In jest, I am imagining a bunch of data scientists working late into the night, running the numbers and various scenarios, and then one person finally stands up and says, "FK it, let's just shut down the whole country and hope for the best."
Why it’s so hard to make a good Covid-19 model
21–30 of 96 posts
Re: Why it’s so hard to make a good Covid-19 model
#22The article is a long listing of ways to say GIGO. It's hard to get good clean accurate data.
GIGO is a principle i learned at audio engineering school and it applies to all input/output relationships across multiple disciplines.
Have a 4k tv but only a 1080 cable box? Your tv will only show 1080.
Did you record too much compression on the master track? Now you have to deal with that in the mix.
GIGO is any time you get an input that will never give a desired or expected output. In circuits, its easy. It works or it doesn’t. In data science, GIGO can be hidden by hiding the assumptions made to reach the level of knowable information from the data provided.
Data scientists have a huge uphill battle right now. It is far more complex than looking at the numbers and trying to find patterns. People can find patterns in clouds.
Re: Why it’s so hard to make a good Covid-19 model
#23Good luck trying to predict how much of a population is going to refuse to isolate and interact anyway.
Also relies on governments and politicians to not fudge testing and death counts, which is never going to be accurate.
btw the financial times has maybe the best graph on the stats however flawed:
http://com.ft.imagepublish.upp-prod-us.s3.amazonaws.com/2251...
Re: Why it’s so hard to make a good Covid-19 model
#24Its 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 fatalities, but even then its because its based on mostly hard data (unless its china...)
Re: Why it’s so hard to make a good Covid-19 model
#25What 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…
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Re: Why it’s so hard to make a good Covid-19 model
#26Earlier quoted context omitted.
It's like trying to calculate the Butterfly Effect during winter at the Reserva de la Biosfera Mariposa Monarca (Monarch Butterfly Biosphere Reserve). https://en.wikipedia.org/wiki/Butterfly_effect https://en.wikipedia.org/wiki/Monarch_Butterfly_Biosphere_Re...
I don't think it is - I think you can write "x is like y" but you have to understand and explain why. Otherwise I can say "a hippo is like a bright blue sky" and then claim that I am right! I don't think that this is like modelling the impact of a butterfly on storms - I think this is more like modelling the diffusion of a bottle of dye in a swimming pool.
Grandparent is somewhat nonsensical, but I think what they were trying to say is that since human society is a highly dynamical system, it's not really possible to have a highly accurate model to represent how COVID-19 is going to spread. The best we can do is use naive models and plan around worst-case scenarios.
Re: Why it’s so hard to make a good Covid-19 model
#27Earlier quoted context omitted.
>the models themselves are so simplified that they can't capture much of the important dynamics going on That isn't my (outsider) understanding, could you provide a reference? By reference I mean a recent survey that demonstrates the specific limitations? My understanding of the Imperial College model is that it uses a 30m*30m grid of the world and the expected people in the world and various additions to simulate sc…
30m is quite a lot bigger than the Planck length, and you can’t predict human behavior by playing The Sims.
you can predict human behavior with big data and linear models/embeddings with a few billion parameters. This works so unbelievably well, I expect that eventually health modelling folks will do this, provided they have enough high quality data.
Re: Why it’s so hard to make a good Covid-19 model
#28What 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…
Agree. I think a better exposition on COVID-19 models is Zenep Tufecki's article in The Atlantic [1]. TLDR: They're more directional roadmaps, showing you which possible outcome paths you need to prune off the tree of outcomes, not exact numerical predictions. [1] https://www.theatlantic.com/technology/archive/2020/04/coron...
In a sense, much of this work is similar to A* search and reinforcement learning. You have a limited view of the world, the responses to your actions are not directly causal, but if you can use the data you have to make reasoned decisions on what parts of the (extremely large) action space are unlikely to pay off, you can avoid wasting resources on them.
Re: Why it’s so hard to make a good Covid-19 model
#29What about our models for global warming?
The thing with climate is that you don't need to believe in the forecast. You could just look at the PAST results. Let's say just the last 10 years. And compare that to the last 200 years. May be that will teach you that something is going wrong and not going in the right direction.
Re: Why it’s so hard to make a good Covid-19 model
#30Best article I've read through this entire Pandemic.