How to optimize tuberculosis case finding: explorations for Indonesia with a health system model

Area of Science:

• Mathematical modeling applied to public health interventions.
• Epidemiological analysis of tuberculosis (TB) control strategies.

Background:

• Tuberculosis (TB) remains a significant global health challenge, particularly in developing countries.
• Effective TB case finding is crucial for reducing mortality and improving treatment outcomes.
• The Indonesian health system context presents unique challenges for TB control.

Purpose of the Study:

• To mathematically model the Indonesian health system to evaluate TB case-finding strategies.
• To assess the impact of three interventions on TB mortality and treatment outcomes.
• To inform public health policy for improved TB control in Indonesia.

Main Methods:

• Development of a compartmental mathematical model simulating patient flow through the Indonesian health system.
• Inclusion of patient and health system delays in the model.
• Quantification of model parameters using a Delphi survey with Indonesian TB experts.

Main Results:

• Model validation showed reasonable agreement with existing epidemiological data.
• Reducing the proportion of TB patients who never seek care was predicted to have the largest impact on preventing TB deaths.
• Increasing referrals of TB suspects to Directly Observed Treatment, Short-course (DOTS) facilities was linked to higher cure rates.

Conclusions:

• Mathematical modeling provides a valuable tool for evaluating health system interventions for TB control.
• Expert opinion can effectively parameterize models when detailed data are scarce.
• Active case finding and improved referral systems are critical for enhancing TB treatment outcomes in resource-limited settings.