Infectious Disease Forecasting

Similar with numerical weather prediction, operational forecast of infectious disease outbreaks can be realized using dynamical models in conjunction with data assimilation techniques. We developed computational methods to advance real-time forecasts of infectious disease spread, with a particular focus on the spatial transmission of influenza, dengue, and COVID-19. We also addressed the problem of optimizing surveillance networks for respiratory diseases. See related works published in PNAS, Nature Communications (2017), PLoS Computational Biology (2020), and Nature Communications (2021).