Implementation and applications of EMOD, an individual-based multi-disease modeling platform

Area of Science:

• Epidemiology
• Computational Biology
• Software Engineering

Background:

• Individual-based models (IBMs) are crucial for infectious disease modeling at within-host and population levels.
• The complexity of IBMs often poses implementation challenges for students and researchers.
• Existing modeling approaches may lack the structural flexibility and modularity required for diverse disease dynamics.

Purpose of the Study:

• To describe a multi-disease framework approach using formal software support for infectious disease modeling.
• To highlight the advantages of a shared codebase for efficiency, usage, and testing in epidemiological software.
• To detail the development process and principles behind the EMOD software framework.

Main Methods:

• Development of the EMOD epidemiological modeling software over a decade.
• Structuring EMOD with a majority of shared code across multiple diseases (malaria, HIV, tuberculosis, dengue, polio, typhoid).
• Incorporation of hundreds of regression, scientific feature, and component tests for verification.

Main Results:

• EMOD provides a flexible, configurable, and modular framework for infectious disease modeling.
• Shared codebase enhances implementation efficiency, code usage, and testing across various diseases.
• Extensive testing suite ensures functionality and prevents unintended changes during development.

Conclusions:

• EMOD offers a robust solution to the implementation challenges of complex individual-based models.
• The software development principles applied result in a reliable and versatile tool for infectious disease research.
• EMOD facilitates efficient and rigorous modeling of multiple infectious diseases, supporting both within-host and population-level dynamics.