MicroHibro

MicroHibro quantifies the fate of pathogenic microorganisms throughout food chains to support quantitative microbial risk assessment by modeling growth, inactivation, transfer, partitioning, and dose-response processes.

Key Features:

• Predictive Microbiology Model Data Base (PMDB): A curated database of predictive models including kinetic growth, inactivation, transfer, partitioning, and dose–response models that can be updated via an online tool using standardized model description methods.
• Microbial Process Estimation: Describes food-chain steps using four microbial processes—growth, inactivation, transfer, and partitioning—to estimate microorganism concentration and prevalence in food products.
• Risk Assessment and QMRA Integration: Integrates predictive models to construct Quantitative Microbial Risk Assessment (QMRA) models for exposure and risk estimation.
• Model Comparison and Validation: Enables comparison of alternative predictive models and validation of models using user-provided data.

Scientific Applications:

• Microbial dynamics analysis: Quantitative modeling of pathogen behavior across stages from production to consumption using growth, inactivation, transfer, and partitioning processes.
• Exposure and risk quantification: Estimation of microorganism concentration and prevalence to inform exposure assessment and QMRA.
• Model evaluation: Comparison and validation of predictive models with experimental or observational data to support model selection for specific scenarios.
• Support for intervention and policy assessment: Provision of quantitative risk estimates to inform development of preservation techniques and regulatory policy.

Methodology:

Uses a PMDB containing growth, inactivation, transfer, partitioning, and dose–response models; represents food-chain steps as combinations of the four microbial processes; integrates predictive models to build QMRA models; supports model comparison and validation with user-provided data; allows PMDB updates via an online tool employing standardized model description methods.