Varying Coefficient SIR Model

This repository includes the R code for varying coefficient SIR model(vSIR) in Sun et al.(2020).

• basic_functions.R

The code provide functions for smoothing, reciprocal fitting and ODE simulation. Here we use a three point smoothing with a weight $3:4:3$ and $7:3$ and $3:7$ for the first and last day. The reciprocal function $\hat{\beta_t} = b/t^{\eta} - a$ fitted by non-linear minimization.

• code_for_vSIR_model.R

The code is for reproducing the estimation of $\beta(t)$, $\gamma(t)$ and $R^D(t)$. The estimates are based on the infected and removed cases each day. See Sun et al.(2020) for method and theory details.

• code_for_prediction.R

The code is for reproducing the prediction result. The prediction for the peak time, ending time and final infected number are based on reciprocal fitting model and simulation function built with the ODE. The prediction intervals are constructed with the Bootstrap method. See Sun et al.(2020) for method and theory details.

Reference

Sun, H., Qiu, Y., Yan, H., Huang, Y., Zhu, Y., Gu, J. and Chen, S. X. "Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model" Journal of Data Science(2020), to appear.