Strategies for ending tuberculosis in the South-East Asian Region: A modelling approach

Abstract

Background & objectives: To support recent political commitments to end tuberculosis (TB) in the World Health Organization South-East Asian Region (SEAR), there is a need to understand by what measures, and with what investment, these goals could be reached. These questions were addressed by using mathematical models of TB transmission by doing the analysis on a country-by-country basis in SEAR.

Methods: A dynamical model of TB transmission was developed, in consultation with each of the 11 countries in the SEAR. Three intervention scenarios were examined: (i) strengthening basic TB services (including private sector engagement), (ii) accelerating TB case-finding and notification, and (iii) deployment of a prognostic biomarker test by 2025, to guide mass preventive therapy of latent TB infection. Each scenario was built on the preceding ones, in successive combination.

Results: Comprehensive improvements in basic TB services by 2020, in combination with accelerated case-finding to increase TB detection by at least two-fold by 2020, could lead to a reduction in TB incidence rates in SEAR by 67.3 per cent [95% credible intervals (CrI) 65.3-69.8] and TB deaths by 80.9 per cent (95% CrI 77.9-84.7) in 2035, relative to 2015. These interventions alone would require an additional investment of at least US$ 25 billion. However, their combined effect is insufficient to reach the end TB targets of 80 per cent by 2030 and 90 per cent by 2035. Model projections show how additionally, deployment of a biomarker test by 2025 could end TB in the region by 2035. Targeting specific risk groups, such as slum dwellers, could mitigate the coverage needed in the general population, to end TB in the Region.

Interpretation & conclusions: While the scale-up of currently available strategies may play an important role in averting TB cases and deaths in the Region, there will ultimately be a need for novel, mass preventive measures, to meet the end TB goals. Achieving these impacts will require a substantial escalation in funding for TB control in the Region.

Keywords: Burden; SEAR - tuberculosis; end TB; epidemiology; modelling; public health.

Fig. 1

Illustration of the basic model structure, replicated by HIV, drug resistance and risk-group status. Compartments in red denote states that are infectious. The NTP (national TB programme) (left-hand side) sector is distinguished from the non-NTP sector (right-hand side). Among latent infection, it is assumed that those who are most at risk of developing disease within the next two years are detectable using a hypothetical, future diagnostic test. Not shown on this figure for clarity, the model also incorporates tuberculosis mortality, as well as recurrent tuberculosis (the latter including relapse of an existing infection, and exogenous reinfection).

Fig. 2

Model fits to World Health Organization estimates for incidence and mortality. Shown, for illustration, are the three countries accounting for 90 per cent of the population in South-East Asian Region: India (red), Indonesia (green) and Bangladesh (yellow). World Health Organization estimates account for recent trends, and it is not clear how these trends may continue in future. We adopted an ‘optimistic’ scenario (black curves) in which current trends persist until 2035, and a ‘pessimistic’ scenario in which current trends stabilize by 2020. Panels A and B show projections for incidence and mortality, respectively.

Fig. 3

Epidemic dynamics under different intervention scenarios. Shown are the dynamics aggregated over all 11 South-East Asian Region countries. Shaded regions show 95 per cent credible intervals (CrI), arising from uncertainty in input parameters (Table SII) and in potential future background trends in tuberculosis burden (illustrated in Fig. 2). The horizontal, dashed lines show the 2035 targets for incidence (left-hand panel) and mortality (right-hand panel).

Fig. 4

Minimum coverage levels for meeting the end tuberculosis goals by 2035. The x-axis denotes the proportion of TB in the general group that is detected per year, while the y-axis denotes the proportion of incipient TB that is successfully diagnosed and treated in the general population, each year. Each curve represents a different scenario for the coverage of case-finding and population prevention in the risk group. For example, yellow curves involve, as well as full implementation of the ‘strengthen’ package, additionally the risk group being screened five times a year for active disease, and (after 2025) for ‘incipient’ disease. The Figure illustrates that focused interventions in the risk group can significantly lower the coverage needed in the general population. However, there is limited incremental benefit to be gained, between screening 3 or 5 times a year in the risk group (comparing green and yellow lines).