockdown:

“I think that the real virus was the panic virus,” Prof Levitt told the Telegraph. “For reasons that were not clear to me, I think the leaders panicked and the people panicked and I think there was a huge lack of discussion.”

Levitt believes that COVID-19 has a natural life cycle. Lockdown did little. The virus burned out by itself:

“In Europe, I don’t think that anything actually stopped the virus other than some kind of burnout,” he added. “There’s a huge number of people who are asymptomatic so I would seriously imagine that by the time lockdown was finally introduced in the UK the virus was already widely spread. They could have just stayed open like Sweden by that stage and nothing would have happened.”

Also:

“There is no doubt that you can stop an epidemic with lockdown but it’s a very blunt and very medieval weapon and the epidemic could have been stopped just as effectively with other sensible measures (such as masks and other forms of social distancing),” he added.

Levitt thinks that the UK will have total deaths around 50,000, which looks quite possible. He’s also drawn the ire of epidemiologists, yet his forecasts have been far more accurate than theirs:

“It turns out numbers are played out very consistently when you look at all the places that have been badly hit, particularly in Europe. The token number of deaths before things stop is about one month of natural deaths, which is something like one in a thousand.”

Based on his estimates, Britain was due to suffer around 50,000 deaths in total. “A lot of things went wrong but I think the main thing is that we just needed to think and discuss things a little bit,” he added. I was told on numerous occasions ‘you are not an epidemiologist, shut up’. I don’t really care. I was just looking at the numbers. I was looking at the cruise ship, looking at Wuhan. The same number held for these places.”

A few days before the Telegraph interview took place, an article comparing Levitt’s spot-on numbers with Prof Neil Ferguson’s off-piste ones appeared in The Critic: ‘We’re all in the big numbers now’.

As its author, Alistair Haimes, says, we are now in a place to begin studying UK coronavirus deaths and statistical curves.

This is how wrong, to be polite, Ferguson’s Imperial College numbers were:

Imperial College haven’t had a good war, and after their performance in other recent epidemics perhaps they will now pass their mantle onto another team.  Preferably one that can code to levels fit for publication, never mind policy: it is increasingly awkward to hear the Prime Minister quoting their forecast that, were it not for lockdown, the UK could have been looking at half a million deaths when, at the tail-end of the epidemic, there are only 320,000 deaths worldwide.

By contrast, we have Dr Levitt’s accurate predictions, but no one wanted to know because Levitt is not an epidemiologist!

In mid-March, Stanford’s Nobel laureate Michael Levitt (biophysicist and professor of structural biology) discussed the “natural experiment” of the Diamond Princess cruise ship, a virtually perfect sealed petri-dish disproportionately filled with the most susceptible age and health groups. Even here, despite the virus spreading uncontrolled onboard for at least two weeks, infection only reached 20% of passengers and crew (an “upper bound” to infection levels?); Levitt concluded that we must have high levels of innate immunity that can clear the virus. And using very simple mathematics (not “15,000 lines of uncommented code” like Neil Ferguson) he demonstrated that the virus’s spread had never been exponential but rather has been running out of steam from day one. Who listened?

The end result is a death toll that is no worse than a bad influenza year:

If we simply move covid-19 deaths from spring to winter, the death-toll and the extent of the epidemic is put in the context of recent bad (but not dramatic) influenza years.

We have had bad flu years in the UK, and within the past two decades, but we didn’t get hysterical about them:

Remember the killer flu of 2000, and the lockdown after the Millenium super-spreader events? Me neither. Covid-19 might not be “just flu”, but that’s because there’s no “just” about flu.

According to the article, Sweden’s no lockdown strategy was that of Britain’s SAGE (Scientific Advisory Group for Emergencies) member and our Chief Scientific Adviser, Sir Patrick Vallance:

In Sweden, Professors Giesecke and Tegnell have managed the epidemic within Sweden’s healthcare capacity without suspending civil liberties or shutting down schools or society (Sir Patrick Vallance’s “Plan A”), with no greater death-toll than our own. The Free Swedes pointed out all along that lockdown would be much easier to get into than out of: no kidding, we’re in an eel-trap.

We have no idea if the UK government looked at models that contradicted Ferguson’s. Oxford University has more realistic models, but we paid attention to Ferguson’s numbers from Imperial College. They have never been right for other pandemics, so why would he have been right about this one?

One thing the article omits is the media narrative that drove us to lockdown. Britain was going along with the Swedish model of social distancing, but the 24/7 news channels — BBC and Sky — ramped up Project Fear by asking why we didn’t have a lockdown, too.

No doubt advisers put pressure on Prime Minister Boris Johnson, too, because everyone in that stratum of society, Boris included, will watch some BBC news every day. He probably already knew the narrative.

Hence, lockdown on the evening of Monday, March 23.

SAGE minutes actually state that the British public was so scared that they would comply:

SAGE minutes make it clear that the public was explicitly petrified in order to ensure compliance with lockdown.

Lockdown was a YUGE mistake socially and economically.

We are due to go through the worst economic disaster since the early 18th century. Years differ: 1704, 1706, 1708. Take your pick.

Questions must also be asked of Neil Ferguson. He ruined the farming industry with his past predictions. Now he’s ruined not only the British economy, but, perhaps, others where leaders looked at his unrealistic extrapolations. (The United States comes to mind.)

One could be forgiven for thinking that Ferguson has an agenda of some sort. It certainly looks that way.

Boris, his government ministers and his advisers now have to get us out of this mess, sooner rather than later.

Boris’s ‘baby steps’ won’t cut it.

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