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December 4, 2020 - 11:34am
It’s starting to feel like the end of the beginning of the pandemic, with news that a vaccine for Covid-19 has been approved in the UK and that two are set to be authorised imminently in the US. And yet, until very recently, many commentators, politicians and experts were incredulous that such a turn of events would be possible so soon — in their minds, the idea that a vaccine would be approved in less than 18 months — let alone in under a year since its design — was completely fanciful.
At the same time, I had been telling friends in May that vaccines would most likely be authorised for emergency use by the end of the year, and in July, a McKinsey report came to the same conclusion. In August, I explained in detail why I believed a rapid timeline was very likely, with the most likely outcome being that a vaccine would be approved and distributed in enough doses to vaccinate 25 million people in the US around February 2021. My friend and fellow forecaster Jonathon Kitson predicted in October that a vaccine would be approved in the UK in December and rolled out in January.
These weren’t random guesses. There were very good reasons to be optimistic even back in the spring. There was the observation that most patients were able to clear the virus from their body, suggesting that this immune response could be primed using a vaccine. There was the slow mutation rate of the virus, which made it more likely that a working vaccine would protect us against multiple strains. There was the fact that funding was at an unprecedented level, that the virus’ genome had been sequenced and shared publicly incredibly swiftly, and that trials were running multiple phases in parallel. There were already vaccines for other coronaviruses developed for use in animals, and there were more vaccines in development for this single disease than ever before.
But there were also uncertainties: would the disease remain pervasive, allowing scientists to test whether a vaccine would protect the participants in clinical trials from the disease? And how safe and effective would the frontrunner vaccines turn out to be, given some of them used new technology?
As the summer went on, these uncertainties narrowed down: the disease did remain pervasive in countries where trials were ongoing, and the results from phase one and two trials were fairly promising. So it’s not surprising that many forecasters updated their forecasts according to new developments.
You might ask, however, why those predictions changed quite so much. In May this year, superforecasters rated the possibility that a vaccine would be approved and distributed at large-scale by April 2021 as having only a 5% chance, on average. By September, that forecast rose dramatically to 70%, and then leapt to 98% by December.
Shouldn’t superforecasters have predicted that those crucial but uncertain developments — the prevalence of the disease and the results from trials — would probably occur? And if they didn’t, does that make their forecasts useless?
Research indeed suggests that forecasters who make detailed initial forecasts and then update incrementally to new information are more reliable than those who make large swings in their predictions. So we shouldn’t simply take the average of the predictions that superforecasters gave, but we should scrutinise how each forecast was made: How did they compile the evidence and justify their reasoning? How did they quantify their uncertainty?
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SubscribeIt was the “superforecasters” with their mathematical models that created the pandemic of fear in the first place. They were superwrong with superenormous consequences.
I think you’ve misunderstood the concept of a superforecaster. I wonder what your forecasts were back in March?
Indeed,most forecasts for infections and death overstated the cases by a factor of ten or more,hence the panic.
It’s like predicting the end of the world. One day someone will be right.
It was relatively easy for the numerically literate to see – back in March – that the original Imperial College paper was extraordinarily wrong. Back in March, there was enough data to establish what the risk profile was for this disease and subsequent events have not made a material difference to the risk profile. Most people (including most politicians) are not numerically literate – and this renders them vulnerable to fearmongering from epidemiological modellers who are, it should be observed, generally third rate mathematicians (if that).
The same issues apply to climate science modeling. You have to suspect that those engaged in the field know they are taking advantage of the fact that politicians and the public are not numerically literate. You also have to suspect that this is why they have taken to the tactic of denouncing anyone who questions their orthodoxy as a denier
It has nothing to do with politicians’ numerical literacy. They look through a different lens and calculate very carefully which side to take to make themselves look the most important and relevant so they can get re-elected. They then choose the science and the data that best supports the side they have taken. The political judgement on both COVID and climate change is to be pro the precautionary principle – generally that is the safe political position as you can’t be wrong. Disaster happens – we were right, maybe not cautious enough early enough, but this was something bigger than we could stop and those who did not listen to us are partly to blame and the disaster would have been even worse had we done nothing. Or disaster does not happen and we were right and our precautions have saved the day. It is not a conspiracy theory as such, just the way politics works.
