Welcome to Week Two lecture one of Julia Scientific Computing. So, in this lecture, I discuss the Ebola epidemic of 2014. You might ask yourself, why am I talking about something medical, something social, something that made a lot of news? When we are actually dealing with Julia as a programming language. So, I want to spend some time talking about why we are using this example. It will be the main example for this week and for next week. After this lecture, you will be able to describe the Ebola virus disease. You will be able to outline the time course of the West African EVD epidemic. You'll be able to distinguish the reality of Ebola virus disease from two related things, models of the disease and the available data on the disease. So, what I'm not talking about today in this lecture,is the relationship of this to Julia. So, let me just very briefly motivate why I want an example of this case. It gives us a rich set of tasks to do in Julia. So, this is an example that is a very good context for placing tasks in Julia. There's so many things one can do in Julia that it's a very good thing to just limit yourself to things that are suggested, by a particular contexts such as the Ebola virus disease epidemic. In this week, for instance, you will see how to read and write data, how to write loops, and how to make plots and then once we've got all of that together, we can make a modelling project and see how Julia starts operating when we have something slightly more ambitious and just a few very small functions of you few small plots. So, the particular example that gives us is reached at a task is the outbreak of Ebola virus disease in West Africa 2014. It was a very important event made news and stayed in the news worldwide, almost two years. So, to see it therefore, if we can see that learning Julia will help us understand this important event that helps to motivate us to learn Julia. It's also this particular outbreak is that there is a lot of data that is very easily obtainable, and then the third thing is that being an epidemic, it illustrates many of the things that one can learn about in computing. So, that's introducing our example, let's now turn to the disease itself. So, Ebola virus disease is spread by direct contact with body fluids. Things like flim or snot coming out of the mouth or maybe blood and so on. Here, it is to be direct contact, it has to be I'll get onto the skin and into the mucous membranes of the person who is going to be infected.So airborne particles do not spread the disease. If you get the disease you're likely to get extremely ill, pain, fever, diarrhea, vomiting and so on. Also, unfortunately, pretty likely to die. In the West African epidemic, if the cases were uncreated then something like seven out of ten people who contracted the disease actually died. If they were treated there's still the case that about one out of three died. So, it's a very serious disease you could get it. However, it's not entirely clear how infectious it really is, if you are in daily contact with an ill person you frequently touch them, the cloth, the bed clothes then you are at higher risk. In particular of course, medical personnel do this things all the time and at one stage one in every ten cases were actually the among the medical personnel. This improved as it became clear that precautions have to be taken. So, by the end of the epidemic, the number was not nearly as high as that. On the other hand, if you're just in the presence of you just in the same room as somebody who is ill but you don't touch, you don't touch them you don't touch a bit clothes and so on. Then it appears that you really ain't very much at risk at all. So, people who were in the same room as ill people, and they were writing notes, and just keeping a record of what's going on and never actually touching the things that may have been contaminated by body fluids, they didn't get the disease. So, in West Africa, the epidemic was quite new in 2014 Central Africa 1000 kilometers away from West Africa because Africa is such a big continent. All of the known cases up to 2013 were from Central Africa. Then in 2014, cases were reported from Guinea in West Africa. Eventually, they were traced back to a single child who became ill and died in December of 2013. In all of these three countries, it spread from the small villages into the towns and cities and became a very serious epidemic. So, because a single case of EVD can potentially infect many others. Because it kills so many who gets it, it is a very serious health threat throughout almost the whole of 2014. The number of new cases per week seemed to be just bigger than the number of new cases and the week before the epidemic just seem to be accelerating. So, before we get into exploring this with Julia, I just want to make one very important point. So, Julia can be used to explore the EVD epidemic and in the process, we will illustrate many of the features of the language. In particular, we will be learning how to handle date-time data. We'll be writing fore loops, we will be making plots, we'll be using if statements and we will be using array slicing and user defined functions. So, this is practicing a lot of the features of Julia that you briefly see so in week one and extending that. Then in week three, we will study a particular way of modelling it and then we will be using fore loops more intensively. We will be passing parameters to functions. Eventually, we will able to draw a curve, that fits the data and change the curve in such a way that it actually fits the data better and better just by hand. An eye Julia notebook is a very convenient interactive way of just exploring the data like that. So, you might be thinking that now you have shown really how the epidemic spread because you have a model for it, and please resist that. A model is always far simpler than the real thing. In fact, it is simpler than the data it's fitted to and that is the whole point of a model, because it is simple and can be completely understood. We want to work with a model, but the real world is far more intricate than the data. The data cannot contain the actual social relations act of contacts between people. The role that a traveling from place to place, how far apart the places or maybe there are animals involved. Then, just not in the data the data don't record that. So, the model is actually only talking to the data we have. The model itself is simpler than the data, and the data are much simpler in the real world. So, the model doesn't tell us how the epidemic spread in all details. It gives us some of the features of how the epidemic spread. A good model will give us the important features. So, that's the end of lecture one of week two. Now, let's get on with actually using Julia to understand EVD.
