1504 replies to this topic

[gamesguru]

Study exploring the idea of a Fall 2020 resurgence.  Thank you.

 

Pollen Explains Flu-Like and COVID-19 Seasonality

Abstract

Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19.

 

Pollen is documented to be antiviral and allergenic, play a role in immuno-activation, and seems to create a bio-aerosol lowering the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics including COVID-19. We tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in The Netherlands with its 17 million inhabitants. We combined changes in flu-like incidence per 100K/Dutch citizens (code: ILI) with weekly pollen counts and meteorological data for the same period. Finally, a discrete, predictive model is tested using pollen and meteorological threshold values displaying inhibitory effects on flu-like incidence.

 

We found a highly significant inverse association of r(224)= -.38 between pollen and changes in flu-like incidence corrected for incubation period, confirming our expectations for the 2019/2020 COVID-19 season. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -.48 (p < .001) when pollen thresholds of 610 total pollen grains/m3 per week, 120 allergenic pollen grains/m3 per week, and a solar radiation threshold of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu- like seasons. Solar radiation is a supportive factor, temperature makes no difference, and relative humidity associates even with flu-like incidence increases.

 

We conclude that pollen is a predictor for the inverse seasonality of flu-like epidemics including COVID-19, and solar radiation is a co-inhibitor. The observed seasonality of COVID-19 during Spring, suggests that COVID-19 may revive in The Netherlands after week 33, the start being preceded by the relative absence of pollen, and follows standard pollen-flu seasonality patterns

[ambivalent]

Well it may turn out that the recent mass gatherings in the US and Europe may well have been beneficial to the pandemic-cause: we might build up a sizeable portion of immunity amongst the population with low risk to life. (if the virus still spreads asymptomatically).

Edited by ambivalent, 08 June 2020 - 10:12 PM.

[gamesguru]

virus spreads asymptomatically

 

doubtful it is a major factor.  Best to just testing, trace, isolate through the Summer months

Asymptomatic spread of coronavirus is ‘very rare,’ WHO says
Published Mon, Jun 8 20201:05 PM EDTUpdated 36 min ago

• Government responses should focus on detecting and isolating infected people with symptoms, the World Health Organization said.
• Preliminary evidence from the earliest outbreaks indicated the virus could spread even if people didn’t have symptoms.
• But the WHO says that while asymptomatic spread can occur, it is “very rare.”

Coronavirus patients without symptoms aren’t driving the spread of the virus, World Health Organization officials said Monday, casting doubt on concerns by some researchers that the disease could be difficult to contain due to asymptomatic infections.

Some people, particularly young and otherwise healthy individuals, who are infected by the coronavirus never develop symptoms or only develop mild symptoms. Others might not develop symptoms until days after they were actually infected.

Preliminary evidence from the earliest outbreaks indicated that the virus could spread from person-to-person contact, even if the carrier didn’t have symptoms. But WHO officials now say that while asymptomatic spread can occur, it is not the main way it’s being transmitted.

“From the data we have, it still seems to be rare that an asymptomatic person actually transmits onward to a secondary individual,” Dr. Maria Van Kerkhove, head of WHO’s emerging diseases and zoonosis unit, said at a news briefing from the United Nations agency’s Geneva headquarters. “It’s very rare.”

Government responses should focus on detecting and isolating infected people with symptoms, and tracking anyone who might have come into contact with them, Van Kerkhove said. She acknowledged that some studies have indicated asymptomatic or presymptomatic spread in nursing homes and in household settings.

[ambivalent]

It looks as though pollen is a great therapeutic - now would be a very good time to get the virus. 

[Mind]

More solid evidence that the novel(?) coronavirus was circulating in Wuhan as early as September of 2019. https://abcnews.go.c...ory?id=71123270

 

Once again hats off to Daniel Cooper and others who speculated about this earlier in this thread. The narrative that the communist party in China wants everyone to believe - that the disease was first identified on December 31st - it very likely false.

 

There is no way the disease was not spreading all around the world for months, before the panic in late January and February of 2020.

