Parameter estimation of some epidemic models. The case of recurrent epidemics caused by respiratory syncytial virus.
The research presented in this paper addresses the problem of fitting a mathematical model to epidemic data. We propose an implementation of the Landweber iteration to solve locally the arising parameter estimation problem. The epidemic models considered consist of suitable systems of ordinary differential equations. The results presented suggest that the inverse problem approach is a reliable method to solve the fitting problem. The predictive capabilities of this approach are demonstrated by comparing simulations based on estimation of parameters against real data sets for the case of recurrent epidemics caused by the respiratory syncytial virus in children.
Capistrán
Marcos A
MA
CIMAT, Jalisco S/N, Valenciana, Guanajuato, Mexico, CP 36240. marcos@cimat.mx
Moreles
Miguel A
MA
Lara
Bruno
B
D002648:Child; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D005387:Finland / Q000453:epidemiology; D005714:Gambia / Q000453:epidemiology; D006801:Humans; D055641:Mathematical Concepts; D008954:Models, Biological; D015233:Models, Statistical; D012008:Recurrence; D018357:Respiratory Syncytial Virus Infections / Q000453:epidemiology*; D012621:Seasons