Hi Tom, are you running more recent code published in this blog? -

Modeling a Pandemic like Ebola with the Wolfram Language

Some elements of the code set up and timings were improved there. The notebook is attached at the end of the blog. On the machines used in the blog it does not take more than 250 seconds. Speedup beyond that is limited by large data size. Perhaps Marco also has some ideas or timings.

Cheers, Vitaliy

It is because you are making that many runs to W|A servers as you have cities: each EntityValue in Map will run to the servers for every city. This is the way to make a single run for all cities:

EntityValue[CityData[{All, "Nigeria"}], "Name"]

In the blog you can see the same method in In[64] and In[69].

Here there is a useful theoretical view on the problem, it doesn't use Mathematica to simulate it but basic differential equation integration systems.

Hi Theresa,

here are the lines that you would have to execute.

First you define the equations:

sus[i_] := sus[i] = sus[i - 1] - rho sus[i - 1] inf[i - 1];
inf[i_] := inf[i] = inf[i - 1] + rho sus[i - 1] inf[i - 1] - lambda inf[i - 1];
rec[i_] := rec[i] = rec[i - 1] + lambda inf[i - 1];

These are difference equations. Next you need to define the parameters and the initial state, i.e. how many infected, recovered and susceptible there are at time 1.

sus[1] = 0.95; inf[1] = 0.05; rec[1] = 0; rho = 0.2; lambda = 0.1;

The actual calculation is done like this:

tcourse = Table[{sus[i], inf[i], rec[i]}, {i, 1, 100}];

Last but not least you want to plot everything:

ListPlot[Transpose[tcourse]]

That is it. You can, of course, put everything into one cell. The respective notebook is attached for your convenience.

Cheers,

Marco

Attachments:

Related article in Nature today, http://www.nature.com/news/ebola-by-the-numbers-the-size-spread-and-cost-of-an-outbreak-1.16144

There is an interesting related article:

’1 in 5 chance’ Ebola will spread to the US in September

with a few striking visualizations:

Air traffic connections from West African countries to the rest of the world (credit: PLOS Currents: Outbreaks)

This data visualization, updated today (Sept. 10), shows the actual trends of total number of cases (4,269 as of Sept. 5 — WHO) and the prediction of cases for the next six weeks in the current Ebola virus disease outbreak ( credit: Health Intelligence, http://healthintelligence.drupalgardens.com )

Dear Marco,

I must say the post is excellent - thank you very much for spending time and writing this up. That was me who asked and then deleted the question. I was just curious about visualizations and the conclusions we can derive from them. Your descriptive text was very brief - I just wanted to understand more details.

I also would like to bring to your attention that post most probably was viral for a few days after you published it - judging by ~ 10K views it gathered over the weekend. Here are some discussions of it on popular media:

Hacker News

Reddit

Discussions there sometimes are very frank and noisy but perhaps there are some grains of useful information too. If you plan an update you may wanna take a look at those for a feedback. And here is how many Twitter accounts your post have reached:

Ups, really sorry. You are absolutely right. I guess that there is no point in blaming auto-correct. My bad. I meant disadvantage.

Thanks for reading that embarrassingly long article and commenting, Marco

PS: I'll post an update some time later. There was a question/reply earlier on, but apparently it has disappeared.