ViralSim - A Novel Method for Simulating Pandemics with Geographical Data
Cai, B. D.
Show abstract
Accurately simulating viral evolution is critical for evaluating analytical tools, forecasting outbreaks, and improving our understanding of pathogen dynamics. ViralSim introduces a geographically structured agent-based model that emphasizes spatial transmission across clustered populations. Unlike prior approaches that primarily focus on genetic, purely statistical, or temporal parameters, ViralSim incorporates location-driven spread and explicit trait evolution. More over, the produced phylogeny enables the calculation and fine-tuning of diverse fitness metrics directly from ViralSim. These fitness measures provide insight into lineage success, and with enough development, offer a new way to analyze phylogenies. By combining spatial transmission, trait development, and fitness evaluation, ViralSim enables controlled benchmarking of phylogenetic and epidemiological analyses.
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