Spatio-temporal predictive modeling framework for infectious disease spread

Abstract A novel predictive modeling framework for the spread of infectious diseases using high-dimensional partial differential equations is developed and implemented. scalar function representing infected population defined on a space its evolution over all directions described by balance equation (PBE). New infections are introduced among susceptible from non-quarantined based their interaction, adherence to distancing norms, hygiene levels any other societal interventions. Moreover, recovery, death, immunity aforementioned parameters modeled space. To epitomize capabilities features above framework, prognostic estimates Covid-19 six-dimensional (time, 2D space, infection severity, duration infection, age) PBE presented. Further, scenario analysis different policy interventions behavior presented, throwing more insights into spatio-temporal across disease, severity age population. These could be used science-informed planning.