Abstract
Mathematical modelling of the spread of infectious diseases is a well established field with high practical importance. Underlying most analytical approaches is the assumption of “perfect mixing”, that is the idea that the spatial structure of the population can be neglected. This assumption is crucial to the solvability of the models, but can be dropped when using computational models instead of analytical approaches. Using methods from Artificial Life, we investigate under which conditions the perfect mixing assumption becomes a good approximation to describe the spread of vector borne disease in a population with spatial structure.
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© 2004 Springer-Verlag Berlin Heidelberg
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Chu, D., Rowe, J.E. (2004). Spread of Vector Borne Diseases in a Population with Spatial Structure. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_23
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DOI: https://doi.org/10.1007/978-3-540-30217-9_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23092-2
Online ISBN: 978-3-540-30217-9
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