Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks

1 code implementation • 7 Jan 2024 • Majd Al Aawar, Srikar Mutnuri, Mansooreh Montazerin, Ajitesh Srivastava

The current methods for predicting the spread of new variants rely on statistical modeling, however, these methods work only when the new variant has already arrived in the region of interest and has a significant prevalence.

Benchmarking

Random Forest of Epidemiological Models for Influenza Forecasting

1 code implementation • 17 Jun 2022 • Majd Al Aawar, Ajitesh Srivastava

We demonstrate that our Random Forest-based approach is able to improve upon the forecasts of the individual predictors in terms of mean absolute error, coverage, and weighted interval score.