So we have a government screwing the economy and our children’s futures to protect against COVID and an opposition that goes along whilst criticising the government for not screwing the economy and our children’s futures enough.
On climate change it is basically the same story except it has been running so long we have nutcases like Extinction Rebellion and Greta as well.
Is the planet really warming? Well it goes through complex natural warming and cooling cycles we do not really understand. Take the shortest cycle which is not global but dramatically impacts the climate of a significant area of the planet – El Nino. It happens every 3-5 years and we know what happens and the way it happens, but we don’t really know why it happens in the way it does and we cannot predict well in advance whether it will be a strong cycle with lots of effect or a weaker cycle. On the balance of probabilities, given all the contradictory real data, I would say we probably are still in the warming cycle we have been in since the end of the last ice age.
Are humans adding to that warming effect? Possibly. We use a lot of energy and basic physics tells us that energy of all forms ends up as heat. Heat does radiate away into space and there are natural processes which absorb heat. We know at a local level cities are significantly warmer than rural areas and we have a lot more cities and larger cities as populations have grown, so it would seem logical that these local effects could be adding to a natural global effect.
Is CO2 responsible for any of what is happening? There is a loose correlation between historic warming and CO2 levels, but it is not clear whether this is cause and effect and if there is a cause and effect, as opposed to a correlation, it is highly likely that temperature is the cause and CO2 the effect. So whilst we should not rule out the possibility that CO2 is doing something, it seems highly improbable. That is why all the models that are based on CO2 being the cause are wrong and have to be adjusted all the time before being wrong again. But at least we have Greta who can see this invisible gas and therefore the harm it is doing.
I wonder if it is that consciously motivated. In the current situation and for quite some time, the scientific system of enquiry is beholden to corporations and Government. It is human nature, unconsciously if not consciously, to provide what people want.
The scientific system of enquiry was meant to avoid that, through high levels of objectivity and mechanical function.
However, climate modelling, like many systems, is only as good as what goes into it, i.e. garbage in/garbage out. If great faith is put into a system, whether religious or scientific, people are going to make use of it with higher levels of subjectivity and remain unaware of any conscious or unconscious prejudice, i.e. bias.
In essence, the only result or outcome which can be had is one which is derived from the question or questions asked. If a question is not asked, then that information will never be available. We have long seen this with vaccines in general, where the critical questions are simply never asked.
It is not so much the individual scientists, the little people who are denouncing the questioners, but the vested agendas which employ them.
It is all about where you start from and the money.
If you chose to make a career studying man made climate change you are have already decided it exist and that it is a problem.
Once you get started there is a vested interest in keeping the money flowing so you have to publish in support of the basic contention. There is no future in publishing conclusions to the effect that we can find real evidence man made CO2 emissions have any climatic effects
It is widely accepted that social ‘science’ research is largely fiddled to confirm the researcher’s initial, typically politically conceived, premise.
However, it seems that the same problem is far more common than you might imaging in relation to scientific research. With funding and careers dependent upon results, and with little chance of getting called out, the temptation to manage the results is strong.
Give me a million quid and I will give you a reasoned report in 12 months establishing beyond doubt that grey squirrels are a far greater threat to the planet than climate change, together with request for a further million quid to fund further research into this urgent issue.
Bang on M8
Assuming you refer to Report 9: Impact of non-pharmaceutical interventions (NPIs) to
reduce COVID-19 mortality and healthcare demand. Their model’s risk profiles for IFR and hospitalisaiton appear in Table 1 of the report. They are, correctly, strongly age linked, though their 80+ age group’s IFR appears low compared to other papers I found.
