A novel predictive modeling framework for the spread of infectious diseases using high-dimensional partial differential equations is developed and implemented. Prognostic estimates of Covid-19 spread using a six-dimensional (time, 2D space, infection severity, duration of infection, and population age) modelled in this framework. These insights have been used by local states to frame science-informed policies.

Faculty: Sashikumaar Ganesan

References:

S. Ganesan, D. Subramani: Spatio-temporal predictive modeling framework for infectious disease spread. (2021) Nature Scientific Reports 11, 6741 (2021)