Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review

Area of Science:

• Epidemiology
• Health Economics
• Computational Biology

Background:

• Simulation modeling is vital for optimizing HIV treatment and prevention strategies due to fiscal sustainability needs.
• The credibility of simulation models hinges on their design and the quality of input data.

Purpose of the Study:

• To conduct a narrative review of dynamic HIV transmission models.
• To synthesize and compare structural designs and evidence quality across 19 selected models.

Main Methods:

• Reviewed 19 HIV transmission models (compartmental, agent-based, microsimulation, hybrid).
• Focused on four structural components: population construction; care engagement; disease progression; and infection force.
• Assessed two analytical components: calibration/validation and health economic evaluation with uncertainty analysis.

Main Results:

• Model structures were largely homogenous except for entry, exit, and HIV care engagement.
• HIV testing was often not explicitly modeled.
• Data quality and transparency varied significantly; high-quality health service delivery data was frequently unavailable.

Conclusions:

• Model structure should align with epidemiological context and capture relevant interventions for effective combination strategies.
• Standardized guidelines for evidence synthesis in health economic evaluations are needed to enhance transparency and prioritize data collection.
• Reducing decision uncertainty requires improved data quality and model design in HIV simulation modeling.