“Don’t tempt fate” and all that, but isn’t it quite unlikely we get a variant that’s more infectious than Omicron and at the same time, more severe?
SARS CoV-2 coronavirus / Covid-19 (No tin foil hat silliness please)
- Thread starter Don't Kill Bill
- Start date
“Don’t tempt fate” and all that, but isn’t it quite unlikely we get a variant that’s more infectious than Omicron and at the same time, more severe?
The captain hindsight use of pandemic modelling to argue one side or the other is particularly grating. As has already been mentioned loads of times in this thread, modelling is done in good faith, before the event, using the best data available, to the best of their abilities to guide planning for public safety.
I don’t think anything says “arse hole” more than using said modelling a year later to win an Internet argument. The models are produced by scientists interested in minimising human suffering.
I don’t think anything says “arse hole” more than using said modelling a year later to win an Internet argument. The models are produced by scientists interested in minimising human suffering.
Nothing screams "arse hole" then someone who rants about something which has not even happened.
EDIT: Or are you referring to something on Twitter?
Don’t feel personally attacked, I haven’t even read your posts. It was in response to what I’ve seen on Twitter countless times and I’m sure in this thread too. I glanced over recent posts and saw models/predictions being discussed.
Ah I see, sorry, I was just so confused because I was genuinely not trying to criticise any model there
If you look at the models you'll see dozens of different inputs and outputs modelled. When you see it shortened down by the clickbait headline writers they usually go for the most extreme (typically the scariest) version and ignore the inputs that fed the model. A year later the same headline writers describe them as ridiculous (or even deliberately misleading) predictions, which they weren't - they were a possible scenario presented for planning purposes, usually one of lots of scenarios.
So, sure, you can call them predictions if you want. I just don't think it helps people understand them as "what if" scenarios, which is how they are actually used.
Maybe. From original, to alpha, to delta they became more infectious and more severe each time. So it was always a worry that there’s a link between transmissibility and severity of disease. Omicron bucked that trend. Which is a huge relief.
I would say that the general public understand what a "prediction" means. Saying something is "not a prediction" may have the adverse effect of implying to the general public that said outcome(s) will definitely occur if the conditions are met. A model can of course never be definitive. If anything, the language you are using in my view therefore also leads to confusion.
Having said that, the best solution would simply be for journalists to not use clickbait titles in the first place!
When the line between model-based policy making and policy-based modelling blurs and impacts people's livelihood then scrutiny of the SAGE models and evidence is fair game. The distance between the models and reality have been huge, to the point where there's a strong argument for how useful they are with such a huge error rate.
Imperial College's model for SAGE suggested back in March last year that only 45% of the country would have protection from the virus by late June, despite a month later ONS figures was showing an estimated 68.3% of the adult population having antibodies and second doses scheduled after the ramp up in January & February of last year. A rhetoric question, but why would they under call the impact of prior infection and the vaccination programme? With that level of gap and inaccuracy in the data affecting policy, then to hold them beyond reproach isn't useful for this and future pandemics.
I'd still say some of the early modelling that was pushed in some media was worst case scenarios (which wasn't made clear, it was as if it was going to happen) and over blown to make people more scared. Doom and gloom sells. Obviously it wasn't all media outlets.
I know you said the scientists done the modelling, some will have been quite wrong I understand as it's not exact, but the way most people get their info is direct from media, and they chose to cherry pick whichever they wanted to fit their story, so if they wanted a big headline they'd grab the worse case scenario one.
We got a lot of feedback from students that our (in-person) labs were the high points of their (otherwise virtual) semesters. The one I taught was strictly distanced and much quieter than it used to be pre-covid, but they still liked it. So even with much older students, even with restrictions, in-person is important. I get that.
But I'm teaching in a rich private university that could afford to reduce class sizes, install HEPA filters, give every student a fresh surgical mask* for every lab, this was before even delta... It was a microbio course with most of the students aiming for medicine or research, they were old, informed, and motivated enough to respect masking and distancing rules. Our group of 18 had either zero or one case over 4 months of teaching. I am asthmatic, fat and unfit but not obese, live alone, and am 30, not zero risk but not terrible.
