Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic

Understand

Accurate forecasts of COVID-19 is central to resource management and building strategies to deal with the epidemic.

• We propose a heterogeneous infection rate model with human mobility for epidemic modeling, a preliminary version of which we have successfully used during DARPA Grand Challenge 2014.
• By linearizing the model and using weighted least squares, our model is able to quickly adapt to changing trends and provide extremely accurate predictions of confirmed cases at the level of countries and states of the United States.
• We show that during the earlier part of the epidemic, using travel data increases the predictions.