e3SIM: epidemiological-ecological-evolutionary simulation framework for genomic epidemiology

Area of Science:

• Epidemiology
• Ecology
• Evolutionary Biology
• Computational Biology

Background:

• Infectious disease dynamics involve complex interactions between epidemiological, ecological, and evolutionary factors.
• Current models often oversimplify these interactions, failing to capture how pathogen evolution influences transmission.
• Accurate modeling is vital for understanding disease spread and informing public health interventions.

Purpose of the Study:

• To introduce the epidemiological-ecological-evolutionary simulator (e3SIM), an open-source framework for integrated modeling.
• To provide a tool that concurrently simulates pathogen transmission, molecular evolution, and environmental influences.
• To offer a flexible and scalable platform for studying complex infectious disease systems.

Main Methods:

• Developed an agent-based, discrete-generation, forward-in-time simulator (e3SIM).
• Integrated compartmental models, host contact networks, and quantitative-trait pathogen models.
• Incorporated time-varying environmental factors and a graphical user interface.

Main Results:

• e3SIM enables concurrent modeling of disease transmission and pathogen molecular evolution.
• The framework is modular, scalable, and flexible for diverse epidemiological and genetic complexities.
• Demonstrated capabilities with realistic SARS-CoV-2 and Mycobacterium tuberculosis outbreak simulations.

Conclusions:

• e3SIM offers a comprehensive approach to modeling infectious disease dynamics.
• The simulator facilitates the study of genomic epidemiology for various pathogen types.
• Provides a valuable tool for advancing public health research and strategy development.