How can mathematical models advance tuberculosis control in high HIV prevalence settings?

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Tuberculosis (TB) control is challenging in high human immunodeficiency virus (HIV) prevalence settings.
• Existing TB control strategies have shown limited success in co-epidemic areas.
• Mathematical modeling offers a valuable tool for understanding and optimizing TB-HIV interventions.

Purpose of the Study:

• To review the contributions of TB modeling in high HIV prevalence settings.
• To propose a research agenda for TB-HIV modeling based on expert consensus.
• To guide future modeling efforts for more effective TB-HIV epidemic response.

Main Methods:

• Overview of past and recent TB modeling contributions.
• Expert discussions convened by the TB Modelling and Analysis Consortium.
• Identification of high-priority research areas for TB-HIV modeling.

Main Results:

• Key research priorities include TB-HIV diagnosis and mortality, disease progression, health systems, natural disease progression uncertainty, and combined interventions.
• The need for co-ordination between modelers and stakeholders (advocates, policymakers, donors) is highlighted.
• A continuing dialogue is crucial for effective communication and policy relevance.

Conclusions:

• A coordinated modeling research agenda is essential for advancing TB-HIV epidemic control.
• Addressing specific high-priority areas through modeling will support public health and economic benefits.
• Collaboration and communication are vital to ensure modeling outputs inform policy and practice.