diff --git a/episodes/model-choices.Rmd b/episodes/model-choices.Rmd
index ba8f3456..b33f6b17 100644
--- a/episodes/model-choices.Rmd
+++ b/episodes/model-choices.Rmd
@@ -374,7 +374,10 @@ output_samples <- Map(
 
 output_samples <- bind_rows(output_samples) # requires the tidyverse package
 
-ggplot(output_samples[output_samples$compartment == "infectious", ], aes(time, value)) +
+ggplot(
+  output_samples[output_samples$compartment == "infectious", ],
+  aes(time, value)
+) +
   stat_summary(geom = "line", fun = mean) +
   stat_summary(
     geom = "ribbon",
diff --git a/episodes/simulating-transmission.Rmd b/episodes/simulating-transmission.Rmd
index 98f10a1d..1348de63 100644
--- a/episodes/simulating-transmission.Rmd
+++ b/episodes/simulating-transmission.Rmd
@@ -516,7 +516,10 @@ output_samples <- bind_rows(output_samples)
 3. Calculate the mean and 95% quantiles of number of infectious individuals across each model simulation and visualise output
 
 ```{r  plot, fig.width = 10}
-ggplot(output_samples[output_samples$compartment == "infectious", ], aes(time, value)) +
+ggplot(
+  output_samples[output_samples$compartment == "infectious", ],
+  aes(time, value)
+) +
   stat_summary(geom = "line", fun = mean) +
   stat_summary(
     geom = "ribbon",