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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References
Janssen, M.A., Martens, W.J.M.: Modeling malaria as a complex adaptive system. Artificial Life 3(3), 213–236 (1997)
Kleinschmidt, I.: Spatial statistical analysis, modelling and mapping of malaria in Africa. PhD thesis, University Basel (2001)
Who Study Group on Malaria. Vector control for malaria and other mosquito borne diseases. Technical Report 857, World Health Organisation (1995)
Casti, J.: Would-Be Worlds. John Wiley & Sons, New York (1997)
Holland, J.: Hidden Order. Addison-Wesley, Reading (1995)
Holland, J.: Emergence. Oxford University Press, Oxford (1998)
Gross, D.: Agent-Based Modelling: An Interdisciplinary Approach. PhD thesis, University of Bergen (2000)
Gross, D., Strand, R.: Can Agent-Based Models Assist Decisions on Large-Scale Practical Problems? A Philosophical Analysis. Complexity 5(5), 26–33 (2000)
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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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