diff --git a/episodes/describe-cases.Rmd b/episodes/describe-cases.Rmd
index 10ebe134..bac21804 100644
--- a/episodes/describe-cases.Rmd
+++ b/episodes/describe-cases.Rmd
@@ -255,9 +255,10 @@ confidence interval and using 100 bootstrap samples.
 
 ## Visulaziantion with ggplot2
 
-`{incidence2} produces basic plots for epicurves, but additional work is required to create well-annotated graphs. However, using the {ggplot2} package, you can generate more sophisticated and better-annotated epicurves.
-{ggplot2} is a comprehensive package with many functionalities, but we will focus on three key elements essential for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation.
-The example below demonstrates how to configure these three elements for a simple `{incidence2} object.
+
+`{incidence2}` produces basic plots for epicurves, but additional work is required to create well-annotated graphs. However, using the `{ggplot2}` package, you can generate more sophisticated and better-annotated epicurves.
+`{ggplot2}` is a comprehensive package with many functionalities, but we will focus on three key elements essential for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation.
+The example below demonstrates how to configure these three elements for a simple `{incidence2}` object.
 
 ```{r, message=FALSE, warning=FALSE}
 breaks <- seq.Date(