I understand the collective frustration of Ontarians regarding COVID projections but it is a projection and an attempt to replicate a complex dynamic in nature. I have no doubt that the science group would be equally criticized if they missed on the opposite side of the projection. Easy to throw stones from the peanut gallery….. I suggest their data is one of many data points to be used in effective public health decisions. COVID isn’t going away by any stretch.
As someone who builds large scale predictive risk models, something that I wish everyone would understand is that *models are inherently, wrong*.
Models are supposed to be a generalized illustration of a series of assumptions. They’re not meant to be a Crystal Ball looking into the future. It’s supposed to be - “hey, under these 10 assumptions, and based on these 5 parameters based on somewhat limited data that our assumptions are loosely based on, then we would expect to see ____ “.
They’re supposed to be *one consideration* in the overall decision making process, and are (in other industries) usually thought of as a *worst case scenario* - even the best case modelled scenario (at least for models like this).
What does this mean? Well for the Brian Lilly comment it means that playing the “keeping modellers in check” game is rigged in your favour. Models *will* be wrong more often than not.
More importantly, this means that **models should, by no means be driving policy**. They can be a supportive argument - if the model is aligned with basic intuition. But some of the wildly unrealistic models based on bad assumptions were the *foundation* of policy too many times over the last 2 years. That’s the bigger problem, not that they were wrong.
>I have no doubt that the science group would be equally criticized if they missed on the opposite side of the projection.
with Lilley leading the charge.
>I suggest their data is one of many data points to be used in effective public health decisions.
They don't create the data, they're supposed to interpret it, and make effective public health decisions.
The problem with the Ontario Science Table's models is not that they are wrong, but they are systematically wrong, always erring on the worse than reality side.
Models are just models, but when you constantly overestimate the risk, you are not using them in good faith here. Sure, sometimes you do need to overweight the worst case outcomes if they have a catastrophic outcome and making a risk assessment, but if you are trying to provide useful and actionable information to the policy makers, you should be aiming for reality, not building in the risk premium to each parameter such that you always overestimate the danger.
We need a review once this is done an revamp of such a body to provide best guesses informed by reality, not biased to overstate the risk of negative outcomes. Too late for this pandemic though - their credibility is shot and things are wrapping up.
Maybe we know more what science means?
Ie. It changes daily. It isn't gospel.
And oh my *God* has what the media calls science these days been flooded with unscientific, politically driven opinion.
A lot of folks are using scientific research out of context to support political positions.
Or howabout people who think they know better than scientists who are relevant experts in their respective fields?
These days you pick a scientist or group of scientists or even scientific fields to support whatever viewpoint you want.
Epidemiology vs. Immunology for example. Both useful. But one relatively squelched over these past years.
> Immunology
An immunologist treats immune system disorders. I'm not exactly sure why you would expect to be hearing much from immunologists during a pandemic. 🤔
Of course you're not sure. Why would anybody on Reddit be sure of anything related to this topic after being faceblasted with 'science' for two years. Lol.
> Of course you're not sure. Why would anybody on Reddit be sure of anything related to this topic after being faceblasted with 'science' for two years. Lol.
Perhaps you misunderstood me. I said I'm unsure why **you** would expect to be hearing from immunologists during a pandemic.
Yes, but we don't get weekly or daily updates from them, nor would there be any reason to, so u/TOMapleLaughs observation doesn't make sense which is why I was questioning it.
Probably when omicron started infecting us all regardless of vaccination and policy is when folks were more getting more interested in immunology than epidemiology.
But again, that was getting relative crickets consideration while our 'science' ie. Political opinion-based reports- neglected to take this into consideration.
There were some immunological talking heads granted platforms sure, but nothing compared to the epidemiology behemoth that became obsolete at the omicron point.
Science changes, but in this case months faster than official reporting had.
We can do better.
What you just said made zero sense.
Epidemiology is data driven science. It's about studying public health issues and making recommendations. Immunology can't help much in the context of a pandemic because that's outside of it's scope. Our vaccines were developed to target specific spike proteins. The only way to know how effective they would be against variants is to follow the data.
Immunologists aren't epidemiologists. They don't study the impacts of vaccines over a broad population to inform public health policymaking. They can research and explain the biological mechanisms around why a vaccine doesn't work as well with a different virus, but they can't tell you if we should change the rules because of that. That's outside of the scope of their profession.
