Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19.

Accurate epidemiological models are necessary for governments, organizations, and individuals to respond appropriately to the ongoing novel coronavirus pandemic. One informative metric epidemiological models provide is the basic reproduction number ([Formula: see text]), which can describe if the infected population is growing ([Formula: see text]) or shrinking ([Formula: see text]). We introduce a novel algorithm that incorporates the susceptible-infected-recovered-dead model (SIRD model) with the long short-term memory (LSTM) neural network that allows for real-time forecasting and time-dependent parameter estimates, including the contact rate, [Formula: see text], and deceased rate, [Formula: see text].