In the US, where this debate is very much part of the culture war:
Many regular schools have crowded classes, no ventilation, often no testing, young kids with very different information and motivations and hence very variable masking, older and at-risk teachers with multiple comorbidities, all living with others in their household. Basic safety requirements demanded by teachers unions are not being provided by city govts even when they are funded.
Inevitably, as you said, it's spreading like wildfire through schools (an amazing graph here). And while most people aren't getting anything serious, with hospitalisations and deaths rising as quickly as in previous waves, those who do get serious symptoms might well have to fend for themselves.
Add to this that the people pushing fairy-tale science in 2020 regarding schools are back and prominently pushing re-opening, it's bound to increase suspicion. (For example, Emily Oster, an economist who in 2020 said covid can't spread much in schools and created a deliberately undercounted dashboard, whose data she used in the WaPo and NYT, is back prominently on CNN with the same recommendations)
And that's the impact on teachers and households without going into the students themselves. Since your post I've seen these stories:
It's better to say
1. We have lost the current phase of the fight to contain covid
2. Full re-opening of schools means an estimated x deaths and possibly y long-term issues for students and teachers (it's tough to model households)
3. But we must prioritise face-to-face human social contact over other issues.
And let parents and teachers decide accordingly. Clarity instead of what seems to be haphazard, dysfunctional nonsense.
Is there a link between severity and transmissibility? I'd say there were far few data points to suggest a significant causal link at the moment. Severity can go up or down a bit without affecting the fitness of each variant significantly whereas any new dominant variant has to be more infectious or it will die out. So on average new variants will be less infectious than Omicron so new dominant variants will become less and less likely. If we can get to an endemic state with a reduction in the number of infections, particularly long term infections that many think tend to produce new variants most often, then we will be less likely again to get a new more infectious variant.
So in summary we will get a new more harmful and infectious variant by COB today
Is there a link between severity and transmissibility? I'd say there were far few data points to suggest a significant causal link at the moment. Severity can go up or down a bit without affecting the fitness of each variant significantly whereas any new dominant variant has to be more infectious or it will die out. So on average new variants will be less infectious than Omicron so new dominant variants will become less and less likely. If we can get to an endemic state with a reduction in the number of infections, particularly long term infections that many think tend to produce new variants most often, then we will be less likely again to get a new more infectious variant.
So in summary we will get a new more harmful and infectious variant by COB today
Can I ask if the bolded is opinion or fact?
It is more or less just basic probability. A new variant will be more or less infectious than the dominant variant. For the sake of argument the initial probability that a new variant would be more infectious would be approx 50/50. As each more infectious dominate variant arises the chances of each new variant being more infectious gets less and less because there are only so many mutations possible for the virus to remain functional. In other words instead of there being a 50/50 probability of a new variant being more infectious that the dominant strain the vast majority will less infectious and die out. I was told by a friend who works vaguely in the area that this is (partly) why highly infectious diseases like Measles tend to be more stable than the common cold. It doesn't mean more infectious variants can't arise, just that they are likely to do so less often. If they aren't more infectious severity is irrelevant as they won't become the dominant strain and/or will die out.
Severity is more likely to go either way because as long as the virus can be passed on during the infectious period severity doesn't really make much difference to viral fitness. I'm sure there is more nuance to it all but that seemed to be the basics of what I was told.
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Thanks, that logic makes sense. Although all this seemingly positive news is making me a bit nervous though. I'm waiting for the next kick in the nuts.
We now need to get the world vaccinated as this will further reduce the odds of a new dominant variant.
My body: You have symptoms, better get tested.
My body during wait for test result: This is bad, you're burning up, probably will be hospitalised and die.
My body after negative test result: Symptoms? What symptoms, pussy?
My body during wait for test result: This is bad, you're burning up, probably will be hospitalised and die.
My body after negative test result: Symptoms? What symptoms, pussy?
Modelling may be in good faith but it’s reasonable to ask why it’s been so wrong especially if policy decisions are going to be influenced by it going forward.
What has been so wrong? If it is variant related then modelling would be based on existing variants so will vary when a new variant arises. I'd guess the other factor is that human behaviour becomes more and more important as infectiousness increases. And human behaviour is hard to model on such short timeframes.
I'm not sure what you mean. Wrong in what way? Actions are taken to reduce the impact, so that will affect the outcome.
Are you suggesting that because things didn't turn out as 'predicted' that using models is inherently flawed?
