Refine placeholders

instructors/03-practical-tutors.qmd

@@ -567,7 +567,7 @@ From the plot of cumulative cases by day for each simulated chain:
 | 5 | R = 1.5, k = 0.1 | 65 | ~890 | ~50 days |
 | 6 | R = 1.5, k = 0.5 | 216 | ~850 | ~90 days |
 
-Individual-level variation in transmission means that although the probability of extinction is high, new index cases also have the potential for explosive regrowth of the epidemic. This is reflected above: most simulated chains die out quickly, while a small number — especially at low dispersion (k) — cross the 100-case threshold.
+Individual-level variation in transmission means that although the probability of extinction is high, new index cases also have the potential for explosive regrowth of the epidemic. This is reflected above: most simulated chains die out quickly, while a small number, especially at low dispersion (k), cross the 100-case threshold.
 
 # Continue your learning path
 
@@ -589,4 +589,4 @@ Epi R handbook episode on {epicontacts} to visualise transmission chains in time
 :::
 
 
-# end
+# end

instructors/data/01-practical-activity-2.R

@@ -50,8 +50,8 @@ dat_delays %>%
 dat_incidence <- dat_linelist %>%  
   # Transform from individual-level to time-aggregate
   incidence2::incidence(
-    date_index = #<COMPLETE>,
-    groups = #<COMPLETE>, # the categorical variable
+    date_index = #<COMPLETE>, # add one or more
+    groups = #<COMPLETE>, # add one or more
     interval = #<COMPLETE>,
     complete_dates = TRUE
   )
@@ -68,7 +68,7 @@ dat_incidence %>%
     fill = #<COMPLETE>, # the categorical variable # <KEEP OR DROP>
     #nrow = 1, # 1 or 2 <KEEP OR DROP>
     show_cases = FALSE, # <KEEP OR DROP>
-    angle = 45, # <KEEP OR DROP>
+    #angle = 45, # <KEEP OR DROP>
     n_breaks = 5 # <KEEP OR DROP>
   )