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Why it’s so hard to make a good Covid-19 model

fivethirtyeight.com

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Re: Why it’s so hard to make a good Covid-19 model

#71

Post by dragontamer »

watwut wrote: post #48
mikorym wrote: post #39

Earlier quoted context omitted.

There is another point too, which also to some extend goes against your point—that we model epidemiology in standard ways, and that in order to use those standard ways we need the parameters in the set of differential equations. And these do make predictions based on the equilibria. I am not saying they solve everything, but they are routinely used to for example calculate how many people need to be vaccinated to sto…

R_0 changes as people change their behavior. It is not one constant common to all places and times with virus. Edit: people down voting this, please look at definition and those papers. R_0 does changes.

Even without changing behavior, R0 can change as a virus enters different conditions. The flu in the winter (aka: Flu season) has higher R0 than the flu in the summer. Even if all humans acted the same in both cases.

R0 is assumed to be a constant so that the math / models work. But it really changes dramatically in practice. Maybe someone else will eventually make a model where the constant is more... constant. But until then, we will continue to use this model.

Re: Why it’s so hard to make a good Covid-19 model

#72

Post by m0zg »

macintux wrote: post #70
m0zg wrote: post #65

Earlier quoted context omitted.

So what you're saying is Donald Trump saved 2 million lives, then? :-) I think once we're through this, you will see that there wouldn't be 2 million deaths no matter what, although the measures did help, of course. The current IHME models get routinely revised downward by a lot (to 1/3-1/4th the initial figures) even though _they assumed "measures" right from the start_. As of this morning, the projected fatalities…

I don’t know that anyone expected (nearly) every state to impose a stay-at-home order. Crashing our economy into a brick wall is not an easy decision. I frankly expected things to get much worse before state governments took action. Obviously we could have done much better, much sooner, but I certainly can believe why early estimates were much more pessimistic. And that’s all disregarding the fact that we still don’t…

> I don’t know that anyone expected (nearly) every state to impose a stay-at-home order.

IHME model did. And it still overestimated (and continues to overestimate) by a lot. What it predicted initially isn't even observed in countries where there's no lockdown at all.

Re: Why it’s so hard to make a good Covid-19 model

#73

Post by coronqueue »

dragontamer wrote: post #71
watwut wrote: post #48

Earlier quoted context omitted.

R_0 changes as people change their behavior. It is not one constant common to all places and times with virus. Edit: people down voting this, please look at definition and those papers. R_0 does changes.

Even without changing behavior, R0 can change as a virus enters different conditions. The flu in the winter (aka: Flu season) has higher R0 than the flu in the summer. Even if all humans acted the same in both cases. R0 is assumed to be a constant so that the math / models work. But it really changes dramatically in practice. Maybe someone else will eventually make a model where the constant is more... constant. But…

How certain of this are we (for the flu)?

When I've looked into it, I've found it difficult to assess the degree to which we are looking at "behavior changes between seasons" vs "the season matters".

Reasons the season might matter: Thicker air (higher humidity) may reduce particulate spread. Viral lifespan may be different under different temperatures.

Yet, in researching the issue, I tend to find things like "well, in animal models, this is what we've seen". Or "we think the heat reduces the effectiveness of a protective membrane that the flu uses".

Despite some effort, I've not found sources that both (1) seem reliable, and (2) provide a clear/concise understanding of what we know and why/how we think we know these things.

Re: Why it’s so hard to make a good Covid-19 model

#75

Post by wahern »

Thrymr wrote: post #10

What this article misses is that simple models of complex systems in science are most useful for understanding the dynamics of phenomena, not for making accurate quantitative predictions. This is not a model of a mass accelerating in a vacuum where Newton's laws are sufficient to a high degree of accuracy, or even a numerical model of the aerodynamics of an airplane, where the physics are well understood but there ar…

Well said, but it should be noted that making quantitative predictions based on simple models (and scattershot data) of complex systems is FiveThirtyEight's bailiwick and Nate Silver's claim to fame. The subtext of the article is that the problem is so difficult even they are stumped.

Re: Why it’s so hard to make a good Covid-19 model

#77

Post by oehpr »

I've found this topic pretty interesting, and I've enjoyed trying my hand at it myself.

One of the things I've been playing with is Insight Maker https://insightmaker.com/ This site is a totally free platform where you can set up the kinds of simulations this article describes (stock and flow models). You can even specify your uncertainty in your baseline assumptions and run sensitivity analysis to see what the relative impact of each factor is on the model, and the range of potential outputs you could have. This system is very much like https://www.getguesstimate.com/, except much more flexible and way less intuitive.

Insight maker isn't a professional tool, it's really more of an advocacy and outreach platform, but despite that it's really quite powerful.

I think after you've read this article and internalized the difficulties in modeling pandemics (and have re-affirmed to yourself that you are not an epidemiologist, unless you are, more power to you if so), you might have some fun trying to build the model this article describes.

Re: Why it’s so hard to make a good Covid-19 model

#78

Post by lbeltrame »

mcguire wrote: post #53
jefftk wrote: post #9

Note that this article is from March 31st, and while that wouldn't normally be very long ago things are moving extremely quickly.

" Meanwhile, a report from Imperial College London that made headlines for its dire, modeling-based forecasts predicted about 2.2 million U.S. deaths from the coronavirus, if nobody changes their everyday behavior. " On the other hand, they're still quoting that study, which was very out of date well before the 31st.

Do you (or anyone else) have any resources for a critique/comment of that report? I'm interested since I tried reading it and I think I lacked a finer understanding.

Re: Why it’s so hard to make a good Covid-19 model

#79

Post by GoodJokes »

KaiserPro wrote: post #24

Its pretty simple: there isn't any decent data. The data we have is strongly biased to older and sicker people. There is no systematic surveillance of a geographic area, only panic testing of those who are showing symptoms. Until there is sampling of a a borough, city or town, from start to finish, we will have wildly wrong models. The only thing that we can plot reasonably accurately is the exponent of the fatalitie…

Nate silver loves to attempt to make predictions based on shitty data. I can’t think of worse data set than polling.
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