 

What most likely happened is that it was spreading all over the world since September of 2019 (or earlier) and everyone was chalking it up to a "bad" flu. When winter hit in the northern hemisphere and the virus got into nursing homes in Europe and the U.S., the deaths increased. Panic and quarantine ensued, leading to the denial of regular medical care, and more excess deaths.

[gamesguru]

The increased traffic occurs around normal respiratory flu season and should not be taken as a direct indicator of spread of COVID-19.

 

It's important to keep in mind in the early days of Wuhan the people have absolutely zero awareness of a novel disease, and hence zero mitigation or distancing.  The disease had a R0 > 3 for months with latent period ~7d, probably starting in November.

 

Please don't believe the claims it "started way earlier than that".  These claims are self-contradictory with themselves.  Suppose the latent period is 7 days and R0 is 3, then it doesn't work.  We have to increase R0, but then by this point (8 months later) we should have had it circle the globe twice.. but there are still plenty of new infections in hotspots like New Orleans.  These epidemiological "thinkers" can't have their cake and eat it.

 

These ideas—that it started way earlier and is way more widespread—are coming from guys who just confirm what they want to believe.  It's not real science.  It's not backed up by any evidence or real modeling.  You're being lied to about the lethality and prevalence of a disease we still know little about for purely political reasons.

 

Model built by U of T researchers suggests coronavirus outbreak began in November, has yet to be controlled

[gamesguru]

Wow.  California is inflating the curve now, so much for flattening it.  Good luck telling that to Felon Musk tho

 

This comes despite much increase in testing capacity.

We are truly entering a second wave before the Fall.  Brilliant.  Be ready to hunker back down at home for round 2 of lockdown..

 

California coronavirus cases remain on upward trajectory
Tue 09 Jun 2020

The number of coronavirus infections throughout California continues to rise steadily as counties further lift stay-at-home restrictions amid increasing efforts to restore the battered economy.

On Monday, health officials reported nearly 3,100 cases, bringing the total to more than 134,000 infections in the state.

California surpassed 100,000 cases a little less than two weeks ago and has reported at least 2,000 infections every day since.

The bulk of the state's infections and deaths are still occurring in Los Angeles County, where nearly 64,700 people have contracted the virus and more than 2,600 people have died. On Saturday and Sunday, officials announced 81 more deaths — the highest number of deaths reported over a weekend in more than a month.

[ambivalent]

 

What most likely happened is that it was spreading all over the world since September of 2019 (or earlier) and everyone was chalking it up to a "bad" flu. When winter hit in the northern hemisphere and the virus got into nursing homes in Europe and the U.S., the deaths increased. Panic and quarantine ensued, leading to the denial of regular medical care, and more excess deaths.

 

I have to say I believe this to be quite unlikely. The spread of the disease (in uk) fitted analyst's modelling of the disease and that was predicated on a seeding early in the year. If it had been in the uk for months then we should already have found ourselves knee deep in a pandemic: we weren't. The number of cases rose exponentially, from a handful to hundreds to thousands. If it had been circulating for months then instantly thousands and thousands should have been identifying with covid symptoms - switch the light on everywhere instantly infected: people were scared reporting minor worries but the covid frequency was low. It could only ever hide in seasonal flu briefly, it is far too infectious and contagious to do so for too long - it makes no sense for it to have been here for months, unless there was some paradoxical seasonal factor suppressing it.

 

Lombardy and New York blew up so quickly I doubt any model would reverse extrapolate a point of origin that would go back months. If the doubling rate was say 3 days you simply couldn't have hundreds of people infected roaming around  New York in November. The city would have been in a full blown crisis by Christmas.

 

The infection spread in the world is in line with how reported events developed in Wuhan - it is highly contagious, it just couldn't have conned us for months.

 

(It would also be fairly easy to spot from above average levels of daily death rate - variance couldn't hide COVID's impact for months, its too contagious)

Edited by ambivalent, 09 June 2020 - 10:53 PM.

