Update Supplement.Rmd

Author: kathsherratt

report/supplement/Supplement.Rmd

@@ -48,6 +48,16 @@ Forecast and observed data were sourced from the European COVID-19 Forecast Hub,
 
 Data for this work were downloaded on 30th May 2023. These data are available in the Github repository for this paper at: <https://github.com/epiforecasts/eval-by-method/tree/main/data>
 
+```{r load-data}
+# Load data
+scores <- process_data(scoring_scale = "log")
+ensemble <- scores |>
+  filter(grepl("EuroCOVIDhub-ensemble", Model))
+scores <- scores |>
+  filter(!grepl("EuroCOVIDhub-ensemble", Model))
+n_forecasts <- nrow(scores)
+```
+
 \newpage
 
 # Model characteristics
@@ -62,16 +72,6 @@ knitr::include_graphics(here("output", "plots", "flowchart.png"))
 
 ## Model characteristics
 
-```{r load-data}
-# Load data
-scores <- process_data(scoring_scale = "log")
-ensemble <- scores |>
-  filter(grepl("EuroCOVIDhub-ensemble", Model))
-scores <- scores |>
-  filter(!grepl("EuroCOVIDhub-ensemble", Model))
-n_forecasts <- nrow(scores)
-```
-
 ```{r metadata}
 table_metadata(scores) |>
   select(-Description) |>
@@ -103,14 +103,14 @@ We retrospectively categorised each week as “Stable”, “Decreasing”, or 
 
 ```{r trends,fig.cap="Trends (cases)", fig.height = 8, fig.width = 10}
 scores |>
-  filter(outcome_target == "Cases") |>
+  filter(epi_target == "Cases") |>
   trends_plot() +
   ggtitle("Cases")
 ```
 
 ```{r death-trends,fig.cap="Trends (deaths)", fig.height = 8, fig.width = 10}
 scores |>
-  filter(outcome_target == "Deaths") |>
+  filter(epi_target == "Deaths") |>
   trends_plot() +
   ggtitle("Deaths")
 ```
@@ -120,7 +120,8 @@ scores |>
 ## Variant phase identification
 
 ```{r variant-phases, fig.cap="Variant phases identified by dominant variant in each location and week"}
-variant_phases <- classify_variant_phases() # see: R/utils-variants.R
+# see: R/utils-variants.R
+variant_phases <- classify_variant_phases() 
 variant_phases |>
     ggplot(aes(x = target_end_date, y = location, fill = VariantPhase)) +
     geom_tile() +
@@ -166,3 +167,16 @@ knitr::include_graphics(here("output", "plots", "check_Deaths.pdf"))
 plot_effects(results$effects, 
              variables = c("Trend", "Location", "VariantPhase"))
 ```
+
+### Results on the natural scale
+
+We present results from scoring forecast error on the natural scale (difference between observation and prediction in count of case or death incidence), from which the WIS is calculated.
+
+```{r scores-natural}
+scores <- process_data(scoring_scale = "natural")
+ensemble <- scores |>
+  filter(grepl("EuroCOVIDhub-ensemble", Model))
+scores <- scores |>
+  filter(!grepl("EuroCOVIDhub-", Model))
+print_table1(scores)
+```