Short tasks (10-15 minutes)

1. Design a disease with an Infectivity of zero. Run the simulation and observe the results. Change any factor besides the Infectivity and run the simulation again. What do you notice?
2. Investigate the effect of the average overall health of the population on the spread of disease. Keep all sliders at their default settings, but run the simulation twice with different values for overall population health selected.
3. Use the simulation to demonstrate how a novel (new) disease is more devastating to a population than a disease that has been around for a few years. (Hint: think about immunity.)
4. Create a very deadly and highly contagious disease. Run that disease through the simulation a few times with different population densities. (You can adjust population density either by changing the initial population without changing the grid size, or changing the grid size without changing the initial population.) How are the results similar? How are the results different? Explain.
5. Investigate the effect of three different levels of social distancing on the simulation. Use the default settings and compare.
6. Manipulate the model to demonstrate how a disease can spread within members of the same household. What sliders are irrelevant once a member of a household is infected. Show this with the model.
7. Using the default population grid size; design a disease that kills the entire population. What factors were most important to incorporate in this task?
8. Design a disease in which herd immunity quickly develops with little loss of life. What factors contributed?
9. Design a disease where herd immunity develops, but not until many lives have been lost. What factors contributed?

Longer tasks (45-60 minutes)

1. Find at least three ways that you can create a disease that will not last 100 days. What factors contribute to the disease being choked out so soon?
2. Design a disease that will thrive in the population while being relatively mild and killing very few people. What factors played a role in the disease being so successful?
3. Investigate the effect of different population densities on the spread of disease. What challenges do cities face when it comes to the spread of disease due to population density? Use evidence from the simulation.
4. Research a disease that is not very contagious, but has a very high mortality rate. Design a model of that disease and run it through the simulation. Use the data from the simulation to show that you have completed the task.
5. Design a disease that will last for over 1000 days while reducing the initial population by at least 50%. Introduce a vaccine with a high rate of effectiveness at or around day 1000. Continue the simulation and evaluate the data for the next 1000 days. Explain how and why the trends changed.
6. Research one of the following diseases and adjust the model to accurately represent how it behaves in the real world: ebola, measles, chickenpox, or the common cold.
7. Create a new disease and run the simulation for at least 50 cycles. Pause the simulation and analyze the data. Create two two-minute news broadcasts that analyze the data in completely different ways; the first in very optimistic terms and the second very pessimistically. Be sure to use actual data from the simulation. Record your presentation as a video or present it live in class. This assignment could be extended for several days.
8. Do both of the shorter activities #8 and #9. Use data gathered to explain when it might be appropriate to employ drastic societal measures like shelter-in-place orders, and when it might be best to let the disease run its course.