(c) Ted Kaehler 2003 |
Epidemics usually follow S-shaped curves. The predictions here are based on pure exponential growth. When the middle of the S-shaped curve is reached, the rate of infection will slow, and exponential growth predictions will no longer be useful. The reported data shows that the epidemic is still in an exponential growth phase.Via Dave Smith but blogged first by Frank.
Wow - something Squeakily useful.
Now the question is - will this feed go out AGAIN so my comment can be seen by all?
The graph that shows current stats is fabulous... but I didn't see anything on the site that would lead me to belive that Ted (who made the graph) or any of the software developers at squeak have any knowledge about epidmics. I could have made the same graph in excel and made the same claims about millions of deaths within the year... but I don't really know anything about SARS either.
But still, it's scary. Can't really dismiss it, but can't believe it either... what's a boy to do?
Uh oh.
"12 SARS Patients Die in Japan in One Day" ABC News report
I was under the impression that the imperial 99-year lease of Hong Kong ended in 1997 and that the territory had been handed back to China...
Weird. Typo?
Kevin said: "I could have made the same graph in excel and made the same claims about millions of deaths within the year"
Yes, if you assumed that the growth is actually exponential. You might want to have a look at my Worldwide Growth Rate of SARS page. It shows a few different curves fit to the data along with their R-squared correlation coefficients. At this point (up to and including April 23rd data) it looks like exponential is just about the worst fit of all.
Adrian wrote:
> At this point (up to and including April 23rd data) it looks like exponential is just about the worst fit of all.
Not necessarily. It's always possible to come up with 2 parameters "a" and "b" such that "a Exp [b x]" provides a good fit, even for an observed dataset which looks linear.
There's certainly no certainty that the SARS epidemiology follows an exponential pattern, but the fact is that disease transmission dynamics can have an exponential component.
Mathematical models based on infected persons contact graphs -- where the persons are nodes and the relationships are edges -- yield pretty interesting insights. Markov Chain Monte Carlo simulations of random graphs -- encountered e.g. in social network models -- can in fact yield statistical exponential results.
SARS SUX ASS!!!!!!!!!!!!!!!!!