STI-GMaS

STI-GMaS simulates within-host mathematical models of sexually transmitted infections to study infection replication and ascension through the genital tract across menstrual cycle phases and to evaluate interventions, demonstrated for Chlamydia trachomatis including vaccination scenarios.

Key Features:

• Integration with published models: Integrates mathematical models from published literature for simulation and analysis.
• Simulation environment (CHASTE): Implements simulations using the CHASTE framework (Cancer, Heart and Soft Tissue Environment).
• Hybrid PDE and cellular automata model: Implements a hybrid partial differential equation (PDE) and cellular automata model to represent tissue-level infection dynamics and simulate scenarios such as vaccination.
• Visualization tools: Integrates open-source plotting software for visualization of simulation results.
• Case study—Chlamydia trachomatis: Includes a focused application to Chlamydia trachomatis, the most prevalent bacterial sexually transmitted pathogen in humans.
• Parameterization and adaptability: Supports parameterization of models with the ability to adjust parameters based on experimental data.
• Extensibility: Designed to be extensible to additional bacterial and viral sexually transmitted infections.

Scientific Applications:

• Intervention evaluation: Simulates infection dynamics to evaluate potential treatments and vaccine scenarios.
• Female reproductive health studies: Models infection replication and ascension through the genital tract across menstrual cycle phases to investigate reproductive health implications.
• Pathogenesis of Chlamydia trachomatis: Explores within-host dynamics and disease progression under conditions such as treatment delay or absence.
• Hypothesis testing and scenario analysis: Enables scenario analysis and hypothesis testing to inform pathogenesis studies and public health strategies.

Methodology:

Mathematical models from published literature are implemented and simulated within the CHASTE framework using a hybrid partial differential equation (PDE) and cellular automata model, with results visualized via integrated open-source plotting software and models parameterized based on experimental data.