Slashdot Mirror
Sim Epidemic
Dotnaught writes "Scientific American has an intriguing story about EpiSims, an outbreak simulator. Designed by Los Alamos National Laboratory (LANL), it deals with a social networking of a different sort: 'To understand what a social network really is and how it can be used for epidemiology, imagine the daily activities and contacts of a single hypothetical adult, Ann. She has short brushes with family members during breakfast and then with other commuters or carpoolers on her way to work. Depending on her job, she might meet dozens of people at work, with each encounter having a different duration, proximity and purpose.'"
I read an article in Popular Science a few months ago while waiting in the dentist office about a similar program developed by CERN. The main difference was that it was text based instead graphical. The coolest thing I saw about it was that they used it to re-enact the spread of the bubonic plaguge which killed so many people years ago. I think they were developing it for WHO and the associated organizations.
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Some more amusing ways to torture my Sims.
For a minute there, I thought this article was going to be about how millions of teenage girls are displaying frightening symptoms: siting inside all day instead of socializing, playing computer games all day, turning away from reality. I guess the Sims has the power to turn girls into guys. But that's not what this is about...
A friend of mine works with the WHO which has solicited many different people to do work like this for them. In light of all the terrorism talk and threats of bio-terrorism, we've had talks on this. Different universities etc. The problem with it is that no model is able to conform to historical records of various outbreaks well enough across the board to develop policy on. One model is highly based on an aids breakout of the 1980s or an asian flu epidemic, and the model fits well to it. But when the model is applied to different epidemics they don't work out. There are just so many factors differing by area, culture etc. Think close knit community vs big city. Also the way things are transmitted. You would have to have a different model for each scenario which is very difficult/costly. Until we can predict everything going into a situation these models aren't very useful.
Models working with more people is definitely a step forward, but just an improvement.
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To understand what a social network really is and how it can be used for epidemiology, imagine the daily activities and contacts of a single hypothetical adult, Ann....
Of course, this is slashdot. If Ann was a slashdotter, her epidemiology would consist only of contact between Ann and her parents, at the dinner table, during the approximately 45 minutes per day that Ann leaves the cellar.
Perhaps it should read something like:
To understand what a social network really is and how it can be used for epidemiology, one must not be a slashdotter. Imagine the daily activities and contacts of a single hypothetical adult, Ann....
I have no problem with your religion until you decide it's reason to deprive others of the truth.
Sounds a little like the Zombie Infection Simulator.
A tool like this could be adapted for some other fascinating uses:
Marketing (particularly the viral type)
Political meme simulation
Catching terrorists and other criminals through investigating their social linkage
Pharmacological demand forecasting
All technology has alternate uses - some good, some not...
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... till they come out with the "gay bathhouse" mod pack.
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It's the end of my comment as I know it and I feel fine.
After all, it is basically a "WHO's on first" post.
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It's the end of my comment as I know it and I feel fine.
First off, here's a link to the EpiSims site at Los Alamos National Labs. They have a neat (250 meg) video showing smallprox propagation, as well as several graphs.
Here's a link to the general web page at LANL for Dynamic Simulation Science, which also includes information on things like simulation of transportation networks.
A google scholar search turns up a few interesting-looking research papers:
Structural and Algorithmic Aspects of Massive Social Networks (Eubank et al, 2004)
Understanding Large-Scale Social and Infrastructure Networks: ASimulation-Based Approach (Barrett et al)
BioWar: A City-Scale Multi-Agent Network Model of Weaponized Biological Attacks
19.35 - You are in your parents basement. It's very dark. You are likely to be eaten by a grue.
'up'
19.40 - You are in your parents hall. You hear voices to the east.
'east'
19.45 - The room is full of people. You are likely to catch the plague.
'mingle'
19.50 - Your aunt kisses you.
'use handkerchief'
19.55 - You feel dizzy
'South'
20.00 - You are in the kitchen. You have caught the plague. You feel very hot.
'South'
20.05 - You are in the garden. You are dead.
The real cause for concern is not Ann, the typical adult, but Bob, the traveling salesman. Bob comes into contact with hundreds of people spread across a wide area. Bob can give the infection to client sin remote sites and airline passengers. Worse, Bob will give the disease to hotel and airline workers (who spread it to other "Bob"s that travel).
The connectivity of people lies on a 2-D spectrum of distance and numerousity. Highly connected, highly-travelled people will play a much greater role in spreading the disease than typically-connected, less mobile people. Given the incubation delay and delays in reporting of an epidemic, the Bobs of the world will have done their damage long before the government realizes the danger and closes the airports.
Two wrongs don't make a right, but three lefts do.