Adds qa_alpha=0.3 to transmission & delay tasks

Author: tristan-myles

src/nipah_delays/nipah_delays.R

@@ -227,6 +227,8 @@ lanonc_colours <- ggsci::pal_lancet("lanonc")(9)
 text_size <- 28
 
 qa_thresh_vec <- c("all"=-1, "qa"=0.5)
+qa_alpha_vec <- c(0.3, 1)
+
 labels <- c("SI_allqa", "")
 colour_columns <- c("parameter_type",
                     "population_group",
@@ -244,6 +246,7 @@ p7_oo_reduced_plots <- list("all"=list())
 for (i in seq_along(qa_thresh_vec)){
   label <- labels[i]
   qa_threshold <- qa_thresh_vec[i]
+  qa_alpha <- qa_alpha_vec[i]
   plot_type <- names(qa_thresh_vec)[i]
   dir.create(plot_type, showWarnings = FALSE)
   for (colour_col in colour_columns){
@@ -273,7 +276,7 @@ for (i in seq_along(qa_thresh_vec)){
       p1_incb_plots[[plot_type]][[colour_col]] <- forest_plot(
         d1 |> filter(qa_score>qa_threshold), "Incubation period (days)",
         colour_col, c(0,35), text_size=text_size, segment_show.legend = NA,
-        sort=TRUE, custom_colours = custom_colours)
+        sort=TRUE, custom_colours = custom_colours, qa_alpha=qa_alpha)
 
       ggsave(file.path(plot_type,
                        paste0("figure_5", label, "_incubation_",
@@ -285,7 +288,8 @@ for (i in seq_along(qa_thresh_vec)){
       p2_oa_plots[[plot_type]][[colour_col]] <- forest_plot(
         d2 |> filter(qa_score>qa_threshold),
         'Symptom onset-to-hospitalisation delay (days)', colour_col, c(0,20),
-        text_size = text_size, sort=TRUE, custom_colours = custom_colours)
+        text_size = text_size, sort=TRUE, custom_colours = custom_colours,
+        qa_alpha=qa_alpha)
 
       ggsave(file.path(plot_type,
                        paste0("figure_5", label, "_onset_admis_",
@@ -309,7 +313,7 @@ for (i in seq_along(qa_thresh_vec)){
       p3_ao_plots[[plot_type]][[colour_col]] <- forest_plot(
         d3 |> filter(qa_score>qa_threshold), 'Hospitalisation-to-outcome (days)',
         colour_col, c(0,45), text_size = text_size, sort=TRUE,
-        custom_colours = custom_colours)
+        custom_colours = custom_colours, qa_alpha=qa_alpha)
       ggsave(file.path(plot_type,
                        paste0("figure_5", label, "_admis_outcome_",
                               colour_col_label, ".pdf")),
@@ -355,7 +359,8 @@ for (i in seq_along(qa_thresh_vec)){
       d4_x_axis_label, colour_col, xlim,
       text_size = text_size, sort=TRUE,
       segment_show.legend = c(shape=FALSE, colour=TRUE),
-      custom_colours = custom_colours) +
+      custom_colours = custom_colours,
+      qa_alpha=qa_alpha) +
       # Showing Sim overlaid
       geom_point(data=sim_duplicated_row,
                  aes(x = parameter_value, y = refs,
@@ -402,7 +407,7 @@ for (i in seq_along(qa_thresh_vec)){
         d6 |> filter(qa_score>qa_threshold),
         'Symptom onset/Hospitalisation-to-outcome (days)',
         colour_col, xlim, text_size = text_size, sort=TRUE,
-        custom_colours = custom_colours)
+        custom_colours = custom_colours, qa_alpha=qa_alpha)
       ggsave(file.path(plot_type,
                        paste0("figure_5", label, "_onset_admis_outcome_",
                               colour_col_label, ".pdf")),
@@ -434,7 +439,7 @@ for (i in seq_along(qa_thresh_vec)){
         d7 |> filter(qa_score>qa_threshold),
         'Symptom onset-to-outcome (days)',
         colour_col, c(0,85), text_size = text_size, sort=TRUE,
-        custom_colours = custom_colours)
+        custom_colours = custom_colours, qa_alpha=qa_alpha)
       ggsave(file.path(plot_type,
                        paste0("figure_5", label, "_onset_outcome_reduced_",
                               colour_col_label, ".pdf")),

src/nipah_transmission/nipah_transmission.R

@@ -125,18 +125,20 @@ names(custom_colour_genome_groups) <- all_genomes
 # Repeat twice - with and without QA filter
 # -1 to include all articles
 qa_thresh_vec <- c(-1, 0.5)
+qa_alpha_vec <- c(0.3, 1)
 labels <- c("SI_allqa_", "")
 
 for (i in seq_along(qa_thresh_vec)){
   label <- labels[i]
   qa_threshold <- qa_thresh_vec[i]
+  qa_alpha <- qa_alpha_vec[i]
 
   p1 <- forest_plot(d1 |> filter(qa_score>qa_threshold),
                     expression(Evolutionary~Rate~(s/s/y ~10^{-4})),
                     "genome_site",
                     c(-0.01,15), custom_colours = custom_colour_genome_groups,
                     segment_show.legend=c(color=TRUE, shape=FALSE),
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     scale_color_manual(values=custom_colour_genome_groups,
                        limits=names(custom_colour_genome_groups)) +
     scale_fill_manual(values=custom_colour_genome_groups,
@@ -151,7 +153,7 @@ for (i in seq_along(qa_thresh_vec)){
                     expression(Substitution~Rate~(s/s/y ~10^{-4})),
                     "genome_site",
                     c(0,16), custom_colours = custom_colour_genome_groups,
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     guides(shape = guide_legend(title = "Parameter type", order=1),
            fill = guide_none(),
            color = guide_none())
@@ -160,23 +162,23 @@ for (i in seq_along(qa_thresh_vec)){
                     "Overdispersion (max nr. of cases related to a case)",
                     "population_group", c(0,35),
                     custom_colours = custom_colour_pop_groups,
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     guides(color = guide_none(),
            shape = guide_none())
 
   p4 <- forest_plot(d4 |> filter(qa_score>qa_threshold),
                     "Primary Attack Rate (%)",
                     "population_group",
                     c(-0.01,3), custom_colours = custom_colour_pop_groups,
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     guides(color = guide_none(),
            shape = guide_none())
 
   p5 <- forest_plot(d5 |> filter(qa_score>qa_threshold),
                     "Proportion of Symptomatic Cases (%)",
                     "population_group",
                     c(-5, 110), custom_colours = custom_colour_pop_groups,
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     guides(color = guide_none(),
            shape = guide_none())
 
@@ -185,7 +187,7 @@ for (i in seq_along(qa_thresh_vec)){
                     "population_group",
                     c(0, 1.5), custom_colours = custom_colour_pop_groups,
                     segment_show.legend=c(color=TRUE, shape=FALSE),
-                    text_size=text_size) +
+                    text_size=text_size, qa_alpha=qa_alpha) +
     scale_color_manual(values=custom_colour_pop_groups,
                        limits=names(custom_colour_pop_groups)) +
     scale_fill_manual(values=custom_colour_pop_groups,