ArticleMethods in ecology and evolution2026
e3SIM: Epidemiological-ecological-evolutionary simulation framework for genomic epidemiology.
Article in Methods in ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Comparing methods to estimate time-varying reproduction numbers using genomic and epidemiological data.Infectious Disease Modelling · 2026Article
- SIMPLICITY is an agent-based, multi-scale mathematical model to study SARS-CoV-2 intra- and between-host evolution.Communications biology · 2026Article
- Gaussian Process Emulation for Exploring Complex Infectious Disease Models.medRxiv : the preprint server for health sciences · 2025Article
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15 authors.
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Abstract
Infectious disease dynamics result from the complex interplay of epidemiological, ecological and evolutionary (epi-eco-evo) processes. Accurately modelling these coupled processes is crucial for understanding pathogen spread and informing public health strategies. However, existing genomic epidemiology simulators typically assume conditional independence among these processes: generating transmission trees independently of pathogen evolution, and then superimposing neutral mutations onto fixed genealogies without ecological feedback. This simplification fails to capture how pathogen evolution dynamically reshapes epidemic trajectories.We introduce e3SIM, an open-source, agent-based, forward-time simulator for macOS and Linux that explicitly integrates pathogen transmission dynamics, molecular evolution and environmental factors. e3SIM incorporates configurable compartmental models, user-defined host contact networks, customizable pathogen genetic architectures and optional eco-evolutionary features (e.g. within-host dynamics, multi-strain infections). This integration enables realistic modelling of pathogen spread and evolution. Key features include modularity, flexible epidemiological and population-genetic modelling, time-varying environmental factors and a user-friendly graphical interface.We demonstrated e3SIM's capabilities by simulating SARS-CoV-2 and
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