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‎instructors/04-practical-tutors.qmd‎

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@@ -51,9 +51,9 @@ This practical is based in the following tutorial episodes:
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This practical has three activities.
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## Activity 1: Generate disease trajectories
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## Activity 1: Generate disease trajectories across age groups
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Generate disease trajectories of **infectious individuals** and **new infections** using the following available inputs:
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Generate disease trajectories of **infectious individuals** and **new infections** across age groups using the following available inputs:
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- Social contact matrix
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- Age group of the infectious population
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Within your room, Write your answers to these questions:
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- What are the time and size of the epidemic peak for *infectious individuals* in each age group?
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- Compare and describe the similarities and differences between these two outputs: the epidemic peak of *infectious individuals* across age groups, and the plot of *new infections* across age groups.
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- Modify the basic reproduction number (R₀) from 1.46 to 1.1 or 3. What changes do you observe in the time and size of the peak of *new infections*?
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- Compare: What differences do you notice compared to the outputs from other rooms (if available)?
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- Compare and describe the similarities and differences between these two outputs: the table with epidemic peak of *infectious individuals* across age groups, and the plot of *new infections* across age groups.
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- Compare: What differences do you observe compared to the outputs from other rooms (if available)?
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### Inputs
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Room 1
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* across age groups | |
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Write your answers to the questions above:
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Room 2
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* across age groups | |
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Write your answers to the questions above:
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Room 3
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* across age groups | |
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Write your answers to the questions above:
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+ Both plot trajectories seem to share the time of peak.
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+ Other packages that can estimate trend of new infections are `{EpiNow2}` and `{epichains}`.
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Modify the basic reproduction number (R₀):
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| R = 1.1 | R = 3 |
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|---|---|
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| ![image](https://hackmd.io/_uploads/H1UupFOAyl.png) | ![image](https://hackmd.io/_uploads/ryVoat_R1l.png) |
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- An epidemic with `R₀ = 1.1` has a days delayed and smaller outbreak based on number of infections (day 1200, 9000 new infections), compared with `R₀ = 3` with an earlier and higher peak than `R₀ = 1.46` (day 100, 1,000,000 new infections).
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Comparison between rooms:
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| Vietnam | Zimbabwe |
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## Activity 2: Compare interventions
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## Activity 2: Compare the baseline scenario with a single intervention
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Compare the disease trajectories of **new infections** against an intervention using the following available inputs:
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Compare the disease trajectories of **new infections** in the whole population with those under an intervention, using the following available inputs:
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- Time to start the intervention
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- Duration of the intervention
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- Type of intervention (on contacts, on transmission, or vaccination)
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- Type of intervention (on contacts, on transmission rate, or vaccination)
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- Reduction effect or rate of vaccination
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Within your room, write your answers to these questions:
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- How can the start of interventions (early vs. late) affect the timing and size of the peak of new infections?
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- Is the impact of the intervention, as shown in these results, what you would expect? Why or why not?
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- Does the impact of the intervention, compared to the baseline, align with your expectations? Why or why not? Use all the available outputs.
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- Interpret the results: How would you explain these findings to a decision-maker?
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- Compare: What differences do you observe compared to the outputs from other rooms (if available)?
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|---|---|---|
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| 1,2,3 | Zimbabwe | <https://doi.org/10.5281/zenodo.3886638> |
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| Room | Intervention | Reduction/Vaccination rate | Early start (day) | Late start (day) | Duration (days) |
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|---|---|---|---|---|---|
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| 1 | School | Age 0–19: 0.5; Age 20+: 0.01 | 100 | 200 | 250 |
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| 2 | Mask | All ages: 0.163 | 100 | 200 | 250 |
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| 3 | Vaccination | All ages: 0.001 | 100 | 200 | 250 |
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| Room | Intervention | Reduction/Vaccination rate | Time begin (day) | Duration (days) |
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|---|---|---|---|---|
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| 1 | School closure | Age 0–19: 0.5; Age 20+: 0.01 | 200 | 250 |
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| 2 | Mask mandate | All ages: 0.163 | 200 | 250 |
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| 3 | Vaccination | All ages: 0.001 | 200 | 250 |
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::: {.content-visible when-format="docx"}
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Room 1
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population | |
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Write your answers to the questions above:
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Room 2
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population | |
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Write your answers to the questions above:
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Room 3
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Plot of *all compartments* and age groups | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population | |
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Write your answers to the questions above:
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## Activity 3: Combine interventions (Optional)
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## Activity 3: Combine multiple interventions (Optional)
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Combine two intervention in the same simulation and compare the disease trajectories of new infections against the baseline or only one intervention. Use the intervention parameters above.
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Compare the baseline scenario with two intervention in the same simulation. Use the intervention parameters above.
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Within your room, Write your answers to these questions:
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- Interpret: How would you communicate these results to a decision-maker?
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- Compare: What differences do you identify from other room outputs? (if available)
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- Compare: What differences do you observe compared to the outputs from other rooms (if available)?
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### Inputs
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Room 1
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population comparing interventions | |
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Write your answers to the questions above:
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Room 2
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population comparing interventions | |
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Write your answers to the questions above:
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Room 3
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| output | paste here |
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| **Output** | **Paste below** |
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|---|---|
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| figure | |
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| table | |
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| Table of *infectious* across age groups | |
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| Plot of *new infections* in the whole population comparing interventions | |
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Write your answers to the questions above:
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```
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### Additional challenge
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<!-- In Activity 1
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- Modify the basic reproduction number (R₀) from 1.46 to 1.1 or 3. What changes do you observe in the outputs? (increase the total simulation time if needed) -->
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<!-- Modify the basic reproduction number (R₀):
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| R = 1.1 | R = 3 |
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|---|---|
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| ![image](https://hackmd.io/_uploads/H1UupFOAyl.png) | ![image](https://hackmd.io/_uploads/ryVoat_R1l.png) |
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- An epidemic with `R₀ = 1.1` has a days delayed and smaller outbreak based on number of infections (day 1200, 9000 new infections), compared with `R₀ = 3` with an earlier and higher peak than `R₀ = 1.46` (day 100, 1,000,000 new infections). -->
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In Activity 2
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- How can the start time or duration of interventions affect the timing and size of the peak in *new infections*? Try changing the start time from day 200 to day 100, or the duration from 250 days to 100 days.
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# Continue your learning path
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