We are looking into the broken links issue. Thank you for reporting this.

Is the information on the number of cases per ‘date of onset of illness’ as published in:
http://www.cdc.gov/mmwr/PDF/wk/mm5817.pdf
been used to produce these maps? Or rather the total number of confirmed cases per country?

I also hope that some of this work is in conjunction with other complexity modeling and simulation at IU - of which I almost became a part.

However, any mathematical model - nor matter how accurate or well designed - is only as good as the data that is being fed into it. Unfortunately, the data you guys are getting is poor for three reasons. First, the nature of this disease is such that it is virtually indistinguishable from regular seasonal flu (at least, in the early stages), which means that there may be more sick people running around the world than what the governments and health authorities are actually telling us. Second, it is almost pointless to go by the number of confirmed cases, as the WHO is dreadfully slow and inconsistent in the way they handle the ‘backlogs’. Third, some health authorities are now suggesting that up to one third of the carriers may not even show symptoms at all - but can still infect others (though whether that is true remains to be seen). To add to the confusion, the Mexican government has (for better or worse) ceased reporting new cases of infection entirely, so your data may become even staler than it already is.

So as a fellow researcher who makes a living out of publishing prediction data, but has to live with the not-so-pleasant consequence of getting it wrong (which happens from time to time, nobody is perfect!), my suggestion is this: perhaps you can run a scenario analysis based on different sets initial conditions, with the base case scenario being the official data provided by health authorities. The worst case might assume some sort of multiplier to the reported cases (say, ten times). I understand that this doesn’t sound as exciting as making statements like ‘our calculation shows xx infections by May 17th’, but it’s virtually impossible to make any kind of single point prediction with any degree of accuracy. At the very least, the scenario simulations will allow us to get a better feel for the degree of perbutation based on different sets of initial conditions.

As I mentioned earlier, I do think your team is on to something, and regardless of some of the nasty comments you’ve been getting on this post (it’s normal, everyone’s a critic!) , this project provides valuable insight for the public who is being kept in the dark - as they often are at times like this. I am not sure how long it takes for you to run your models, but my opinion is that an extra bit of information will go a long way in adding value to your hard work.

Again, thanks for your great work, and I look forward to seeing any sort of scenario analysis results.