General Behavior of Infections
Introduction
Problem definition
My semestral paper was on visualization of disease and it´s spreading amongst population. Although there are many models available, most of them are quite straightforward and very simple. Mostly they are concentrating on spreading the disease itself, without any thought places into the surrounding environment, like spread of people. I tried to make the whole system more complex by adding some basic behavior to the agents as well as more variables, by which is the infection defined. This creates a more complex insight into the way of spreading infections. At least to better extend than most models.
Note: I have do add, that the model is far from my liking actually. It still lacks complexity I would like to see and implement. That is partly due to problem with speed. Although simulating 10 000 agents with relatively simple behavior is possible, by adding more and more complex behavior, the whole system started to slow down considerably (I ended with one tick per 30 seconds which is not exactly ideal state for simulating).
How does it work?
There are two main modules. One take care of logic behind moving of agents and the other one is for infection spread. Although for easier navigation they are split into more files. The whole model consist of breed of agents called people. Patches have attributes, that tells agent, if they are inside city, village or out in country side. People have various decisions how to move. Mostly they move around in either country side, villages or cities. When they are in city, there is very big chance, that they stay inside the city. This simulates behavior, that we stay inside city, work and life here and occasionally venture out. Same goes for villages, but to a smaller degree, as the size of villages are smaller. Once in a while (when WILL to go out is bigger than randomly generated number), agent venture out to a randomly generated coordination. After he reaches it, he goes via the shortest way back where he came from.
Model
Globals: Chance to infect x
Agents: People Centers
Variables: Number of people Number of cities Number of infected population in % Chance to cure
