Additionally, notice that the orange data points (actual hospitalizations) are significantly under the "With Intervention" plot. So why even include the slide? Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks.
Not a good sign if people are making actual decisions based on this.
> Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks.
I feel like I’m taking crazy pills with the way people are talking about this whole thing still being out of control, when data shows the situation is even better than the most optimistic models were predicting. And by that I mean, pretend I was on HN 3 weeks ago predicting 25K deaths in the USA by today. I’d have been downvoted into oblivion and told I was delusional. But here we are.
Clearly NYC was hit far harder than the rest of the country, but it seems like every state and municipality is simply basing their models on NYC case numbers scaled by population. I don’t get it.
I don't understand what you're suggesting, that California should ease up faster? It seems to me that reality being better than models had predicted is more the result of everyone flying blind due to lack of testing... California has probably been lucky that it turned out its infection was lower than New York's turned out to be. It is just hard to make a model starting from extremely shitty and noisy base data about facts on the ground, but someone still has to make very difficult public health decisions based on the best models available.
> I feel like I’m taking crazy pills with the way people are talking about this whole thing still being out of control
A week ago, I remember reading how the Bay Area was bracing for a bracing for a surge and it was the calm before the storm. The Santa Clara county covid-19 dashboard told a different story: day-over-day, new cases were roughly the same for the past two weeks. 2+ weeks into the lockdown, there was obviously no surge coming.
I think there was genuine concern that the quarantine as implemented would not be enough. You can see lots of stories locally wherever you are about how people aren't obeying the order. Italy was still in a lot of trouble despite having had some quarantine measures in place. Hindsight shows the quarantine was effective enough to get numbers down. The US, despite reacting too late, did lockdown fully relatively quickly.
I would agree that modeling after NYC seems like a bad idea given the lack of density and public transportation. On the other hand, Michigan looked pretty exponential, and as the lagging cases came in from other states, they also began to look fairly exponential as well. Despite cases staying elevated for now, the exponential growth has died down.
The US missed the worst of hospitals being overrun and it running away in multiple cities.
The IHME model is proving to be wildly inaccurate on the downslope due to bad data coming out China. Their projections will continue to creep up in terms of deaths over the next few weeks because the predicted drop offs won’t be happening, sad to say.
If you want to see examples, check out their predictions on Italy. Their figures have been underestimating by over 50%, and the gaps will widen each day over the upcoming week. Heck, the ranges for the last few days have been outside their confidence interval.
I think the point of the plot is to suggest that intervention efforts are being quite successful relative to expectations at the time the "With Intervention" model was generated.
The brighter dashed line is there to show what happens if intervention is disabled completely.
I really like that the milestones are placed as questions, rather than dates. It is the right way to message the unknown.
This is ridiculous criticism. There are so many unknowns with this virus. We don’t know how many people have it, how fast it is spreading or what the mortality rate. Everything is a fairly rough estimate.
It turns out that social distancing is working better than expected, or the virus isn’t as contagious as expected, or slightly less severe than expected. That doesn’t mean the lockdown was the wrong thing to do, or that it isn’t still necessary. What it does mean is that we’ll be able to start easing restrictions as the hospitalizations continue to drop — and perhaps we can stop it completely with testing and contact tracing.
The line is the average of high and low estimates. The issue we are dealing with exponential growth so 1/10th x to 10x makes it look like the estimate is wildly off even when it’s surprisingly accurate.
Further, these estimates are much older than the data so showing their accuracy is useful.
xienze|5 years ago
I feel like I’m taking crazy pills with the way people are talking about this whole thing still being out of control, when data shows the situation is even better than the most optimistic models were predicting. And by that I mean, pretend I was on HN 3 weeks ago predicting 25K deaths in the USA by today. I’d have been downvoted into oblivion and told I was delusional. But here we are.
Clearly NYC was hit far harder than the rest of the country, but it seems like every state and municipality is simply basing their models on NYC case numbers scaled by population. I don’t get it.
ridaj|5 years ago
dehrmann|5 years ago
A week ago, I remember reading how the Bay Area was bracing for a bracing for a surge and it was the calm before the storm. The Santa Clara county covid-19 dashboard told a different story: day-over-day, new cases were roughly the same for the past two weeks. 2+ weeks into the lockdown, there was obviously no surge coming.
https://i.imgur.com/LrFZj3S.png
Looking at that chart on the April 7th, nothing pointed to a surge.
altcognito|5 years ago
I would agree that modeling after NYC seems like a bad idea given the lack of density and public transportation. On the other hand, Michigan looked pretty exponential, and as the lagging cases came in from other states, they also began to look fairly exponential as well. Despite cases staying elevated for now, the exponential growth has died down.
The US missed the worst of hospitals being overrun and it running away in multiple cities.
throwaway237683|5 years ago
[deleted]
glaugh|5 years ago
This shows laudable transparency, in my view.
(Also the model was directionally correct, it’s not like it was entirely the wrong shape.)
[1] https://covid19.healthdata.org/united-states-of-america/cali...
wjossey|5 years ago
If you want to see examples, check out their predictions on Italy. Their figures have been underestimating by over 50%, and the gaps will widen each day over the upcoming week. Heck, the ranges for the last few days have been outside their confidence interval.
jf22|5 years ago
Do you have a background in disease modeling or anything?
I'm curious.
ISL|5 years ago
The brighter dashed line is there to show what happens if intervention is disabled completely.
I really like that the milestones are placed as questions, rather than dates. It is the right way to message the unknown.
empath75|5 years ago
It turns out that social distancing is working better than expected, or the virus isn’t as contagious as expected, or slightly less severe than expected. That doesn’t mean the lockdown was the wrong thing to do, or that it isn’t still necessary. What it does mean is that we’ll be able to start easing restrictions as the hospitalizations continue to drop — and perhaps we can stop it completely with testing and contact tracing.
mikekij|5 years ago
dehrmann|5 years ago
It's pretty sloppy to show surge capacity on the same graph as total hospitalizations, not active active hospitalizations.
Retric|5 years ago
Further, these estimates are much older than the data so showing their accuracy is useful.