Parameter estimation and real-time prediction of Dengue outbreaks using model averaging (R-3511)

The parameter estimation (Final size of epidemics, turning point, R0) and the real-time predictions of simple and multi-picks dengue outbreaks are treated in several papers using only the Richards model and its variants for multi-picks dengue outbreaks. The aim of the present study is to estimate parameters and to make real-time predictions using several non linear models and carrying out the model averaging to incorporate for model uncertainty in the set of possible non linear sigmoid models. In the case of multi-picks dengue outbreaks a new methodology is created, which is compared with the frequently used in recent paper. The proposed methodology will be apply to 2001 and 2006 simple and multi-picks dengue outbreak data occurred in Cuba. Finally, we will take into account the urban structure of the population, i.e., taking into account transmission within municipalities in a city, extending the non linear model to the setting of non linear mixed effects models.

Keywords:MODELS INFECTIOUS DISEASES

Disciplines:Information and computing sciences, Biological sciences, Computer engineering, information technology and mathematical engineering, Basic sciences, Clinical sciences, Health sciences, Translational sciences