Figure 2.

Comparison of estimated and predicted effective reproduction numbers for COVID-19, using the model accounting for Google mobility, temperature, and risk awareness.

Comparison between the estimated and predicted effective reproduction numbers ($R_t$) for COVID-19. The model (Model 3; considering Google mobility, temperature, and risk awareness of COVID-19) was applied to the four training data prefectures of Japan: (A) Tokyo, (B) Osaka, (C) Aichi, and (D) Hokkaido. Yellow bars represent reconstructed numbers of COVID-19 cases by infection time; grey bars show the number of predicted incidences using the conditional forecasting method. Blue lines and shaded areas indicate the estimated $R_t$ values and their 95% confidence intervals using the renewal process and profile likelihood, while purple lines and shaded areas indicate the predicted $R_t$ values and their 95% confidence intervals derived from the Laplace approximation normal distribution. Red shaded areas indicate the training period (i.e. March 15 to May 1, 2020 and July 15 to August 31, 2020) used for estimating the parameters of the model.