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Uncertainty Quantification for Meningococcus B Carriers Prediction

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Bioinformatics and Biomedical Engineering (IWBBIO 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10209))

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Abstract

Competition among the different classes of genogroups of meningococcal and further bacteria takes place in the ecosystem they constitute within the human body environment. To the best of our knowledge, most of the epidemiological models neglect competition that could highly influence the dynamics of the meningococcal as well as its outbreak. In this paper, we propose a susceptible-carrier-susceptilbe epidemiological model in order to describe the evolution of the percentage of carriers in the population over the time. Moreover, we introduce a competition model to study the dynamics of the meningococcal genogroups in Spain among the carriers. As we are just interested in the meningococcus B, the latter model considers two subpopulations, meningococcal genogroup B and the rest. Both models depend on a number of parameters that are adjusted using real data from the distribution of the genogroups in Spain in years 2011 and 2012. Since these data survey contain sample errors, we further quantify the uncertainties associated to the model parameters taking advantage of a probabilistic fitting method that has been recently proposed by some of the authors. This allows us to give a probabilistic prediction for the evolution of the carriers of the two genogroup over the next few years by constructing a \(95\%\) confidence interval for the percentage of carriers of meningococcus B.

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Acknowledgements

This work has been partially supported by the Ministerio de Economía y Competitividad grant MTM2013-41765-P and the FIS grant PI13/01459. We also acknowledge Dr. Julio Vázquez from the Carlos III Institute of Health for providing the meningococcal data used in this work.

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Correspondence to Rafael J. Villanueva .

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Acedo, L., Burgos, C., Cortés, JC., Villanueva, R.J. (2017). Uncertainty Quantification for Meningococcus B Carriers Prediction. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_50

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  • DOI: https://doi.org/10.1007/978-3-319-56154-7_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56153-0

  • Online ISBN: 978-3-319-56154-7

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