A computational procedure to capture the data uncertainty in a model calibration: the case of the estimation of the effectivenes of the influenza vaccine

In this paper we propose a technique to estimate the ef- fectiveness of the influenza vaccine. The effectiveness of the vaccine is estimated every year, when the influenza season has finished, analyzing samples of a high number of patients in the emergency departments of the hospitals, and this makes it very expensive.
To do so, our proposal consists of a difference equations model that simulates the transmission dynamics of the influenza where the vaccine effectiveness is included as a parameter to be determined. The proposed technique will calibrate the model parameters taking into account the uncertainty of the data provided from reported cases of influenza. The calibration will return an estimation of the vaccine effectiveness with a 95% confidence interval.