Seasonal? It loves summer here in Australia, I suspect he’s making out it’ll just be a winter thing.
But we’ve been through many months where everyone’s been criticising the lack of restrictions in England and the reality in terms of hospital numbers and deaths have been far below even the most optimistic range of predictions based on the modelling. We can’t turn around now and say that the discrepancy was a result of restrictions that prevented it being even worse - because there hasn’t been any.
Given lack of measures in England for the last few months surely we should be looking to compare the upper end of the modelling predictions that presumably were based around an assumption of minimal public health measures, which is exactly what we have. Surely the lower end of the modelling was based on stringent measures that never happened.
Arguing that modelling designed to take into account changes in public behaviour can’t be expected to accurately take into account changes in public behaviour is also a bit shit
Questioning why it has been so inaccurate seems fair especially given this thread is hardly packed with praise of UK govt for keeping most metrics below the most optimistic of modelling predictions over the last few months.
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Are people really still defending modelling at this point? They are attempting to predict the utterly unpredictable, the majority therefore are always going to be way off and have been just that.
35 million booster jabs, starting with the most vulnerable that would have been hospitalised, has to some extent saved the day. I say to some extent as many have still died or now have life-changing long-term effects, I would word that better if I could.
In defence of modelling (I know, I should never have mentioned it in the first place ).
This is the summary of the modelling that encouraged the UK government to stay open, when the rest of Europe was closing. The models were written when we knew a fair bit about how Omicron affected infection rates, but very little about what happens with death rates amongst older adults, and in particular amongst those who've had boosters.
The models were the basis on which central government went for a Plan B+ that is Plan B plus accelerated booster program, changes in testing rules/advice and a couple of solemn looking press conferences.
Infections and hospitalisations are on track for the lower bounds of Scenario A. We think deaths will come in lower, but we're not sure how much lower - maybe 300/day at peak. The thing the models don't predict are the timing differences between regions and whether regional hospital/care services can cope with their peak.
The models actually were the science advice that suggested stopping football, hospitality, non-essential retail etc weren't actually going to do much other than move some hospitalisations into March, and could potentially cause more deaths overall as boosters started to wane.
I know people view the UK as Plague Island with no rules, but the modelling is part of the reason why they chose a particular gamble on what was worth doing.
On a day to day basis they look at a series of "nowcasts" with daily data on things like mobility patterns, testing, hospital admissions, occupancy where it's available, and predicted data where the daily data is incomplete. A lot of that is public domain, with daily updates on the dashboard, some of the most up to date info appears as a series of .xls files from the NHS.
The short-term (two week) models using that data know the inputs in terms of current government action, people behaviour etc so they have a fair idea where hospitalisations are going - these are the ones that mean government ministers can keep saying "no new restrictions right now" - because they've already decided that if daily admissions stay below 3k we're doing well and we can slam on the brakes if we have to. Different models for different jobs.
).This is the summary of the modelling that encouraged the UK government to stay open, when the rest of Europe was closing. The models were written when we knew a fair bit about how Omicron affected infection rates, but very little about what happens with death rates amongst older adults, and in particular amongst those who've had boosters.
The models were the basis on which central government went for a Plan B+ that is Plan B plus accelerated booster program, changes in testing rules/advice and a couple of solemn looking press conferences.
Infections and hospitalisations are on track for the lower bounds of Scenario A. We think deaths will come in lower, but we're not sure how much lower - maybe 300/day at peak. The thing the models don't predict are the timing differences between regions and whether regional hospital/care services can cope with their peak.
The models actually were the science advice that suggested stopping football, hospitality, non-essential retail etc weren't actually going to do much other than move some hospitalisations into March, and could potentially cause more deaths overall as boosters started to wane.
I know people view the UK as Plague Island with no rules, but the modelling is part of the reason why they chose a particular gamble on what was worth doing.
On a day to day basis they look at a series of "nowcasts" with daily data on things like mobility patterns, testing, hospital admissions, occupancy where it's available, and predicted data where the daily data is incomplete. A lot of that is public domain, with daily updates on the dashboard, some of the most up to date info appears as a series of .xls files from the NHS.