[ambivalent]

No uk patient zero:

 

https://www.bbc.co.u...health-52993734

[gamesguru]

No uk patient zero:

 

https://www.bbc.co.u...health-52993734

 

That's exactly what I argued them from the start.  I told Dan and Mind, if this thing was seeded 180 times in January it would only speed up the curve 3 weeks.  Somehow they have it made up in their mind though that "tons of people in and out = early superexponential growth". 

 

They think this started way earlier, spread way more voraciously, but yet somehow has yet to achieve herd immunity anywhere.  Sometimes I wish I had some graph paper and a Skype interface to make these guys realize the errors in their ways, because this textbox just ain't cutting it

[Mind]

I have to say I believe this to be quite unlikely. The spread of the disease (in uk) fitted analyst's modelling of the disease and that was predicated on a seeding early in the year. If it had been in the uk for months then we should already have found ourselves knee deep in a pandemic: we weren't. The number of cases rose exponentially, from a handful to hundreds to thousands. If it had been circulating for months then instantly thousands and thousands should have been identifying with covid symptoms - switch the light on everywhere instantly infected: people were scared reporting minor worries but the covid frequency was low. It could only ever hide in seasonal flu briefly, it is far too infectious and contagious to do so for too long - it makes no sense for it to have been here for months, unless there was some paradoxical seasonal factor suppressing it.

 

Lombardy and New York blew up so quickly I doubt any model would reverse extrapolate a point of origin that would go back months. If the doubling rate was say 3 days you simply couldn't have hundreds of people infected roaming around  New York in November. The city would have been in a full blown crisis by Christmas.

 

The infection spread in the world is in line with how reported events developed in Wuhan - it is highly contagious, it just couldn't have conned us for months.

 

(It would also be fairly easy to spot from above average levels of daily death rate - variance couldn't hide COVID's impact for months, its too contagious)

 

I appreciate your reasoned response. Thanks.

 

Remember, Italy was dealing with a strange "pneumonia" outbreak late last year, and back in November/December of last year, Dr. Fauci commented on how "severe" the flu season in the U.S. was shaping up to be.

 

Remember, there was no testing for the novel(?) coronavirus until it was officially identified. What I saw in countries where it looked like an exponential spread of the disease was mostly an epidemic of testing. Some of the testing was just catching a lot of the infections that had occurred in the 2 to 3 weeks before the epidemic hit. The virus was also spreading in late winter at a higher rate (typical seasonality). Panic, quarantine, and disruption of regular medical services led to a lot more deaths than would have otherwise occurred.

 

In addition, there was an analysis a few days ago from JPM which seemed to show there was no correlation between lockdowns and infection rates. If it was super contagious, then every country should have seen the same spread, or the countries with no/minimal lockdowns should have seen enormous casualties, which didn't happen.

Edited by Mind, 10 June 2020 - 05:26 PM.

[ambivalent]

Thanks Mind.

 

We have the example of Sweden with no lockdown but implemented social distancing measures. Then there are the other Scandinavian countries: Norway; Finland and Denmark. They have a combined population of around 60% above Sweden. Sweden's current death toll is 4,700; the others combine to round 1150. Approaching a x7 death rate.

 

On lockdown, from a precious government adviser. 

 

https://www.bbc.co.u...health-52995064

 

I certainly cannot explain all exceptional effects of the virus - but what was witnessed in NY and Lombardy was an absolute and rapid crisis. That such a high proportion died in Lombardy is indicative that there are factors governing infection or affection rates which are not understood. I would say that to suggest that lockdown has no impact on the spread of the virus is to presume that it doesn't transmit from human to human. Locking down undoubtedly could backfire - weakened immune systems due to poor diet, lack of exercise and psychological stress is no preparation for future virus exposure. Lockdown works because it decreases human interaction. Britain locked down later than France, Italy and Spain - despite being weeks behind on the timeline we faired much worse: it is scandalous.   We locked late and didn't detect and trace effectively, particularly compared to Germany.

