Lesson 5 Activity 2 - Modeling Epidemics
Modeling the Spread of Disease
In this lesson students will convert their Colliding Turtles model into a simple Epidemic model by adding slider widgets and recovery. The Contagion model represents a very simplified version of an epidemic or spread of a disease. Two variables will be created: transmission rate and recovery rate. Students will later use this model to run experiments to determine if disease will spread throughout a virtual population in different scenarios.
New CS Concepts and Commands
Variables and Sliders
Watch the video above to see how to create a widget called a “slider”. Sliders are interface elements used to set variables. Variables hold values. These values are inputs to our model.
Procedures
Watch the video above to see how to create a procedure. A procedure is a named set of instructions that perform an action. Procedures must be written using a procedure block, then "called" or "invoked" using a call block.
Alter the Colliding Turtles to create an Epidemic Model
What we have already is a model in which there are agents and collisions between agents have an outcome. Now we are going to alter our Colliding turtles to make it into a model of an Epidemic. To do this, we are going to create two variables: transmission rate and recovery rate. Transmission rate is the probability that an agent will get sick upon colliding with a sick agent. Recovery rate is the probability that a sick agent gets healthy at any turn. In the colliding turtles model, turtles always reacted to a collision. In our epidemic model, we will incorporate a transmission rate so only some of the time a disease is passed from one agent to another.
Add a transmission rate to your model then test your model
Save and test your epidemic model. Try changing the transmission rate. Do you see any new outcomes or patterns?
Add in recovery then test your model again.
Save and test your epidemic model. Try changing the recovery rate. Do you see any new outcomes or patterns?
Reflection:
Reflect on the following questions:
In this lesson students will convert their Colliding Turtles model into a simple Epidemic model by adding slider widgets and recovery. The Contagion model represents a very simplified version of an epidemic or spread of a disease. Two variables will be created: transmission rate and recovery rate. Students will later use this model to run experiments to determine if disease will spread throughout a virtual population in different scenarios.
- Watch a video introduction to the Challenge
- Learn new CS concepts and commands (variables and procedures)
- Add contagion to the "Colliding Turtles" to create an Epidemic Model
- Add recovery to the Epidemic Model
New CS Concepts and Commands
Variables and Sliders
Watch the video above to see how to create a widget called a “slider”. Sliders are interface elements used to set variables. Variables hold values. These values are inputs to our model.
Procedures
Watch the video above to see how to create a procedure. A procedure is a named set of instructions that perform an action. Procedures must be written using a procedure block, then "called" or "invoked" using a call block.
Alter the Colliding Turtles to create an Epidemic Model
What we have already is a model in which there are agents and collisions between agents have an outcome. Now we are going to alter our Colliding turtles to make it into a model of an Epidemic. To do this, we are going to create two variables: transmission rate and recovery rate. Transmission rate is the probability that an agent will get sick upon colliding with a sick agent. Recovery rate is the probability that a sick agent gets healthy at any turn. In the colliding turtles model, turtles always reacted to a collision. In our epidemic model, we will incorporate a transmission rate so only some of the time a disease is passed from one agent to another.
Add a transmission rate to your model then test your model
Save and test your epidemic model. Try changing the transmission rate. Do you see any new outcomes or patterns?
Add in recovery then test your model again.
Save and test your epidemic model. Try changing the recovery rate. Do you see any new outcomes or patterns?
Reflection:
Reflect on the following questions:
- What assumptions are made in your model?
- Was there any key factor that was left out that might be important in the real world?
- Would you trust a model if your life depended on it?