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Adaptive movement strategies in cyclic games during an epidemic

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MMVW04 - Modelling non-Markov Movement Processes

We simulate a cyclic game system where organisms face an epidemic beyond being threatened by natural enemies. To survive, individuals of one out of the species usually safeguard themselves by approaching the enemies of their enemies and performing social distancing to escape contamination when an outbreak affects the neighborhood. We explore the impact of pathogen mutation which alters disease virulence in the organisms’ daptability to local disease outbreaks. We quantify the changes of individuals’ spatial organization, and species populations. Finally, we find how organisms adapt to minimize the chances of being infected and dying due to disease complications. Our results help biologists and data scientists to understand how adaptive processes can affect population dynamics in complex systems.

This talk is part of the Isaac Newton Institute Seminar Series series.

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