Dynamic-Parameter SIRD Forecasting: ReproducibleTime-Varying Rate Estimation for COVID-19
This paper introduces a reproducible, hybrid SIRD framework that estimates time-varying epidemic parameters via algebraic inversion and Vector Autoregression to outperform static and naive forecasting baselines in predicting COVID-19 cases and deaths, though it currently exhibits limited probabilistic calibration.