Combining Two Methods of Global Sensitivity Analysis to Investigate MRSA Nasal Carriage Model

Area of Science:

• Microbiology
• Mathematical Modeling
• Computational Biology

Background:

• Staphylococcus aureus nasal carriage is a significant public health concern.
• Understanding the dynamics of S. aureus colonization is crucial for developing effective interventions.
• Mathematical models are valuable tools for exploring complex biological systems.

Purpose of the Study:

• To apply sensitivity analysis techniques to a model of bacterial colonization of the anterior nares.
• To identify key parameters influencing Staphylococcus aureus nasal carriage dynamics.
• To develop a reduced model for enhanced understanding of the biological phenomenon.

Main Methods:

• Application of partial rank correlation coefficients (PRCC) to assess parameter sensitivity over time.
• Development of a reduced model with fewer parameters than the full model.
• Calculation of Sobol' indices to identify interacting parameters and their additional effects.

Main Results:

• Identification of a reduced model with less than half the parameters of the full model.
• Discovery that only two parameters significantly influenced the model's behavior concerning initial infection size.
• These key parameters have biological evidence suggesting a connected but not fully understood relationship.

Conclusions:

• Combining sensitivity measures provides synergistic insights into both model and biological structures.
• The study elucidates model robustness and biological mechanisms of S. aureus nasal carriage.
• Further research is warranted to fully understand the identified interacting parameters.