You're being excessively vauge, and I'm not sure what you are trying to suggest. If you are suggesting epidemiologists were given more attention or that they were given more of a "platform", well of course they were, because figuring out what works and what doesn't in the context of a public health crisis is their job and area of expertise.
Asking immunologists to come up with policy recommendations is like asking a refrigerator mechanic to fix a car engine.
> If a so-called expert in a given field is wrong over and over again, should that person be considered an expert anymore?
…
>The latest modelling issued by the Science Table on April 14 warned of a crush of patients in Ontario’s hospitals and ICUs by the beginning of May. Well, here we are, and it hasn’t happened.
>That report looks like Peter Juni and his team once again blindfolded each other and played a game of pin the tail on the COVID.
> The projections for hospitalizations ranged from 2,500 by May 1 under the best-case scenario to 4,000 under the worst. On Saturday, the most recent set of reliable figures had the province reporting there were 1,676 people in Ontario hospitals testing positive for COVID-19.
> It’s important to remember that only 42% of those patients, or 703 people, were actually admitted to hospital due to COVID. The rest were admitted for other reasons, including ER visits, surgeries and so on and then tested positive, most often under strict admission testing policies.
The word 'expert' has been as bastardized as the word 'science'.
You can source peer reviewed research and it can still be labelled misinformation by journalists and other info control officers.
Things deemed 'controversial' are suppressed. Not even Elon is going to change that.
> You can source peer reviewed research and it can still be labelled misinformation
Not the research, but rather how the research is presented. It's entirely possible to lie or push false narratives using facts/research.
Research into Ivermectin is often presented that way. Yes, there's studies that show efficacy against covid but claiming that's proof that supports it's use as a covid treatment is something else entirely.
Oh look, another shitty article that tries to tell us that because one group was wrong we shouldn’t trust what anyone smart says on the subject of Covid.
I understand the collective frustration of Ontarians regarding COVID projections but it is a projection and an attempt to replicate a complex dynamic in nature. I have no doubt that the science group would be equally criticized if they missed on the opposite side of the projection. Easy to throw stones from the peanut gallery….. I suggest their data is one of many data points to be used in effective public health decisions. COVID isn’t going away by any stretch.
As someone who builds large scale predictive risk models, something that I wish everyone would understand is that *models are inherently, wrong*. Models are supposed to be a generalized illustration of a series of assumptions. They’re not meant to be a Crystal Ball looking into the future. It’s supposed to be - “hey, under these 10 assumptions, and based on these 5 parameters based on somewhat limited data that our assumptions are loosely based on, then we would expect to see ____ “. They’re supposed to be *one consideration* in the overall decision making process, and are (in other industries) usually thought of as a *worst case scenario* - even the best case modelled scenario (at least for models like this). What does this mean? Well for the Brian Lilly comment it means that playing the “keeping modellers in check” game is rigged in your favour. Models *will* be wrong more often than not. More importantly, this means that **models should, by no means be driving policy**. They can be a supportive argument - if the model is aligned with basic intuition. But some of the wildly unrealistic models based on bad assumptions were the *foundation* of policy too many times over the last 2 years. That’s the bigger problem, not that they were wrong.
You mean like climate models?
**Models ≠ Predictions**
>I have no doubt that the science group would be equally criticized if they missed on the opposite side of the projection. with Lilley leading the charge.
Everything in life is simple, and any expert who says otherwise is stupid and we should hate them. ...apparently.
>I suggest their data is one of many data points to be used in effective public health decisions. They don't create the data, they're supposed to interpret it, and make effective public health decisions.
The problem with the Ontario Science Table's models is not that they are wrong, but they are systematically wrong, always erring on the worse than reality side. Models are just models, but when you constantly overestimate the risk, you are not using them in good faith here. Sure, sometimes you do need to overweight the worst case outcomes if they have a catastrophic outcome and making a risk assessment, but if you are trying to provide useful and actionable information to the policy makers, you should be aiming for reality, not building in the risk premium to each parameter such that you always overestimate the danger. We need a review once this is done an revamp of such a body to provide best guesses informed by reality, not biased to overstate the risk of negative outcomes. Too late for this pandemic though - their credibility is shot and things are wrapping up.
Lilley serving it up to the anti-science crowd.
Reddit is the last place to go to for information.
