Health Care Management Science

, Volume 15, Issue 3, pp 239-253

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Modelling the impacts of new diagnostic tools for tuberculosis in developing countries to enhance policy decisions

  • Ivor LangleyAffiliated withClinical Group, Liverpool School of Tropical Medicine Email author 
  • , Basra DoullaAffiliated withNational Tuberculosis and Leprosy Programme, Ministry of Health and Social Welfare
  • , Hsien-Ho LinAffiliated withInstitute of Epidemiology and Preventive Medicine, National Taiwan University
  • , Kerry MillingtonAffiliated withClinical Group, Liverpool School of Tropical Medicine
  • , Bertie SquireAffiliated withClinical Group, Liverpool School of Tropical Medicine


The introduction and scale-up of new tools for the diagnosis of Tuberculosis (TB) in developing countries has the potential to make a huge difference to the lives of millions of people living in poverty. To achieve this, policy makers need the information to make the right decisions about which new tools to implement and where in the diagnostic algorithm to apply them most effectively. These decisions are difficult as the new tools are often expensive to implement and use, and the health system and patient impacts uncertain, particularly in developing countries where there is a high burden of TB. The authors demonstrate that a discrete event simulation model could play a significant part in improving and informing these decisions. The feasibility of linking the discrete event simulation to a dynamic epidemiology model is also explored in order to take account of longer term impacts on the incidence of TB. Results from two diagnostic districts in Tanzania are used to illustrate how the approach could be used to improve decisions.


Developing Countries Simulation Transmission modelling Cost effectiveness Tuberculosis