 

Yes I agree with increased testing, comes increased cases - so the growth is distorted. But as I mentioned we weren't testing high in the beginning when everyone was jittery and yet the number of deaths (including excess morbidity deaths) did increase significantly as the weeks went by.

 

There is much to be understood and much remains unexplained - perhaps conditions altered or the virus mutated but as the previous linked article demonstrated that in the uk at least, most tested infected strains entering during those months.  

 

As for bad flu seasons, they're rather like bad hurricane seasons these days - all too common.  Anyhow, lets hope the virus isn't as contagious as thought or it was and that with lockdown-release we don't see a second wave, with help from the pollen.

[ambivalent]

Death doubling rates though of Finland, Norway, Sweden, Denmark are all rather similar:

 

https://ourworldinda...rg/covid-deaths

 

 

 

Edited by ambivalent, 10 June 2020 - 07:56 PM.

[ambivalent]

Too late to edit - but that was previous government adviser, rather than precious (we have plenty of those :P)

[gamesguru]

Not to mention the fact that J.P. Morgan is not an academic source.

 

Academic sources have been consistently finding that lives were saved by lockdowns.

 

For critics of the lockdowns, there is a study done by Drexel University showing an estimated 6,202 lives were saved in Philadelphia alone and more than 57,000 avoided hospitalization.

 

The study was conducted specific to 30 cities around the U.S., with a remarkable 23,000 fewer deaths in the city of Baltimore, Maryland.

 

"All of the many sacrifices they're making by staying home are not in vain, that it actually has this impact that affects all of us," professor and study's author Amy Carroll-Scott, Ph.D., told ABC-6 in Philadelphia.

 

 

 

One of the most telling metrics I look at is the % positive rate for testing.  Obviously it helps to look at it side by side with the total testing capacity, as if that remains constant but the % positive greatly changes we can assume the population prevalence has greatly changed.

 

Since we can see the testing capacity has remained at ~20k per day^[1], one can rightly infer the lockdown has been a boon for New York.

[albedo]

Here are the details of the study reported by Forbes on lockdowns with a picture on how different EU countries implemented different measures. Reported also here.

"From the last paper in Nature, it looks like the measures in EU, in particular the differentiated lockdowns, saved 3.1 million people in EU from possible deaths (table 1). The research team is from UK and US."

Flaxman, S., Mishra, S., Gandy, A. et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Nature (2020). https://doi.org/10.1...1586-020-2405-7

https://www.nature.c...1586-020-2405-7

 interventions EU.PNG   113.25KB   0 downloads

[Daniel Cooper]

More solid evidence that the novel(?) coronavirus was circulating in Wuhan as early as September of 2019. https://abcnews.go.c...ory?id=71123270

 

Once again hats off to Daniel Cooper and others who speculated about this earlier in this thread. The narrative that the communist party in China wants everyone to believe - that the disease was first identified on December 31st - it very likely false.

 

There is no way the disease was not spreading all around the world for months, before the panic in late January and February of 2020.

 

What most likely happened is that it was spreading all over the world since September of 2019 (or earlier) and everyone was chalking it up to a "bad" flu. When winter hit in the northern hemisphere and the virus got into nursing homes in Europe and the U.S., the deaths increased. Panic and quarantine ensued, leading to the denial of regular medical care, and more excess deaths.

 

China's covid-19 timeline has never passed the smell test.  They say patient zero got sick December 10th, showed up in a Wuhan hospital December 16th, and that by December 31st they had identified a new virus and informed the WHO.  

 

Assuming that they could have isolated and identified the new virus in less that a week (a month would be more likely), that would have given the CCP about 1 week to make the decision to notify the WHO.  That would never have happened.  The Chinese political leadership would have certainly waited long enough to determine if the virus could be contained to China before announcing to the world they had a new and potentially deadly virus that would significantly damage their economy.  They would have only informed the WHO when they had determined that containment to China was not possible.

 

The Chinese government has been lying through their teeth about this the entire time.

