Epidemiological Forecasting with ICC curves and data assimilation
Every week, the CDC posts COVID-19 death forecasts for the US and its states and territories. These estimates are created with an ensemble model that combines probabilistic predictions made by a variety of groups in the US and abroad. Our model, EpiCovDA, which is developed by mathematics graduate student Hannah Biegel, is one of these contributions. In this talk, I will present a novel paradigm for epidemiological modeling that centers around ICC curves, which relate incidence to the cumulative cases of an outbreak. I will then explain how this approach may be used for parameter estimation, and how it is combined with data assimilation in EpiCovDA.
Password: “arizona” (all lower case)