Emergence

Even though our disease model follows simple rules, it can still produce subtle and unexpected behavior. Such behavior is called emergence. In nature, there are many examples of complex systems which produce emergent behavior.

Extending our model

Last time, we had a few ideas for developing the model, such as having disease immunity wear off after a while (so recovered people become susceptible again), and adding death. Here are the rules:

• Each square represents a person.
• Grey means someone is susceptible (they can get sick), red means they are infected, blue means they recovered, and violet means they died.
• On each turn, each infected person has a chance of infecting their susceptible neighbors.
• On each turn, each infected person has a chance of recovering.
• Recovered people are immune from getting sick, but their immunity wears off after a while, and they become susceptible again.
• Infected people have a chance of dying.

Making claims

We can use models to make claims about how disesases work. Answer each of the following questions, providing evidence from your model. In many cases, the best evidence will be a download of the population health plot, along with the disease parameters (infection rate, recovery rate, death rate, and immunity time).

1. What properties allow a disease to survive within a population?
2. What properties allow a disease to sustain a high infection rate within a population?
3. What properties make a disease particularly deadly?
4. Can a rare disease (with very few infected individuals) survive for a long time? What is the lowest steady percentage of infected individuals you can sustain for at least 1000 turns?
5. Can any disease with a death rate above zero last forever in this model?