Multi-strain Evolutionary Model with Mutation driven by Population Threat

We develop a hybrid mathematical model combining exponential growth phases with mutation-triggered transitions. The model captures both the initial rapid spread and the dynamic, state-dependent switching between variants. Through analysis and simulation, we demonstrate how this framework reproduces observed patterns of variant succession and eventual viral attenuation. Our approach not only aligns with evolutionary theory but also provides a predictive tool for understanding long-term epidemic trajectories, with implications for intervention design and public health planning. By integrating population thresholds with mutation dynamics, this work offers a more mechanistic view of viral evolution---one where the virus itself, in response to threat, may shapes the future course of an epidemic.