SEVA: An externally driven framework for reproducing COVID-19 mortality waves without transmission feedback
The paper introduces the SEVA framework, an externally driven model that successfully reproduces the temporal structure of early COVID-19 mortality waves across multiple regions using a single parameter for population-level exposure, thereby offering a parsimonious alternative to traditional transmission-based models by decoupling epidemic dynamics from infection feedback.