I want to use a neural network to predict the number of new cases of COVID-19. For the same, I have decided to use an SIRD (Susceptible-Infected-Recovered-Deceased) Model, which is parameterized by the transmission rate $\beta$, the recovery rate $\gamma_{r}$, and the fatality rate, $\gamma_{d}$. I want to make these parameters time-dependent, such that they can be changing everyday.

I have a dataset containing S,I,R,D values for successive days and want to use these values to predict the SIRD Model parameters over time. After tuning the parameters, I want to forecast the number of new cases each day.

How can I move ahead with this? Any ideas would be appreciated.


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