What are you claming they got wrong?
All models are wrong – some models are useful.
The utility of any modelling must be surrounded by caveats and the greaterthe policy implication, the greater the care must be in presenting modelling results with appropriate caveats.
Specifically, the IC model predicted that an unmitigated response would see over 12,000 deaths per day in the UK for a week or more in May and more than 9,000 deaths per day for about a month. The predicted concentration of death within a six week time period was deeply flawed. Had there been
sensible validation of the model, this prediction would not have been included in the report and the model itself would have been required to undergo some sensible calibration.
Specifically, the IC model predicted that ICU beds would be overwhelmed with people in their 80s and older. This was also a flawed finding – it should not have passed a serious validation review. The clinical effectiveness of mechanical ventilation for the elderly at that time was very low – what they could have modelled was the ethically challenging protocol of not engaging in heroic medicine.
Specifically, the IC model predicted that school and university closure would be more effective in achieving suppression than household quarantine. I
think it is now reckoned that the transmission via children is minimal and that university students virtually never arrive in hospital (unless there is some other underlying health condition)
Why do you go out of your way to distort the report? The unmitigated figures are described in the report as ‘unlikely’ – maybe they should have used stronger language. But it is clear they were essentially a baseline for the model. They were not a forecast, or even central to the analysis, which was to compare suppression and mitigation strategies.
How you came to your interpretation on schools and universities is a mystery, given the summary of the report said “suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures…” [note the word ‘supplemented’].
I’m not saying the Imperial report was a brilliant piece of analysis, but I do get fed up of people misrepresenting the views of others.
Indeed it was a really poor piece of analysis on which a monumental policy catastrophe was based.
I have not misrepresented them at all. The baseline in any analysis is crucial and the IC baseline was a fiasco of analysis. To brush this aside is to misread the paper – it was the main feature of the scaremongering.
The quote on schools comes directly from the report. P10
Apologies on the schools/universities point – I was wrong. However, I still disagree on the bigger point. The model had to assume something about would happen if everyone’s behaviour carried on completely as normal. That’s the very high figures you mention. But the Imperial report did not expect that to happen – who would, given people were already changing their behaviour radially even before the first national lockdown? It was not a forecast of what Imperial thought would happen. The 500,000 deaths was a feature of the scaremongering because it was a (completely unreal) worst case scenario, so the deaths were much higher than what anyone actually expected with either the suppression or mitigation approaches.
The forecasters in an artificial narrative have almost 100% chance of being right.
I don’t understand what the artificial narrative is, but I assume you mean some Deep State plot, driven by Bill Gates and abetted by corrupt politicians and the ‘MSM’. Even if there was a shred of evidence for this confection, it’s not obvious that the various forecasters are in on it, so how could they be guaranteed to be right? In short, I think you are posting nonsense. If I’m wrong, maybe you could make some forecasts yourself that can be verified against what actually happens, as your access to the artificial narrative should give you a very good chance of being right?
I did not make up Event 201 (complete with souvenir corona virus cushions for attendees to the NY symposium in October 2019) or the plans of the World Economic Forum or the British government pouring billions into GAVI since 2011. I just looked on in horror. The products are rushed to the market – it is the people rushing them that are in control of the timing. It is not like predicting the course of an epidemic. All they want is the money and to be indemnified, and it doesn’t matter how many short cuts. The whole article is predicated on gullibility. We need better articles than this.
One of the ridiculous things is that these people actually tell you what they are doing but if you point it out you are relegated to the ranks of the “conspiracy theorists”. Case in point the BBC in one of it conspiracy debunking articles maintain that “The Great Reset” is just a post-Covid economic rescue exercise. Well, you can see that this is not remotely true by just going to the WEF website and looking at their techno-feudalist agenda. People who care about the future of democracy (I don’t mean Saloni but the publishers of Unherd) should not play dim about this: the plans are there in black and white.
