When Zombies Attack: Abstract

When Zombies Attack!: Mathematical Modelling of an Outbreak of Zombie Infection

(Abstract)

A sweet zombie love story

The purpose of this paper is to develop a mathematical model of an outbreak of zombie infection. To simplify the model, this paper only considers popular-culture zombies, which are slow, cannibalistic and undead.
In order to simulate the possible outcomes of a zombie outbreak, five different models were set up. The basic model distinguishes three classes: the susceptible, the removed and the zombies. According to this model, zombies are likely to infect everyone and the collapse of human civilization cannot be avoided. The model with latent infection includes a new class of the infected. The outcome of this scenario is that zombies take over, though it takes them twice as long as without the infection phase. A quarantined area was added to the next model, keeping away the infected and the zombies from humans. This model points out that though the quarantine delays the eradication of humans, it cannot stop it. In the next model the quarantine was substituted by a treatment, in which treated zombies become susceptible humans again. In this case humans are not wiped out but only exist in small numbers. The last model is called impulsive eradication, which seems to be the ultimate solution against zombies. The theory suggests that frequent and powerful attacks on zombies can lead to their eradication in ten days.
The paper suggests that extremely aggressive tactics have to be employed against zombies to avoid the collapse of human civilization. However, it was pointed out that this strategy is only effective provided the outbreak happens quickly. Otherwise, due to the birth and death rates zombies have limitless supply of new human bodies to infect.
This paper is the first mathematical analysis of an outbreak of zombie infection. Although the scenario depicted is not realistic, it is useful to have mathematical models for unusual events. This paper can prove that mathematical modelling can be flexible and helpful towards answering biological challenges.


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