Changes for second submission, needs neatening up

Author: Joel Hellewell

R/box_plot_max_weekly_cases.R

@@ -132,7 +132,8 @@ box_plot_max_weekly_cases <- function(results = NULL,
                               ggplot2::aes(label = label_extinct),
                               col = "black", fill = "white",
                               size = 4,
-                              point.padding = NA)
+                              point.padding = NA) +
+    ggplot2::coord_cartesian(ylim=c(0,y_lim))
 
 
   return(plot)

R/figures2to4.R

@@ -28,7 +28,7 @@ make_figure_2a <- function() {
   out %<>% tidyr::gather("dist", "value", -x)
 
 
-  means <- data.frame(x = c(3.83, 9.1),
+  medians <- data.frame(x = c(3.43, 8.09),
                       dist = c("delay_sars", "delay_wuhan")) %>%
     dplyr::mutate(dist = factor(dist,
                                 levels = c("delay_sars",
@@ -56,7 +56,7 @@ make_figure_2a <- function() {
                                palette = "Set1") +
     ggplot2::scale_colour_brewer(guide = "none",
                                  palette = "Set1") +
-    ggplot2::geom_vline(data = means,
+    ggplot2::geom_vline(data = medians,
                         ggplot2::aes(xintercept = x,
                                      col = as.factor(dist)),
                         lty = 2,

R/supp_fig_9.R

@@ -0,0 +1,78 @@
+make_figure_S9 <- function(sweep_results = NULL){
+  temp <- sweep_results %>% filter(index_R0 == 1.5,
+                                   theta=="15%",
+                                   delay == "SARS",
+                                   prop.asym == 0,
+                                   num.initial.cases==20,
+                                   control_effectiveness == 0.8)
+
+
+  ext_df <- temp$sims[[1]] %>% group_by(sim) %>%
+    dplyr::filter(week %in% 12:16) %>%
+    dplyr::summarise(extinct =
+                       ifelse(all(weekly_cases == 0 &
+                                    cumulative < 5000),
+                              1, 0)) %>%
+    dplyr::ungroup()
+
+  p1 <- full_join(temp$sims[[1]],ext_df) %>%
+    filter(sim < 50) %>%
+    ggplot(aes(x=week,y=cumulative,col=as.factor(extinct),group=sim)) + geom_line(alpha=0.6) +
+    cowplot::theme_cowplot() + coord_cartesian(ylim=c(0,1000),xlim=c(0,16)) +
+    scale_color_manual(name="Simulation controlled",values=c("dodgerblue1"),guide="none") +
+    ylab("Cumulative cases") +
+    ggtitle("R0 = 1.5") +
+    xlab("Outbreak week")
+
+
+  temp <- sweep_results %>% filter(index_R0 == 2.5,
+                                   theta=="15%",
+                                   delay == "SARS",
+                                   prop.asym == 0,
+                                   num.initial.cases==20,
+                                   control_effectiveness == 0.8)
+
+  ext_df <- temp$sims[[1]] %>% group_by(sim) %>%
+    dplyr::filter(week %in% 12:16) %>%
+    dplyr::summarise(extinct =
+                       ifelse(all(weekly_cases == 0 &
+                                    cumulative < 5000),
+                              1, 0)) %>%
+    dplyr::ungroup()
+
+  p2 <- full_join(temp$sims[[1]],ext_df) %>%
+    filter(sim < 50) %>%
+    ggplot(aes(x=week,y=cumulative,col=as.factor(extinct),group=sim)) + geom_line(alpha=0.6) +
+    cowplot::theme_cowplot() + coord_cartesian(ylim=c(0,1000),xlim=c(0,16)) +
+    scale_color_manual(name="Simulation controlled",values=c("firebrick1","dodgerblue1"),labels=c("Uncontrolled","Controlled")) +
+    ggtitle("R0 = 2.5") +
+    ylab("Cumulative cases") +
+    xlab("Outbreak week")
+
+  temp <- sweep_results %>% filter(index_R0 == 3.5,
+                                   theta=="15%",
+                                   delay == "SARS",
+                                   prop.asym == 0,
+                                   num.initial.cases==20,
+                                   control_effectiveness == 0.8)
+
+  ext_df <- temp$sims[[1]] %>% group_by(sim) %>%
+    dplyr::filter(week %in% 12:16) %>%
+    dplyr::summarise(extinct =
+                       ifelse(all(weekly_cases == 0 &
+                                    cumulative < 5000),
+                              1, 0)) %>%
+    dplyr::ungroup()
+
+  p3 <- full_join(temp$sims[[1]],ext_df) %>%
+    filter(sim < 50) %>%
+    ggplot(aes(x=week,y=cumulative,col=as.factor(extinct),group=sim)) + geom_line(alpha=0.6) +
+    cowplot::theme_cowplot() + coord_cartesian(ylim=c(0,1000),xlim=c(0,16)) +
+    scale_color_manual(name="Simulation controlled",values=c("firebrick1","dodgerblue1"),labels=c("Uncontrolled","Controlled")) +
+    ylab("Cumulative cases") +
+    ggtitle("R0 = 3.5") +
+    xlab("Outbreak week")
+  p3
+  p1 + p2 + p3 + patchwork::plot_layout(guides="collect")
+}
+