[gamesguru]

Please see the above post with the U of T model.  While it's true the virus crossed into humans before December, it likely did not occur before November.  We don't presumptively push it back to September or whatever lol. Swear you guys get an inch you'll take a mile

[Daniel Cooper]

Please see the above post with the U of T model.  While it's true the virus crossed into humans before December, it likely did not occur before November.  We don't presumptively push it back to September or whatever lol. Swear you guys get an inch you'll take a mile

 

These are models gg.  They aren't gospel.  The conclusions of these models are baked into the assumptions.  If U of T's assumptions are good, then the model outputs are probably good.  Otherwise not.

 

They may well be correct, but model outputs should be approached with a certain amount of skepticism.  They are not facts in the same manner as measured data.  And, we have now have a 4 or 5 month history of covid models being mostly wrong, sometimes dramatically so.  

 

Having not looked at the details of UoT's models I have no opinion on their validity.  But let's be aware that we are talking about models, not something that is an independent fact.

Edited by Daniel Cooper, 11 June 2020 - 01:47 PM.

[gamesguru]

we have now have a 4 or 5 month history of covid models being mostly wrong, sometimes dramatically so.  

 

Having not looked at the details of UoT's models

 

So which models are you going off exactly??  I suggest we look at those—with equal skepticism—and see which prevails.

 

Take a look at them please.

[Daniel Cooper]

I'm not going off any models.  When I predicted that the covid outbreak started at least months before the Chinese said it did, that was based on a knowledge of the history of prior pandemics and the fact that China also has a history of not being truthful about these sorts of things.  

 

Even if China were being forthright, it has been a clear pattern in prior pandemics that once the dust starts to clear it become obvious that the pandemic started sometime before you initially thought it did.  It's just logic.  Whomever your thought was patient zero is very unlikely to have been the actual patient zero.  Likely as not, the real patient zero was asymptomatic or simply didn't get ill enough to go to a hospital, as we know most covid patients not in a high risk category will be.  

 

Also, unless you're talking about models of a well described physical system (for example - transistor models are very accurate), these complex highly interwoven systems are just too susceptible to the modeler's biases.  Even well intentioned modelers are susceptible to letting their biases of how they think a system works creep into the model that they build.  It just goes with the territory.  In a very complex system you can never get all the inputs that actually affect the output and a complete model is many times too computationally burdensome to work with.  So, you have to make simplifying assumptions to reduce the number of inputs to something manageable (or in many cases eliminate inputs that you have no reliable data on) or to reduce the computational burden. At that point you are in the realm of judgement calls.  Is this input important or not? How does this input affect the output? That sort of things.

 

In many cases, you only get a good model after you've watched whatever system you're modeling fully evolve, at which point you may no longer care about the model because you now have the actual data.  All of this is why I'm more enthusiastic about machine learning models, and even those have their issues.  The person setting them up makes a judgement call on what data to expose the ML algorithm to when they train it, and if you leave out something that is actually important in the system your ML model will be wrong as well.  But, at least it is a step in removing the bias of how the modeler thinks a system works. 

[gamesguru]

I'm not going off any models.

 

But, at least it is a step in removing the bias of how the modeler thinks a system works. 

 

Thanks for admitting you're just pulling idea out of your hat while claiming to be the relativity to Newtonian mechanics and being the only camp that is bias-free while also providing only weak speculation in defense of it?

 

It's fine to be critical of models, but please offer up something concrete of your own.  Please confine yourself in the main to those problems in regard to which it possible to say something positive and constructive, since merely negative criticism seems out of place at this point.

 

I mean no pandemic has worked that way, and math suggests increased travel won't accelerate as much as assumed.. just look at H1N1 it was modern, novel, and took multiple years to spread.

[Daniel Cooper]

The increased traffic occurs around normal respiratory flu season and should not be taken as a direct indicator of spread of COVID-19.
 
It's important to keep in mind in the early days of Wuhan the people have absolutely zero awareness of a novel disease, and hence zero mitigation or distancing.  The disease had a R0 > 3 for months with latent period ~7d, probably starting in November.
 
