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Updated: Jun 21, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

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

Peiyu Xu¹, Shenni Liang², Andrew Hahn²

¹Department of Molecular Biology & Genetics, Cornell University, Ithaca, NY, USA.

Biorxiv : the Preprint Server for Biology

|July 15, 2024

Summary

This summary is machine-generated.

A new simulator, e3SIM, models infectious disease spread, pathogen evolution, and environmental factors together. This tool enhances understanding of disease dynamics for improved public health strategies.

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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.