Optimal control and parameter estimation in some epidemiological models

Aziz Belmiloudi (1) , Fabrice Mahé (1)

1 IRMAR - Institut de Recherche Mathématique de Rennes

In real word, experimental data in epidemiology are incomplete, uncertain, or even impossible to product. Therefore, the estimation of parameters and optimal adaptation of model in real process will become difficult tasks. In order to alleviate these difficulties, optimal control strategies (consistent with data measurements) coupled with mathematical modeling and numerical simulation tools, allow to build, to test and to compare theories and hypotheses on the spread/eliminate of infectious diseases. In order to estimate the effectiveness of vaccination, isolation and treatment, and then to devising optimal intervention strategies, we are led to study different models corresponding to different situations. Often, a numerical code, adapted to each situation, is developed. We propose a general formalism allowing to describe many models and thus to simulate, with the same tool, different situations as well as to compare performances and reliability of these models.

Domaines: Analyse numérique [math.NA]; Optimisation et contrôle [math.OC]; Santé publique et épidémiologie

Aziz Belmiloudi, Fabrice Mahé. Optimal control and parameter estimation in some epidemiological models. 21st International Epidemiological Association World Congress of Epidemiology (WCE 2017), Aug 2017, Saitama, Japan. ⟨hal-01835439⟩