add steps to part two

Author: avallecam

instructors/data/04-practical-activity-2.R

@@ -3,20 +3,35 @@
 # Practical 4
 # Activity 2
 
+# step: fill in your room number
 room_number <- #<COMPLETE> replace with 1/2/3/4
 
 # Intervention ---------------------------------------------------------
 
 rownames(socialcontact_matrix)
 
-test_intervention <- epidemics::intervention(
-  #<COMPLETE>
+# step: create the intervention object:
+# identify if you need to keep: 
+# epidemics::intervention() or epidemics::vaccination()
+# then add:
+# - name of the intervention
+# - type of intervention ("rate" or "contacts"), if needed
+# - time when the intervention begins and ends (as values or matrix*)
+# as given in table of inputs
+# - reduction or vaccination rate (as values or matrix*)
+# *if matrix, values follow same order as in the social contact matrix
+test_intervention <- epidemics::intervention(#<COMPLETE>
+)
+test_intervention <- epidemics::vaccination(#<COMPLETE>
 )
 
 test_intervention
 
 # Run {epidemics} ---------------------------------------------------------
 
+# step: add the intervention argument
+# as a list (for interventions against contacts or transmission rate) 
+# or as an object (for vaccination)
 simulate_intervention <- epidemics::model_default(
   population = population_object,
   transmission_rate = transmission_rate,
@@ -32,6 +47,8 @@ simulate_intervention
 
 # Plot all compartments --------------------------------------------------
 
+# step: paste plot and table output in report
+
 simulate_intervention %>%
   ggplot(aes(
     x = time,
@@ -55,16 +72,22 @@ epidemics::epidemic_peak(data = simulate_intervention)
 # Visualize effect --------------------------------------------------------
 # Plot new infections 
 
+# step: 
+# add intervention name
+# if your intervention is vaccination, then
+# activate the argument compartments_from_susceptible
+# run and paste plot output in report
+
 infections_baseline <- epidemics::new_infections(
   data = simulate_baseline,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 infections_intervention <- epidemics::new_infections(
   data = simulate_intervention,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 # Assign scenario names

instructors/fig/04-practical-instructor-2.R

@@ -3,6 +3,7 @@
 # Practical 4
 # Activity 2
 
+# step: fill in your room number
 room_number <- 1 #valid for all
 
 # Group parameters -------------------------------------------------------
@@ -19,6 +20,16 @@ intervention_duration <- 250 # change (e.g., range 150-250)
 
 rownames(socialcontact_matrix)
 
+# step: create the intervention object:
+# identify if you need to keep: 
+# epidemics::intervention() or epidemics::vaccination()
+# then add:
+# - name of the intervention
+# - type of intervention ("rate" or "contacts"), if needed
+# - time when the intervention begins and ends (as values or matrix*)
+# as given in table of inputs
+# - reduction or vaccination rate (as values or matrix*)
+# *if matrix, values follow same order as in the social contact matrix
 test_intervention <- epidemics::intervention(
   name = "School closure",
   type = "contacts",
@@ -31,6 +42,9 @@ test_intervention
 
 # Run {epidemics} ---------------------------------------------------------
 
+# step: add the intervention argument
+# as a list (for interventions against contacts or transmission rate) 
+# or as an object (for vaccination)
 simulate_intervention <- epidemics::model_default(
   population = population_object,
   transmission_rate = transmission_rate,
@@ -46,6 +60,8 @@ simulate_intervention
 
 # Plot all compartments --------------------------------------------------
 
+# step: paste plot and table output in report
+
 simulate_intervention %>%
   ggplot(aes(
     x = time,
@@ -69,16 +85,22 @@ epidemics::epidemic_peak(data = simulate_intervention)
 # Visualize effect --------------------------------------------------------
 # Plot new infections 
 
+# step: 
+# add intervention name
+# if your intervention is vaccination, then
+# activate the argument compartments_from_susceptible
+# run and paste plot output in report
+
 infections_baseline <- epidemics::new_infections(
   data = simulate_baseline,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 infections_intervention <- epidemics::new_infections(
   data = simulate_intervention,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 # Assign scenario names
@@ -169,13 +191,13 @@ epidemics::epidemic_peak(data = simulate_intervention)
 infections_baseline <- epidemics::new_infections(
   data = simulate_baseline,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 infections_intervention <- epidemics::new_infections(
   data = simulate_intervention,
   # compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 # Assign scenario names
@@ -264,13 +286,13 @@ epidemics::epidemic_peak(data = simulate_intervention)
 infections_baseline <- epidemics::new_infections(
   data = simulate_baseline,
   compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 infections_intervention <- epidemics::new_infections(
   data = simulate_intervention,
   compartments_from_susceptible = "vaccinated", # if vaccination
-  by_group = FALSE # if TRUE, then age-stratified
+  by_group = FALSE # if TRUE, then age-stratified output
 )
 
 # Assign scenario names