I think what Michael may mean is that there are multiple narratives in our social constructions of the world. And, if a forecaster plugs in enough assumptions from any one narrative, their outcomes will support that given narrative. And that can include a “deep state” narrative.
Garbage in, garbage out. One of the first admonitions researchers learn in research methods class.
The hard part, as the author points out, is finding the narrative (social construction) that best aligns with science.
Any model will be 100% accurate if all of the inputs are correct. However, in real life there are incalculable possibilities and the odds of getting them all correctly determined and weighed is next to nil. So then is the likelihood of getting an accurate model.
I look at it from a thermodynamic point of view. One can say there is an almost certain probability that a single molecule of water put into the head of the Mississippi river will at some point in time end up 1000 mile south, in the gulf of Mexico.
But there is no way possible to determine just how long it will take or the exact route that it takes to get there. There are simply too many variables.
That said, the modeler has no choice but to choose a static set of possibilities and model that. In the case of the Covid models, the way I understand it is that scenarios chosen to model were the cases having the worst possible scenarios withing the normative range. I don’t fault them for that. If I were making decisions on an unknown virulent virus, that is what I would want to know too.
Where I put blame is on the politicians who, after they should have seen that clearly the situation was nowhere near the worst case predictions continued and still continue to behave as if those models were accurate.
Surely the problem is that it is impossible to enter all factors, because there are so many, so the inputs are never fully correct. One change, however small, can have dramatic effects on outcomes.
When the modeller chooses what to enter, he or she is making a choice, probably subjective, which will influence if not dictate outcome.
In short, the scientific system of enquiry in this day and age is deeply flawed and modelling systems even more so. As a whizz-bang, techo-toy, it is popular, but as a means of understanding it offers very little.
It reminds me of the introduction of the microwave oven which, in the beginning, was supposed to revolutionise cooking. It didn’t because it has major limitations. It is useful superficially in a kitchen but has little use for real cuisine or cooking, and can only cope with trivialities in terms of good food production.
Much the same for modelling systems. Recognising the limitations of each is critical to making the best use and preventing major errors.
Nothing is ever 100% accurate surely, particularly not number-crunching?
Well, mathematically a 100% accurate model is not impossible and there are perfect models of very simple processes. The problem is that, as you explained (and I had as well) as you add inputs the odds of a perfect model fall away in an exponential free-fall.
How ever, number crunching is about the ONLY place where there is 100% accuracy, though you can contain just about all of the examples of it known to man in a single Textbook.
Everything else just trundles off into infinity on a river of digits streaming behind the decimal point.
I had to go and check who this lady is – her college gives her ‘PhD’ after her name but then says ‘research student’.Hmmm! Anyway, I’ve taught research methods for longer than she has lived at world class business schools and one of the first things we ask students to do is look at the assumptions in what they read. Why? Because, if you start in the wrong place and set off in the wrong direction, you are not likely to get anywhere you want to be. This is OK for travel in an exciting world but not in science. This lady’s assumption is that having a vaccine is a good thing but why, when evidence shows that we are now 80% immune? How much money is being spent on something we don’t need/may be dangerous and, more importantly, why??? I could also have forecasted that vaccines would be rushed through because I know how manipulative the government and its corporate backers are and this comes from 8 decades experience.
John,
“evidence shows that we are now 80% immune”
Firstly you need to understand the difference between evidence and proof. Some evidence may suggest that but other evidence contradicts that. There is no proof. You have also made the assumption that the evidence, which you have not cited, is valid. It may be based on good data but that data may have been misinterpreted or indeed it may be based on bad data in which case it is almost certainly wrong.
Secondly you assume that the purpose of the vaccine is to defeat the virus. However I would assert that the real problem is the fear of the virus that has been generated by politicians and MSM working from flawed evidence, which they have selectively interpreted to give answers that support their chosen course of action. This fear has led to a disproportionate reaction to a real but in my opinion vastly over exaggerated threat. Hence the current “cure” – lockdowns and ineffective restrictions, is far worse than the real disease.
