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8 février 2022


Panayiota Touloupou (University of Birmingham) - Séminaire commun GAINS-LMM

Titre: Scalable Inference for epidemic models with individual level data.

Webinar - 8 février 2022

Résumé :

Motivated by this demand, we construct a model that incorporates this additional information regarding the strains in which the bacterium appears and propose a statistical algorithm for inference. The model improves upon existing methods in the sense that it allows for both imperfect diagnostic test sensitivities and strain misclassification. Extensive simulation studies are conducted in order to assess the performance of our method, while the utility of the developed methodology is demonstrated on data obtained from a longitudinal study of Escherichia coli O157:H7 in feedlot cattle in which 8 competing strains were identified using genetic typing methods. We show that surprisingly little genetic data is needed to produce a probabilistic reconstruction of the epidemic trajectories, despite some possibility of misclassification in the genetic typing. We believe that this complex model, capturing the interactions between strains, would not have been able to be fitted using existing methodologies.


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