An epidemiological forecast model and software assessing interventions on COVID-19 epidemic in China

Peter X Song; Lili Wang; Yiwang Zhou; Jie He; Bin Zhu; Fei Wang; Lu Tang; Marisa Eisenberg

The copyright holder for this preprint (which was not peer-reviewed) is the . prediction steps. We let the transmission rate modifier πptq be either a step function or an exponential function, and let the quarantine rate φptq follow a Dirac delta function with pre-specified points of jump and sizes of jumps. The package provides various plots for users to visualize the MCMC results, including the estimated prevalence of infection and the estimated probability of removal, and predicted turning points of interest. Various summary statistics are listed in the output, including posterior mean estimates of the transmission and removal rates, estimate of the reproduction number, and forecasts of turning points and their 95% credible intervals. Moreover, the package gives multiple options to users who can save the entire MCMC results, including the output tables and summary plots, traceplots for MCMC quality control, and full MCMC draws for user's own summary analyses. Some illustrations on the use of this software package is given in Section 4. In addition, we developed an online R Shiny App that can automatically update the results whenever the China CDC updates the daily COVID-19 data.