Please don't believe the claims it "started way earlier than that".  These claims are self-contradictory with themselves.  Suppose the latent period is 7 days and R0 is 3, then it doesn't work.  We have to increase R0, but then by this point (8 months later) we should have had it circle the globe twice.. but there are still plenty of new infections in hotspots like New Orleans.  These epidemiological "thinkers" can't have their cake and eat it.
 
These ideas—that it started way earlier and is way more widespread—are coming from guys who just confirm what they want to believe.  It's not real science.  It's not backed up by any evidence or real modeling.  You're being lied to about the lethality and prevalence of a disease we still know little about for purely political reasons.
 
Model built by U of T researchers suggests coronavirus outbreak began in November, has yet to be controlled

 
By the way guru, I went and read the paper (here) and it does not appear that they were trying to determine when the pandemic started, but rather to get a handle on R0 and whether R0 has fallen to 1 or below and the virus is under control.
 
To do that, they assumed the pandemic started in November (they cited genomic based estimates as the basis for that assumption).  Quote from the article:
 

Methods: We developed a simple disease-transmission model in which the 2019-nCoV epidemic was modeled as a branching process starting in mid-November 2019, with a serial interval of 7 days (time between cases) and a basic reproduction number (R0) of 2.3 (new cases from each old case), based on available data and assuming no intervention (Figure 1). The epidemic start date aligned our modeled case counts to point estimates from international case exportation data (4). The model estimated plausible values of the effective reproduction number (Re; reproduction number in the presence of control efforts) after implementation of a quarantine in Wuhan and surrounding areas of China on 24 January 2020 (3) (Figure 1).

So, they were not trying to determine the start date so much as they were trying to determine if R0 was < 1 (pandemic under control). The November start date was an assumption on their part (not an unreasonable one - they had to use something for their model to work). 

 

 

[gamesguru]

Exactly, they cited genomic data on phylogenetic drift indicated the virus likely crossed over in November.  This is corroborated by the timeline predicted by the R0 = 3 curve.

 

Again, not definitive proof, but definitely something highly suggestive of the fact it started in November and a firm establishment of the burden of proof falling on the opposing camp to prove otherwise.  They need to come up with some real data of their own, not just baseless assumptions, that corroborate their view of things.

[Daniel Cooper]

Thanks for admitting you're just pulling idea out of your hat while claiming to be the relativity to Newtonian mechanics and being the only camp that is bias-free while also providing only weak speculation in defense of it?

 

It's fine to be critical of models, but please offer up something concrete of your own.  Please confine yourself in the main to those problems in regard to which it possible to say something positive and constructive, since merely negative criticism seems out of place at this point.

 

I mean no pandemic has worked that way, and math suggests increased travel won't accelerate as much as assumed.. just look at H1N1 it was modern, novel, and took multiple years to spread.

 

Taking multiple years to spread argues in the direction of the virus jumping to man earlier than estimated you understand.  

 

And looking at the examples of prior pandemics is hardly pulling ideas out of my hat. It's not a fact, but it's not based on nothing.  These model predictions on the other hand have been wildly divergent from the actual facts has time has moved forward.  Go look at what the Oxford model was predicting two months ago.

 

You're asking me to offer up something concrete of my own in predicting the future or extrapolating into the past.  What I'm telling you is that there is nothing concrete to be had here.  Not my guesses based on history and not your models.  Just don't grab your preferred model and present its results like they are established fact.  They aren't.  There are any number of models to be had out there.  If I have some issue that I'm trying to "prove" in an argument, I can certainly find a model that will support my position.  I just have to ignore the models that have contrary results.  I have offered up nothing concrete and you have offered up nothing concrete. 

 

We have this tendency to believe that something generated by a computer is "science" and "fact", but running a model that some human thought up on a computer doesn't make it fact just because they used a computer.

Edited by Daniel Cooper, 11 June 2020 - 03:29 PM.

