No abstract

For Tanzania, this integrated modelling approach predicts that full rollout of Xpert is a cost-effective option for tuberculosis diagnosis and has the potential to substantially reduce the national tuberculosis burden. It also estimates the substantial level of funding that will need to be mobilised to translate this into clinical practice. This approach could be adapted and replicated in other developing countries to inform rational health policy formulation.

Efforts to stimulate technological innovation in the diagnosis of tuberculosis (TB) have resulted in the recent introduction of several novel diagnostic tools. As these products come to market, policy makers must make difficult decisions about which of the available tools to implement. This choice should depend not only on the test characteristics (e.g., sensitivity and specificity) of the tools, but also on how they will be used within the existing health care infrastructure. Accordingly, policy makers choosing between diagnostic strategies must decide: 1) What is the best combination of tools to select? 2)Who should be tested with the new tools? and 3)Will these tools complement or replace existing diagnostics? The best choice of diagnostic strategy will likely vary between settings with different epidemiology (e.g., levels of TB incidence, human immunodeficiency virus co-infection and drug-resistant TB) and structural and resource constraints (e.g., existing diagnostic pathways, human resources and laboratory capacity). We propose a joint modelling framework that includes a tuberculosis (TB) transmission component (a dynamic epidemiological model) and a health system component (an operational systems model) to support diagnostic strategy decisions. This modelling approach captures the complex feedback loops in this system: new diagnostic strategies alter the demands on and performance of health systems that impact TB transmission dynamics which, in turn, result in further changes to demands on the health system. We demonstrate the use of a simplified model to support the rational choice of a diagnostic strategy based on health systems requirements, patient outcomes and population-level TB impact.

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.

SETTING: Eight tuberculosis treatment sites in Cavite Province, the Philippines, including two sites specialising in management of multidrug-resistant tuberculosis (MDR-TB).OBJECTIVE: To evaluate costs incurred by TB patients and to determine the proportion of households that faced catastrophic costs, then to consider cost survey responses alongside results of detailed patient-pathway modelling.DESIGN: Clustered cross-sectional survey using a field testing version of the WHO TB patient-costing tool and protocol; face-to-face interviews with 194 patients conducted in May–August 2016. Costs included direct-medical, direct non-medical and indirect costs using the human capital approach. Patients were deemed to incur catastrophic expenditure if TB-related costs exceeded 20% of annual household income. Patient pathways were modelled following multiple health staff interviews.RESULTS: Estimated mean cost incurred by patients with drug-susceptible TB was US$321 vs. $2356 for MDR-TB patients. Catastrophic costs were suffered by 28% of drug-susceptible and 80% of MDR-TB patients, with lost income being the largest contributor. Patient-pathway modelling suggested most patients had under-reported health visits.CONCLUSION: Survey results indicate that patient costs are large for all patients in Cavite, particularly for MDR-TB patients. Patient-pathway modelling suggests these costs are an underestimate due to poor recollection of health visits, suggesting that the WHO instrument and protocol could be improved to better capture the diagnostic journey.