Abstract
Although science usually focuses on studying and modelling phenomena known to and observed in the real world, it is arguably worth go get slightly more creative with choosing a research idea—and taking the zombie invasion as a proper research topic may serve as a perfect example. As part of the project, three different models of the zombie invasion, varying in the level of elaborateness and complexity, have been developed from scratch. A feature common for all the models was that they all used density population maps as an “initial condition” and zombie invasions were all visualised based on those maps. That was because one of the core assumptions made by each of the three models was that in more densely populated areas infections tend to spread faster. The general concussion of the project was that the created models could be used to describe extremely fast-spreading diseases, not only caused by zombies, but also more commonly encountered enemies of the humankind like viruses and bacteria.
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Notes
- 1.
We considered zombies not to be bound by the geopolitical difficulties of travelling between Hong Kong and continental China overland, which the ‘ordinary’ people are subject to.
References
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Acknowledgements
Author’s inspiration for considering this research problem was a post on the blog by Max Breggren [1].
The solution to the problem of modelling zombie invasion in the shape described above was obtained during the ECMI Modelling Week 2019 in Grenoble, France, under the supervision of the author of this work. It would not be possible to achieve those results without the group of remarkably hard-working students from all over Europe. The groups members were:
• Alejandro Tobio Pena,
• Alessandro Sfilio,
• Chiara Borsani,
• Miguel Rebocho,
• Sara Costa Faya,
• Simon Li Ying Yin.
The author would like to thank all of them for their cooperativeness and involvement in the project.
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Gruszka, J. (2020). The Zombie Invasion. In: Lindner, E., Micheletti, A., Nunes, C. (eds) Mathematical Modelling in Real Life Problems. Mathematics in Industry(), vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-50388-8_6
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DOI: https://doi.org/10.1007/978-3-030-50388-8_6
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