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Parameter estimation based synchronization for an epidemic model with application to tuberculosis in Cameroon. (English) Zbl 1238.92037

Summary: We propose a method based on synchronization to identify the parameters and to estimate the underlying variables for an epidemic model from real data. We suggest an adaptive synchronization method based on an observer approach with an effective guidance parameter to update rule design only from real data. In order, to validate the identifiability and estimation results, numerical simulations of a tuberculosis (TB) model using real data of the region of the Center of Cameroon are performed to estimate the parameters and variables. This study shows that some tools of synchronization of nonlinear systems can help to deal with the parameter and state estimation problem in the field of epidemiology. We exploit the close link between mathematical modelling, structural identifiability analysis, synchronization, and parameter estimation to obtain biological insights into the system modelled.

MSC:

92D30 Epidemiology
93B30 System identification
62P10 Applications of statistics to biology and medical sciences; meta analysis
92C60 Medical epidemiology
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