Predicting the spread of epidemics

So we’ve talked about how big data could possibly help us get a better idea of how many people have an illness right now rather than, for example, two weeks ago. Obviously, in an ideal world, however, we’d like to better understand where that epidemic is going to spread to and how bad an outbreak is going to be. Again, this is something which big data and big models can possibly help us with. Now, we know that for a disease to spread between two people, they have to share some kind of proximity, or some element of the environment around them, like a door handle, for example.

So a good model of how a disease is spread is going to have to take into account how many people are near a person we know to be infected. However, people don’t tend to stay still. For example, we all tend to travel to work and back every day, and many of us sometimes travel further afield to other countries, for example, for business reasons, perhaps to see family, or perhaps simply because you want to go on holiday.

Researchers, such as Alex Vepignani and his colleagues, have looked at how we can build models that capture large scale data on how people travel between countries via air, for example, and also large sets of smaller scale data on how we commute in local areas. The results they have to date suggest that integrating this information on how people travel into models of how diseases spread can give us a better idea of where a disease is going to spread to and also how bad the outbreak is going to be. Now, you can imagine that this information is extremely useful for hospitals.

It might be of value for them to work out, for example, whether they need to stock up on a particular kind of medicine or otherwise whether they should reschedule non-urgent operations to free up beds for people we think are going to be affected by this disease. Working out the predictions from these models requires very large computers at this point in time. However, this is something which health authorities around the world are beginning to take into account.