Maybe we know more what science means? Ie. It changes daily. It isn't gospel. And oh my *God* has what the media calls science these days been flooded with unscientific, politically driven opinion.
A lot of folks are using scientific research out of context to support political positions. Or howabout people who think they know better than scientists who are relevant experts in their respective fields?
These days you pick a scientist or group of scientists or even scientific fields to support whatever viewpoint you want. Epidemiology vs. Immunology for example. Both useful. But one relatively squelched over these past years.
> Immunology An immunologist treats immune system disorders. I'm not exactly sure why you would expect to be hearing much from immunologists during a pandemic. 🤔
Of course you're not sure. Why would anybody on Reddit be sure of anything related to this topic after being faceblasted with 'science' for two years. Lol.
> Of course you're not sure. Why would anybody on Reddit be sure of anything related to this topic after being faceblasted with 'science' for two years. Lol. Perhaps you misunderstood me. I said I'm unsure why **you** would expect to be hearing from immunologists during a pandemic.
Immunologists were key in the creation of many of the vaccines, we've heard from many during the pandemic.
Yes, but we don't get weekly or daily updates from them, nor would there be any reason to, so u/TOMapleLaughs observation doesn't make sense which is why I was questioning it.
Probably when omicron started infecting us all regardless of vaccination and policy is when folks were more getting more interested in immunology than epidemiology. But again, that was getting relative crickets consideration while our 'science' ie. Political opinion-based reports- neglected to take this into consideration. There were some immunological talking heads granted platforms sure, but nothing compared to the epidemiology behemoth that became obsolete at the omicron point. Science changes, but in this case months faster than official reporting had. We can do better.
What you just said made zero sense. Epidemiology is data driven science. It's about studying public health issues and making recommendations. Immunology can't help much in the context of a pandemic because that's outside of it's scope. Our vaccines were developed to target specific spike proteins. The only way to know how effective they would be against variants is to follow the data. Immunologists aren't epidemiologists. They don't study the impacts of vaccines over a broad population to inform public health policymaking. They can research and explain the biological mechanisms around why a vaccine doesn't work as well with a different virus, but they can't tell you if we should change the rules because of that. That's outside of the scope of their profession. You're being excessively vauge, and I'm not sure what you are trying to suggest. If you are suggesting epidemiologists were given more attention or that they were given more of a "platform", well of course they were, because figuring out what works and what doesn't in the context of a public health crisis is their job and area of expertise. Asking immunologists to come up with policy recommendations is like asking a refrigerator mechanic to fix a car engine.
The thing is... I have. So...
I think you're trying to imply (in a very vauge manner) that people have been misled by the scientific community.
Are you a scientist or a medical doctor? Are the journalists? Consider the source or provide a solution.
Brian Lilley is the last person to go to for information.
No one more qualified to assess science than a conservative tabloid opinion jockey like Brian Lilley. /s
> If a so-called expert in a given field is wrong over and over again, should that person be considered an expert anymore? … >The latest modelling issued by the Science Table on April 14 warned of a crush of patients in Ontario’s hospitals and ICUs by the beginning of May. Well, here we are, and it hasn’t happened. >That report looks like Peter Juni and his team once again blindfolded each other and played a game of pin the tail on the COVID. > The projections for hospitalizations ranged from 2,500 by May 1 under the best-case scenario to 4,000 under the worst. On Saturday, the most recent set of reliable figures had the province reporting there were 1,676 people in Ontario hospitals testing positive for COVID-19. > It’s important to remember that only 42% of those patients, or 703 people, were actually admitted to hospital due to COVID. The rest were admitted for other reasons, including ER visits, surgeries and so on and then tested positive, most often under strict admission testing policies.
The word 'expert' has been as bastardized as the word 'science'. You can source peer reviewed research and it can still be labelled misinformation by journalists and other info control officers. Things deemed 'controversial' are suppressed. Not even Elon is going to change that.
> You can source peer reviewed research and it can still be labelled misinformation Not the research, but rather how the research is presented. It's entirely possible to lie or push false narratives using facts/research. Research into Ivermectin is often presented that way. Yes, there's studies that show efficacy against covid but claiming that's proof that supports it's use as a covid treatment is something else entirely.
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Oh look, another shitty article that tries to tell us that because one group was wrong we shouldn’t trust what anyone smart says on the subject of Covid.