title: Parameter identification in a tuberculosis model for Cameroon.
abstract: A deterministic model of tuberculosis in Cameroon is designed and analyzed with respect to its transmission dynamics. The model includes lack of access to treatment and weak diagnosis capacity as well as both frequency- and density-dependent transmissions. It is shown that the model is mathematically well-posed and epidemiologically reasonable. Solutions are non-negative and bounded whenever the initial values are non-negative. A sensitivity analysis of model parameters is performed and the most sensitive ones are identified by means of a state-of-the-art Gauss-Newton method. In particular, parameters representing the proportion of individuals having access to medical facilities are seen to have a large impact on the dynamics of the disease. The model predicts that a gradual increase of these parameters could significantly reduce the disease burden on the population within the next 15 years.
authors: Institute of Horticultural Production Systems, Leibniz Universität Hannover, Hannover, Germany.
authors: Dany Pascal
authors: DP
authors: Moualeu-Ngangue
authors: Department of Numerical Mathematics, Zuse Institute Berlin (ZIB), Berlin, Germany.
authors: Susanna
authors: S
authors: Röblitz
authors: Department of Numerical Mathematics, Zuse Institute Berlin (ZIB), Berlin, Germany.
authors: Rainald
authors: R
authors: Ehrig
authors: Beijing Center for Scientific and Engineering Computing, Beijing University of Technology, Beijing, China; Department of Numerical Mathematics, Zuse Institute Berlin (ZIB), Berlin, Germany.
authors: Peter
authors: P
authors: Deuflhard
mesh_terms: D002163:Cameroon / Q000453:epidemiology; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009169:Mycobacterium tuberculosis / Q000302:isolation & purification; D014376:Tuberculosis / Q000175:diagnosis / Q000453:epidemiology* / Q000635:transmission*