How to predict an epidemic of Zika virus?
A challenge in nonlinear stochastic dynamics!
Americo Cunha (IME-UERJ)
Several instances of Zika virus epidemic have been reported around the world in the last 20 years, causing Zika fever to become a disease of international concern. In this context the use of mathematical models for epidemics is of great importance, since they are useful tools to study the underlying outbreak numbers and allow one to test the effectiveness of different strategies used to combat the associated diseases. This work deals with the development of an epidemic model to predict the evolution of Zika virus in Brazilian scenario and the posterior calibration of this predictive tool with respect to real data, from the recent outbreak of the disease, by solving an inverse problem. Model parameters variabilities are taken into account through a parametric probabilistic approach that employs an information-theoretic formalism (maximum entropy principle) to construct a consistent stochastic model and uses Monte Carlo simulation for propagating the uncertainties. This development gives rise to a realistic epidemic model, capable of making robust predictions about epidemic scenarios.