Annals of Computer Science and Information Systems, Volume 11

DOI: http://dx.doi.org/10.15439/2017F264

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 481–484 (2017)

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Abstract. We describe a stochastic method using Dirichlet processes to derive mixture models that allow the numerical description of outbreaks of diseases with multiple sources. We show that existing disease models may be extended using this method and how this may be used in a practical context to support the simulated response to a mass casualty public health emergency.

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