Advancing risk assessment: mechanistic dose-response modelling of

Area of Science:

• Microbiology
• Immunology
• Mathematical Biology

Background:

• Traditional exponential models for Listeria monocytogenes dose-response have limitations in accounting for strain variation and host susceptibility.
• Descriptive models can capture variation but lack extrapolation power beyond specific outbreaks.

Purpose of the Study:

• To develop a mechanistic model for Listeria monocytogenes dose-response relationships.
• To quantify key biological factors in pathogen-host dynamics.
• To connect dose-response curves to underlying bistable dynamics.

Main Methods:

• Developed an efficient computational algorithm and geometric interpretation of the infection pathway.
• Integrated in vitro experiments and human outbreak data to estimate model parameters.
• Performed sensitivity analysis to identify influential factors in host response.

Main Results:

• The mechanistic model quantifies pathogen-host dynamics, offering insights beyond descriptive approaches.
• Host response is most sensitive to the pathogen-immune system interaction.
• Variations in this interaction within subgroups influence dose-response curve shapes.

Conclusions:

• The developed model provides a mechanistic basis for understanding Listeria monocytogenes dose-response.
• Pathogen-immune interaction is a critical determinant of host susceptibility and dose-response curves.
• Results guide future research on immune cells and Listeria monocytogenes strains.