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Worksheet: Using Vaccines to Fight Outbreaks

Part 1: What are vaccines and what do they do?

Watch these videos and answer questions 1-4.
1. List at least three ways the acquired immune system is different from the innate immune system.
2. Explain how vaccines interact with the acquired immune system and how that benefits individuals.
3. List one key similarity and one key difference between a vaccine and the pathogen it protects against.
4. Describe what each phase of a vaccine trial accomplishes.
Phase 1 Tens of individuals
Phase 2 Hundreds of individuals
Phase 3 Thousands of individuals

Part 2: How do vaccines affect outbreaks?

SimPandemic is an online simulator that lets you explore how various factors change a pandemic's evolution.
5. Fill out the Outcomes for Scenarios 1-3 based on the graphs and tables in scenarios 1-3. You will use this information to support your claims in other questions. (Note: SimPandemic reports economic outcomes of the pandemic, too. While this feature is not used in this lesson, you might find it interesting to take look at.)

Scenario 1: COVID-19 Outbreak with No Interventions

Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365

Scenario 2: COVID-19 Introduced After a Strong Vaccination Campaign

Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365

Scenario 3: Strong COVID-19 Vaccination Campaign During an Outbreak

Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365
6. In which scenario (1, 2, or 3) is someone most likely to get sick? In which scenario are they least likely to get sick? Support your claims using evidence from your answers from #5.
7. In scenarios 2 and 3, the simulation settings are such that it takes 30 days to run the vaccination campaign and 14 days to develop immunity. Explain the logic behind these setting choices. Hint: there are two reasons, one is biological and one is logistical.
8. In scenario 2, if you were to draw a line on the graph representing vaccinated individuals, describe where you would place it on the graph relative to the line representing immune individuals (orange line). Explain your logic.
9. How might an effective vaccine administered to a large percentage of the population during a pandemic change the pandemic’s outcome? Support your claim(s) using evidence from your answers from #5.

Part 3: How do the parameters of a vaccination campaign change outcomes for individuals and populations?

In this part, you will use the Sandbox to run your own simulations with settings you put in. If you have questions about how to use the Sandbox, read the FAQ. Make sure to save your work as you go (see FAQ).
  • When you have completed all your simulations, enter the URL for them here for your teacher to see:
  • Use what you learn from your own simulations to answer questions 10-12.
10. Run your own scenarios to investigate the effects of two different vaccine variables on the outcomes of an outbreak that is underway: how effective the vaccine is and what percentage of the population gets vaccinated.
To get started, press the Customize Settings button.
  • In Population Statistics, increase the "Number already infected (Adult)" from 1 to 10.
  • In Vaccine, set "Implement vaccine" to "Yes."
  • In Vaccine, set "Start day" to 45, "How long does it take to vaccinate everyone?" to 30, and "How long does it take for the vaccine to become effective?" to 14 days.
  • Experiment with different "Percentage vaccinated" and "Effectiveness" settings. A good starting range for percentage vaccinated is low =40% and high =75%. A good starting range for effectiveness is low =30% and high =80%.
Record your data below:

Scenario: High Effectiveness, High % Vaccinated

Settings:
Effectiveness (%)
Percentage vaccinated (%)
Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365

Scenario: High Effectiveness, Low % Vaccinated

Settings:
Effectiveness (%)
Percentage vaccinated (%)
Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365

Scenario: Low Effectiveness, High % Vaccinated

Settings:
Effectiveness (%)
Percentage vaccinated (%)
Outcomes:
Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365

Scenario: Low Effectiveness, Low % Vaccinated

Settings:
Effectiveness (%)
Percentage vaccinated (%)
Outcomes: Total Infections per 100,000
Hospitalized (% of capacity)
Total Deaths Caused by Pandemic per 100,000
Total Number Immune per 100,000 at Day 365
11. Based on your data, does it matter how effective a vaccine is? Support your claim using evidence.
12. Individuals who are too young or whose immune systems are too weak cannot be vaccinated. How important do you think it is on a population level to vaccinate everyone who can be vaccinated? Support your claim using evidence from the scenarios you ran and/or scenarios 1-3.

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