Zombies in Bremen
I modeled a zombie outbreak in the city of Bremen in Germany. The outbreak follows a classic SIR model. SIR models are used to describe disease transmission (or in our case transforming from human to zombie) within a population. The letters stand for:
- S = the number of SUSCEPTIBLE individuals/healthy, still non-infected individuals
- I = the number of INFECTED individuals/number of zombies
- R = if you model the flu, R would stand for RECOVERED individuals. Since you normally can’t recover from turining into a zombie, R stands for REMOVED zombies and describes the number of zombies eliminanted by non-infected individuals
Further, the model included the two parameters beta and gamma. Beta describes the infection rate (how quickly the infection is spreading) and gamma describes zombie death/elimination rate. For the next model I used a beta of 0.3 and a gamma of 0.05 (since not everybody is a natural born zombie hunter)
I placed the patient zero in the city center of Bremen because a crowded place is most likely the starting point of the apocalypse.
Note. I didnt not come up with the model specification myself, but was rather inspired by a cool project you can find here: http://maxberggren.se/2014/11/27/model-of-a-zombie-outbreak/
Spread model
The city center would quickly turn into a zombie stronghold and would no longer be safe.
Visualize the development
In this visualization I set the total population to 569.352 (number of citizens in Bremen 2019). Beta and gamma stayed the same. As we can see after 40 days there is little hope left and the zombies take over entirely. Of course the scenario is rather pessimistic, but otherwise it would only be half as interesting.