Sanghani Center researchers win two major awards in COVID-19 forecasting challenges

We knew it for a long time that this pandemic is sort of something that's set in motion. Events that are going to last for the next few years or decades, right? We actually felt that it was actually important to start modelling this, especially because our group and our collaborators actually have experience with modelling similar diseases, specifically influenza. The goal of this project was essentially to model weighted influenza like illness curve in the current season, which is kind of special because it's actually being affected by a pandemic as well and you recover 19. So essentially our idea was to model the current influenza season by and explicitly using data from covert case counties in the United States. And the reason we thought this was important was because the health care seeking behavior of people would actually change and this would actually affect the evolution of the influenza, current influenza season. The way we achieve this was actually by developing a model that was able to effectively leverage historical influenza seasonal data and models from the past, and also leverage models that have been trained on more recent influenza data that's been contaminated by covered 19 pandemic, as well as explicitly using covert case counts. Current influenza season definitely showed some unseasonal peaks in the beginning around March or April of this year due to, you know, people going to the hospital even if they had influenza, thinking it was, it wa