The short-term (two week) models using that data know the inputs in terms of current government action, people behaviour etc so they have a fair idea where hospitalisations are going - these are the ones that mean government ministers can keep saying "no new restrictions right now" - because they've already decided that if daily admissions stay below 3k we're doing well and we can slam on the brakes if we have to. Different models for different jobs.
You can't take a model seriously that has such wide ranges, where the most extreme options actually significantly overlap each other. It's virtually useless. It was just a way for the government to do what they wanted whilst having a study to point at and say 'look, we're following the science'.
Absolutely, but modelling something so unpredictable isn’t really scientific in the true sense of science.
Imperial have now released a study showing that high levels of T-cells from the common cold can protect against Covid infection, which is probably another reason the original models in particular were so ridiculously overexaggerated. In the years to come we’ll have more and more evidence I’m sure to show the first lockdown experiment in human history was based off completely bonkers predictions.
The imperial study backs up this non-peered reviewed paper also.
In a sense that was the point of the model. They couldn't stop it, they could only squash it. They then had to choose how long they would be willing to squash it for. It effectively knocked out the idea that a "short, hard lockdown of 2-4 weeks" starting just before or just after Christmas, would help.
The answer came back that if you don't squash it for months and wait for an Omicron tuned booster or a new antiviral before opening then it didn't help. In fact some measures, short of a full lockdown, made the overall first quarter death toll worse, by adding more infections in March.
Plus, of course if Omicron got replaced by something more virulent, you would see no longer term (12 month) gain either.
If you are a modeller you build in worst case assumptions, even worse than you think, then even if you are wrong, it’s better than being optimistic and wrong the other way.
Also this wasn’t exactly easy to predict, just modellers looking after their Livelihoods or someone else’s.
Also this wasn’t exactly easy to predict, just modellers looking after their Livelihoods or someone else’s.
This is exactly what is happening in Poland. We have several doctors who are 'outside the system' and 'don't fear speaking the truth'. Anti-vaxx movement considers them all heroes who haven't allowed big pharma to bribe them.
Naturally, they all charge 500% of average consultation price, and are all booked for 3-4 months forward by their devoted fans.
Pandemic has been a great opportunity for mediocre doctors to make a name for themselves here and become valued for 'speaking the truth' that people want to hear.
Russia may now be looking at excess deaths approaching 1m now.
https://www.themoscowtimes.com/2021/12/30/russias-excess-death-toll-hits-930k-a75964
Pro-rata against population that's not so far off IC's 500k deaths in the UK if no action taken estimate. The sad thing is that a lot of Russia's death happened in 2021 and occurred despite vaccines being available. The UK managed to delay things long enough to not to see that number of deaths, because the vaccines took over from the other controls before Delta hit - we've still seen 150k deaths though.
Countries that have managed to delay things further, into Omicron territory, particularly if they've got high protection using vaccines in the over 60s - may come in with much lower overall death tolls. They'll still have to take a leap into the unknown though and some still aren't ready for that.
Ok sure but the modelling presumably factored the boosters in to the equation based on low or high take up
The November/December omicron models looked at boosters based on the planned December rollout. One suggestion was that faster/wider booster rollout was a way of making Plan B controls more effective. Another element was to suggest that a stronger push to reach missed high risk groups (basically the ones not mobile enough to get to the big vaccine centres) was needed.
The government responded by asking the NHS and volunteers to increase the number of booster sites. That led to the weekly total of boosters in the UK jumping from around 2.5m/week (late November, early December) to more than 5m/week in the two weeks before Christmas. They also increased the payment to GPs etc who could vaccinate higher risk people like the housebound and other vulnerable patients who'd been missed. Time from dose 2 to booster was reduced and the eligible age group came down.
The models were supposed to give guidance. That information led to policy changes. That's a model working, not a model screwing up.
The booster rollout jump between November and December in England:
I hope I’m not spreading fake news but if this account is legit it gives a good (and incredibly bleak) insight into how China manages to keep covid numbers surprisingly low.
Hong Kong is doing the same.
A good friend of mine is a pilot there and he tested positive a few days into the 21 day quarantine on arrival in similar looking shipping containers (Penny Bay, Google it). Sent immediately to hospital for a 2 week isolation and observation, and will have to do another 2 weeks in the quarantine centre after that.
I've seen the photos. It's horrible.
Holy shit. 4 weeks isolation! That’s nuts.
Isn't that from the Fyre Festival documentary?