Mathematical model and intervention strategies for mitigating tuberculosis in the Philippines

Area of Science:

• Mathematical epidemiology
• Public health interventions
• Infectious disease modeling

Background:

• Tuberculosis (TB) remains a significant public health challenge in the Philippines, ranking as the sixth leading cause of morbidity and mortality.
• Despite advancements like Directly Observed Treatment Short Course (DOTS), controlling TB transmission requires enhanced, targeted interventions.

Purpose of the Study:

• To develop and analyze a mathematical model of TB transmission dynamics in the Philippines.
• To investigate the efficacy of various control strategies, including distancing, latent case finding, case holding, and active case finding, using optimal control theory.
• To identify cost-effective strategies for reducing latent and infectious TB patient numbers.

Main Methods:

• Development of a mathematical model specifically fitted to Philippine TB data.
• Application of optimal control theory to evaluate different intervention scenarios.
• Comparative analysis of single and combined control strategies.

Main Results:

• Distancing control emerged as the most effective single intervention strategy.
• Combined interventions are necessary to overcome the challenges of implementing full-scale distancing.
• Enhancing active case finding, alongside distancing and latent case finding, proved highly effective in curtailing TB spread, outperforming case holding.

Conclusions:

• A combination of distancing, latent case finding, and enhanced active case finding presents a potent strategy for TB control in the Philippines.
• Optimizing intervention combinations is crucial for efficient and effective TB eradication efforts.
• The study highlights the significant potential of active case finding in TB control strategies.