So whilst the real problem is not the disease itself but is therefore largely emotional based on flawed understanding, surely an antidote that is also emotional which can also be based on a flawed understanding – ie a vaccine, is the answer and as long as we believe that, we have a way out of the real problem that we have created though flawed science feeding flawed politics into a flawed communication with the population via a flawed MSM.
There is evidence from the reinfection cases that have been properly investigated and reported:
https://www.thelancet.com/j…
That there are 2 or more distinct COVID-19 illnesses from genetically distinct SARS-CoV-2 agents. The standard tests cannot tell them apart and the immunity developed by recovering from one did not protect against the other. We have no idea whether the vaccines developed will protect against both. Nor which variant the vaccines developed will protect against – there would seem to be a difference in virulence between the variants. However if we find that the vaccines developed don’t protect against all variants, then at least we have the ability to rapidly produce others that do protect against the other variants – especially if we are not targeting the more virulent version.
Is this 2 or more variant hypothesis evidence for the “it was created in a lab” theory? Would it explain why there is evidence a milder variant may have been circulating a lot longer than we thought and it is only when the stronger variant has “got out” that it was really noticed? All valid questions which should be asked, but as yet there is insufficient evidence to provide probable answers.
LOL. Reinfection? There are 69 million coronavirus cases in the world and a handful of “possible reinfections” which could be put down to human error and testing practices. Sorry but this is clearly not a thing to worry about. I do agree with the vaccine point. The vaccine is definitely a solution to the real problem. Which is panic and hysteria. Get a vaccine out. Doesn’t matter if it works. Let Gates and his merry band of psychopaths establish a new well funded biotech monopoly and send the drooling masses back out into the streets magically immune to the virus. They can just say everybody needs a shot every 6 months for the latest “deadly” viruses. Unless of course they are serious about this “great reset” nonsense. We might be forced to sit in front of computer screens, order meals in from Amazon, and wait for the vaccine drone to come jab us when we need our updates.
Dennis,
You have missed the point. It is not reinfection by the same virus but a small number of unlucky people seem to have been infected by 2 similar, but different viruses. Yes the numbers are small, which is why the evidence is not conclusive. There are a lot of people who crap on about the tiny number of “reinfections” (are they really reinfections which given what we know about immunity to other corona viruses seems highly unlikely or dual infections as ALL the cases properly investigated have been?) as evidence immunity, natural or artificially acquired through vaccination, does not last etc. But fail to comprehend the true import of there potentially being 2 or more strains which both give positive tests and are therefore indistinguishable without full genetic analysis, but immunity to one does not give immunity to the other. What does this mean for herd immunity? What does this mean for vaccine effectiveness? What does this mean for the origins of the virus in the first place?
Finally the number of people who have tested positive around the world is probably only 10% of the people who have been infected by one or other of the strains, therefore is stands to reason that potentially the number of known “reinfections” may only be 1% of the number of “reinfections” , Even so that number remains very small compared to the total number of infections.
If this is correct then we desperately need superforecasters working on climate change. As far as I am aware all of the scaremongering climate change predictions in the last 40 years have 0% accuracy.
The problem is politicised science. People misunderstand the true nature of science. It starts off as guesswork and then has a process for maturing that into something that is reasonably reliable and useful. The problem comes when bias enters the process. The worst for creating the unhelpful bias that leads to science providing unreliable and misleading outputs are politicians, because they determine funding and want to use the outputs to support their agendas.
If you look at the full range of scientific opinion and theory on climate change there is a lot that does make sense, but it mostly comes from older scientists who have nothing left to prove as individuals and are not reliant on securing grants to further their research. They still don’t have full and perfect answers because science does not produce such things, but they are more reliable and therefore useful.
