Modelling and Parameter Identification of Tuberculosis in Cameroon


  • Dany Pascal Moualeu* Berliner Mathematical School/Zuse Institute Berlin/
  • Susanna Röblitz Zuse Institute Berlin, MATHEON
  • Rainald Ehrig Zuse Institute Berlin
  • Peter Deuflhard Zuse Institute Berlin Free university Berlin



Tuberculosis (TB) is a common lethal infectious disease usually caused by
Mycobacterium tuberculosis. TB is a preventable and curable disease which most
often affects the lungs. According to the WHO, TB to date, claims the second
largest number of victims due to a single infectious agent right after HIV/AIDS.
Although a widespread implementation of control measures focus on case finding
and short-course chemotherapy, the global burden of TB has increased
over the past two decades [1].

AВ  deterministic modelВ  of tuberculosis inВ  sub-Saharan Africa in general
and Cameroon in particular is designed and analyzedВ  with respect to its
transmission dynamics.
The model includes 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
parameters of the model are identified using the Gauss-Newton Method [2]. In
particular, parameters representing the proportion of individuals having access
to medical facilities have a large impact on the dynamics of the disease.
We demonstrate how an increase of these parameter values over time can
significantly reduce the disease burden in the population within the next 15

Author Biographies

Dany Pascal Moualeu*, Berliner Mathematical School/Zuse Institute Berlin/

PhD student Department of Numerical Analysis and modelling

Susanna Röblitz, Zuse Institute Berlin, MATHEON

Head of the Computational Biology Group






Conference Contributions