inst/scripts/generate_figures.R

@@ -57,7 +57,7 @@ ringbp::box_plot_max_weekly_cases(results = sweep_results, cap_cases = 5000,
                                   filt_control_effectiveness = 0.4,
                                   num_initial_cases = 20, flip_coords = FALSE,
                                   facet_scales = "fixed", record_params = F,
-                                  prop_asym = 0, y_lim = 225)
+                                  prop_asym = 0, y_lim = 125)
 
 ggplot2::ggsave("inst/plots/fig_5.pdf", height = 7, width = 12,
                 useDingbats = FALSE)
@@ -120,7 +120,7 @@ ringbp::box_plot_max_weekly_cases(results = sweep_results,
                                   num_initial_cases = 40,
                                   facet_scales = "fixed",
                                   record_params = F,
-                                  y_lim = 450)
+                                  y_lim = 200)
 
 ggplot2::ggsave("inst/plots/S_fig_5_B.pdf", height = 5, width = 10,
                 useDingbats = FALSE)
@@ -134,7 +134,7 @@ ringbp::box_plot_max_weekly_cases(results = sweep_results,
                                   num_initial_cases = 20,
                                   facet_scales = "fixed",
                                   record_params = F,
-                                  y_lim = 1000)
+                                  y_lim = 100)
 
 ggplot2::ggsave("inst/plots/S_fig_5_C.pdf", height = 5, width = 10,
                 useDingbats = FALSE)
@@ -176,19 +176,24 @@ ggplot2::ggsave("inst/plots/S_fig_7c.pdf", height = 5, width = 7,
                 useDingbats = FALSE)
 ggplot2::ggsave("inst/plots/S_fig_7c.png", height = 5, width = 7)
 
-## S6
-
-ringbp::box_plot_max_weekly_cases(results = results_dispersion_flu,
-                                  cap_cases = 5000,
-                                  extinct_thresold = 0.05,
-                                  filt_control_effectiveness = 0.4,
-                                  num_initial_cases = 40,
-                                  flip_coords = F,
-                                  prop_asym = 0,
-                                  facet_scales = "fixed",
-                                  record_params = F,
-                                  y_lim = 400)
-
-ggplot2::ggsave("inst/plots/S_fig_6.pdf", height = 8, width = 12,
+make_figure_S9()
+ggplot2::ggsave("inst/plots/S_fig_9.pdf", height = 4.5, width = 11,
                 useDingbats = FALSE)
-ggplot2::ggsave("inst/plots/S_fig_6.png", height = 8, width = 12)
+ggplot2::ggsave("inst/plots/S_fig_9.png", height = 4.5, width = 11)
+
+# ## S6
+#
+# ringbp::box_plot_max_weekly_cases(results = results_dispersion_flu,
+#                                   cap_cases = 5000,
+#                                   extinct_thresold = 0.05,
+#                                   filt_control_effectiveness = 0.4,
+#                                   num_initial_cases = 40,
+#                                   flip_coords = F,
+#                                   prop_asym = 0,
+#                                   facet_scales = "fixed",
+#                                   record_params = F,
+#                                   y_lim = 400)
+#
+# ggplot2::ggsave("inst/plots/S_fig_6.pdf", height = 8, width = 12,
+#                 useDingbats = FALSE)
+# ggplot2::ggsave("inst/plots/S_fig_6.png", height = 8, width = 12)