People need to understand that good science done by good scientist in as unbiased a manner as possible is the best way to get imperfect but usable answers to difficult questions. The only thing I am certain of is that there is far too much certainty in the world, because theory and hypothesis get presented as fact.
The first senior UK politician to become interested in the emerging global warming theory was Margret Thatcher. She was taking on the miners at a time when global temperatures had apparently been falling during the post war decades and the possibility of returning to another Ice Age was mooted – very unhelpful if you are trying to shut down uneconomic coal mines. However a theory that said that was not the case and in fact we would start warming again was helpful.
It is the same thing. Climate change wasn’t selling. They tried as hard as they could but they weren’t getting anywhere. The Virus hit the jackpot so to speak. Fauci even tied two together and co-authored a paper stating this is just the first one. This is going to be our existence from now on. We will have more killer viruses because of climate change! https://www.cell.com/cell/f…
‘There are actually four kinds of lies: …lies, damned lies, statistics….& political & business rhetoric based on “predictions”. Let’s all get real they have not given us the whole numbers of deaths due to only Covid progressively each day or week…nor the whole numbers of deaths with co-morbidiltes each day ….& all in age bands …& most importantly the exact numbers of Covid/Flu type deaths this year vis a vie “these type of deaths” in past years. Modelling is like Budgeting…it can predict ANYTHING …How come Media & Politicians were peddling “the only “solution” was “for all to be vaccinated” from the very onset…how could they have “known” this. It’s an obvious RORT as we say in Australia…& if they are able to get huge numbers to “virtually compulsorily” vaccinate each yr by using “incremental tricks” (like kid’s need to vaccinated to go to school & folks to work or Overseas etc)….it will end up huge anual PROFITS for big Pharma (in fact Trillions) & HUGE controls with “Covid passports” etc) for Big Brother… Folks need to wake up its all based on selling fear based on “Predictions”…My Dad used to say “IF” is the smallest word in the Dictionary with the biggest meaning…….NO TYRANT IN HISTORY HAS EVER DREAMED OF HAVING THESE POWERS.
I do not consider what you said as true; but as possible. Except for the last part, which I find very, very true! “NO TYRANT…”
Fear is perhaps the most convincing argument!
And you have all the media selling your “propaganda”…
And all the “rulers” and “ruler boards and committees” imposing your rules… – or at least suggesting and supporting it –
Now that’s a TOY for a Big Brother!
Happy Birthday Big Brother!
You said: And yet, until very recently, many commentators, politicians and experts were incredulous that such a turn of events would be possible so soon ” in their minds, the idea that a vaccine would be approved in less than 18 months ” let alone in under a year since its design ” was completely fanciful.
And that is because to approve such an experimental vaccine in such a short time is fanciful unless one is prepared to be criminally negligent. Approving a vaccine is not the point – approving a safe, well-tested, effective vaccine, i.e. prevents infection, is a different matter and the vaccine being approved is none of that.
As to forecasts, Covid has shown itself to be no threat to more than 99% of people, as some medical and scientific experts predicted, and were ignored, and instead the fear-monger and hysterics won the day.
I mean, seriously. Anyone following this knows how wrong most got it and still do.
May I ask, Ms Dattani, if hysteria rules and a rushed-through Covid vaccine does, as a number of science-medical experts have warned, cause great harm to many and permanent immune function damage, whose fault will it be?
Would you then have more respect for those who urged caution? I hope so, even as I hope the vaccine does not do as much harm as it might.
By the way, since Covid is no threat to more than 99% of people, how would your number-crunching justify the risk of a poorly tested, highly experimental, rushed vaccine?
The point of doing lengthy trials in a serial rather than in parallel way is to minimise the risk that a new drug or vaccine does cause unexpected side effects. Ideally we would run small scale trials for 10 years and ensure we cover as many different types of people in a logical manner that starts with the fittest and least likely to suffer badly and then moving on to those more likely to have side effects. So it is a balance of risk between using a vaccine which has been tested in a significant sized population and shown no real problems but not had the ideal testing against continuing cycles of lockdowns and restrictions.
