Travel and Disease

This blog post is mainly allowing me to put together ideas and research I have found, and to make sure I understand the concepts I will be talking about tomorrow at my schools Biology Discussion Group (BDG) however I thought it was an interesting topic. The biology discussion group from my school meets fortnightly to discuss scientific and ethical topics. In preparation for our session tomorrow, I have been reading up on ‘travel and disease’ which is this weeks topic. I can’t say it’s something I had given much thought to before trying to find some articles to read for this weeks discussion, however, the way epidemics are now predicted is somewhat fascinating.

I always believed that diseases spread from country to country through an infected person jumping on an aeroplane, train or bus to go on holiday. Thus, I thought that if you wanted to predict the spread of a disease, you would look at how many people from one country travelled to another, and how many of those individuals were likely to be infected. Take the Zika Virus, if lots of people were to travel to Rio for the olympics, I would have thought it would spread quickly as each athlete or spectator returned home potentially carrying the disease. I have found however, that it is much more than this.

How quickly a disease can spread depends on two factors – population distribution and human-mobility networks [1]. Thus in a sense, I guess my initial theories were half right. How easy it is for a person to move from place to place is a factor. Consequently, it is not if one person travels from one country to another, but how many people they meet along the way. If an infected person walks into a shop, you then have to consider how busy the shop is likely to be at that time, and how many people the shopkeeper is likely to encounter between the time of infection and the time at which they are potentially unable to work anymore (say at diagnosis). Similarly, if an infected person sneezes on a £10 note and that therefore becomes infected, how many people are likely to encounter that note until it is no longer infectious? The contact goes on and on.

Here are some key points to consider when modelling epidemics:

  • Modern pandemics spread more quickly and less uniformly than those in the past e.g. The Plague. Why? Due to the global air transportation network and and the complex, integrated nature of much of our society.
  • To model the spread of an infectious disease, you must take into account the biological and physical principles alongside social and behavioural factors.

Therefore, what the spread of disease comes down to is actually very minimally air time, but in fact human behaviour. If you know what a population is likely to do, i.e. how many different people may encounter another in a day, the spread of disease is much easier to predict. The more research into human behaviour there is, the more likely it is that we are able to predict the spread of disease accurately [1].

Similarly, a disease is not going to spread across the entire world or even Europe, at the same rate. It may spread between certain cities or countries quickly due to large amounts of human mobility networks and an interactive society. Yet for others, there may be very little contact between two cities and very few people may move from one to the other, meaning that disease would likely spread at a very slow rate.  So, this theory doesn’t work unless we move from analysing small social groups in individual towns or cities, to analysing social aggregate states made up of millions of people [1] – in order to gain a mean activity.

The problems we face with this is that people’s lives are essentially non-conformal. Not everyone does the same thing every day, and each person has their own agenda. As a result of this, standard deviations (the spread of data) are typically extremely large, and there are no typical values for many of the quantities – e.g. the amount of times a person eats out a week.

Consequently, predicting epidemics is no easy feat. There are so many factors to include that it is very rare we will be able to pinpoint the exact spread of a disease. Having said that, techniques allowed scientists to predict the peak in the swine flu pandemic in the USA between late October and November 2009. Whats to learn from this? That the spread of disease is largely due to human behaviour, and that in understanding more of human behaviour we could open many doors to new methods of predicting pandemics and epidemics.

[1] The Flu Fighters – Physics World  – as of February 2010

I will link the podcast to this BDG session here once it has been edited 🙂 

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