[Daniel Cooper]

Exactly, they cited genomic data on phylogenetic drift indicated the virus likely crossed over in November.  This is corroborated by the timeline predicted by the R0 = 3 curve.

 

Again, not definitive proof, but definitely something highly suggestive of the fact it started in November and a firm establishment of the burden of proof falling on the opposing camp to prove otherwise.  They need to come up with some real data of their own, not just baseless assumptions, that corroborate their view of things.

 

 

And genomic extrapolations are not fact either and they subsequently change all the time.  Look at the genomic extrapolations for when HIV crossed over to humans.  Initially I saw estimates from the 1920s to 1930s.  We now see estimates from the 1890s.  See, those are based on models too and sometimes the models are wrong.  You have to make estimates on the coding error rates when these viruses reproduce and even if you're doing the best you can, you sometimes get it wrong.  And we're talking about a few months of debate at this point.  Did it start in October or November?  Let me assure you that those estimates of genomic shift don't have a four week level of certainty.

 

Are we really arguing whether this started in October or November and is anyone silly enough to think our models have that level of accuracy?

[gamesguru]

Taking multiple years to spread argues in the direction of the virus jumping to man earlier than estimated you understand.  

 

And looking at the examples of prior pandemics is hardly pulling ideas out of my hat. It's not a fact, but it's not based on nothing.  These model predictions on the other hand have been wildly divergent from the actual facts has time has moved forward.  Go look at what the Oxford model was predicting two months ago.

 

I can certainly find a model that will support my position.

 

H1N1 didn't take multiple years to start, just multiple years to run its course and spread to over a third of the population.  It's basically the same as COVID-19 is doing afai can tell.

 

What is the comparison exactly to prior pandemics, and what does it prove?  The Oxford model was based on 18th century science, it was both pessimistic in its unmitigated case and optimistic in its lockdown case.  Please don't go down this egalitarian route that since the 18th century model was flawed all the new MIT, U of T, etc models are also flawed.  It's naive and self-defeating, and it precludes the more sophisticated models from the consideration they deserve.

 

Then do it, make your homework assignment to find some peer-reviewed models that agree with your wild stance that it started in September and the CFR < 0.1%.  I don't buy it.  Fauci says less than half of cases are symptomatic, and the latest antibody studies suggest we are detecting at least 20% of all cases and 80% of all deaths.

[gamesguru]

Let me assure you that those estimates of genomic shift don't have a four week level of certainty.

 

Are we really arguing whether this started in October or November and is anyone silly enough to think our models have that level of accuracy?

 

Yes they did Dan, the relative timescale is much less.  If they were studying in January, a difference of four weeks from November was a 50% error.  That's already greater than the 40% from the HIV estimate in the 80s.

 

We're arguing about September vs November.  Yeah at this point I would be very surprised if the crossover was pushed AT ALL before late, late October.

[Daniel Cooper]

But you were touting the predictions of the Oxford model at one point (must I really go back and quote the posts?).

 

If you knew these were flawed "18th century models" why were you using them? Surely not because they supported your position.

 

Come on, let's at least be intellectually honest here.  I have admitted that my estimates of when this started are my opinion based on history. 

 

 

[Daniel Cooper]

Yes they did Dan, the relative timescale is much less.  If they were studying in January, a difference of four weeks from November was a 50% error.  That's already greater than the 40% from the HIV estimate in the 80s.

 

We're arguing about September vs November.  Yeah at this point I would be very surprised if the crossover was pushed AT ALL before late, late October.

 

You're assuming that we even know all the variants in circulation.  That's rather important when you're extrapolating genomic shifts back to a starting point.  Or that we actually know the error rate when these viruses copy.  I'm going to go out on a limb here and suggest that we don't.  That's what we've seen in the past.  Subsequent analysis will modify that November estimate. By the way, do you know the error bars/confidence interval on that estimate?  Since you didn't know that was where that November start date came from, I'm guessing not.

 

Time and time again I see this.  Models that agree with someone's conclusion are to be treated as gospel.  Models that don't are junk.