Merge pull request #58 from ssi-dk/add_burden_level_vignette

Add burden level vignette

.github/workflows/pkgdown.yaml

@@ -55,7 +55,7 @@ jobs:
         shell: Rscript {0}
 
       - name: Upload artifact
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: pkgdown
           path: docs/
@@ -69,7 +69,7 @@ jobs:
       - uses: actions/checkout@v3
 
       - name: Download pkgdown output
-        uses: actions/download-artifact@v3
+        uses: actions/download-artifact@v4
         with:
           name: pkgdown
           path: docs

.github/workflows/test-coverage.yaml

@@ -44,7 +44,7 @@ jobs:
 
       - name: Upload test results
         if: failure()
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: coverage-test-failures
           path: ${{ runner.temp }}/package

DESCRIPTION

@@ -30,9 +30,11 @@ RoxygenNote: 7.3.2
 URL: https://github.com/ssi-dk/aedseo, https://ssi-dk.github.io/aedseo/
 BugReports: https://github.com/ssi-dk/aedseo/issues
 Suggests:
+    grid,
     ISOweek,
     kableExtra,
     knitr,
+    mem,
     rmarkdown,
     testthat (>= 3.0.0),
     tidyr,

NEWS.md

@@ -28,7 +28,8 @@
   - `vignette("generate_seasonal_wave")`,
   - `vignette("aedseo")`,
   - `vignette("seasonal_onset")`
-  providing a comprehensive walkthrough of the application of the functions provided by the `aedseo` package with detailed explanations and illustrative examples (#56, #57).
+  - `vignette("burden_levels")`
+  providing a comprehensive walkthrough of the application of the functions provided by the `aedseo` package with detailed explanations and illustrative examples (#56, #57, #58).
 
 * Improved the autoplot function which can now visualise dates as days, weeks and months on the x-axis with the `time_interval` argument (#56).
 

R/seasonal_burden_levels.R

@@ -20,7 +20,7 @@
 #' The `conf_levels` are specific for each method:
 #'   - for `intensity_levels` only specify the highest confidence level e.g.: `0.95`, which is the highest intensity
 #'     that has been observed in previous seasons.
-#'   - for `peak_levels` specify three confidence levels e.g.: `c(0.5, 0.9, 0.95)`, which are the three confidence
+#'   - for `peak_levels` specify three confidence levels e.g.: `c(0.4, 0.9, 0.975)`, which are the three confidence
 #'     levels low, medium and high that reflect the peak severity relative to those observed in previous seasons.
 #' @param decay_factor A numeric value between 0 and 1, that specifies the weight applied to previous seasons in level
 #' calculations. It is used as `decay_factor`^(number of seasons back), whereby the weight for the most recent season

vignettes/aedseo.Rmd

@@ -38,7 +38,6 @@ More information about the function can be found in the `vignette("generate_seas
 ```{r, include = FALSE}
 withr::local_seed(222)
 # Construct an 'tsd' object with time series data
-set.seed(222)
 tsd_data <- generate_seasonal_data(
   years = 3,
   start_date = as.Date("2021-10-18"),
@@ -170,7 +169,8 @@ Detailed information about each function and their respective arguments can be f
 ```{r}
 seasonal_output <- combined_seasonal_output(
   tsd = tsd_data,
-  disease_threshold = 140
+  disease_threshold = 140,
+  method = "intensity_levels"
 )
 ```
 The default function calculates onset and burden for the current season. If it is desired to see calculations for all previous seasons, the `only_current_season` argument should be set to `FALSE`.
@@ -199,3 +199,7 @@ plot(
   time_interval = "3 weeks"
 )
 ```
+
+Using the `intensity_levels` method to define burden levels, the Outbreak is expected to fall within the `low` or `medium`
+category. This is because the `very low` threshold is the disease-specific threshold, which must be surpassed for five
+consecutive weeks along with a significant positive growth rate.