Fortunately it looks like in the first group to be vaccinated there will be a large number of the most at risk of suffering side effects – care home residents. Therefore if there is a problem that has not been detected by the trial we will find out very quickly. Yes that will be very sad for us all but it won’t result in the loss of many QALYs Vs the number of QALYs which can be saved by no longer screwing our economic any further and not screwing the futures of our children further. Finally a sensible balance of risk decision!
Given I’m planning to be vaccinated, could you point me to the ‘science-medical experts’ you mention? I’m pretty sceptical, but willing to look at what they say. Thanks.
As a general point, though, is it a coincidence that the people who talk UP the risks from the vaccine are usually the same people to talk DOWN the risks of the virus? Your post below brought this out for me. I’d be more convinced by someone who thinks the virus is pretty serious, but the vaccine may have some overlooked risks. Or even acknowledges that the virus will still be substantially more unpleasant and dangerous for most people than the side-effects of the vaccine.
The age stratification of the virus is well known. This shouldn’t be debatable. If there are even a small amount of adverse effects on children the vaccine will be worse than the virus. If you are 70 years old and not in the best of health… what do you really have to lose? It might be worth it.
Is there any proof that the vaccine is poorly tested and highly experimental?
The vaccines have certainly been rushed or developed at speed – largely due to large sums of money, focused efforts and regulators working alongside to help get them approved early. ‘Highly experimental’ is misleading, people have been working with mRNA vaccine development for years and the experiments happened before Stage 3 Trials on 10,000s of people.
Now certainly people shouldn’t be forced to have the vaccine as this is not only illegal but also not proportional – we don’t force people to have TB, Measles or flu jabs either, all of which would and could save lifes.
The hysteria though is a big problem and the massive over reach of lockdown is a serious blow to our freedoms, economy, quality of life and long term health.
However just because some people have overstated the dangers of Sars-Cov-2 to plague like proportions doesn’t mean it isn’t a serious virus that we’re better off not catching. I just wish we’d have a fraction of the focus world wide on easily treatable and bigger killers.
I’m a Taurus. What’s my future?
A load of BS I imagine.
Tis true I shall have to wade through very much if I carry on frequenting this site. 🙂
I forecast and extended spell inside followed by a sore arm and then utopia….
You sir are a super forecaster!
What does that mean, “end of the beginning” of the pandemic?
Reading the article, it sounded to me more like “the beginning of the end of the pandemic”… But I put it on the fact that am not a native English speaker.
Anyhow, if this is just “the end of the beginning of the pandemic” and only now we enter in “main course”, it will be a hell of a ride coming on.
On the other hand, medical and physical health aside, the author is true: The worst part of this “pandemic” (let’s call it that way) is yet to come. Namely; the economic problems, the psychological mutations… World and life as we know it…
Me and a friend of mine, intuiting what’s going on, used to say in february-march:
We’ll (people will) talk in terms “ante-covid” and “post-covid era” as we talk about “before the revolutions of the ’90’s” and “after the revolution”.
No… We didn’t “dare” to go to BC or BCE…
…as in Before Covid Era!
Prediction is very difficult, especially if it’s about the future (Neils Bohr). If you’re so good at it, surely you should be the wealthiest woman in the world?
Bully for you but forecasts about a vaccine are not of much practical use. Some debunking (or at least analysis or forecast) of the clearly discredited Imperial College model which helped get us into this lockdown mess would have been of more use
It seems to me that a lack of bias is necessary for forecasting and this is something anyone in the public eye has difficultly getting rid of. Surely, the benefit of a forecast is to predict what others cannot. And the better predictions would be able to predict in earlier on, if possible. A prediction in April of 5% is now wrong and by definition was useless, unless stated that prediction is likely to be inaccurate. By comparison a prediction in December is relatively easy to make.