Epidemiology Modeling the Spread of Disease Designing and Running Experiments Modeling and Simulation Module 1: Lesson 5

Review from Lesson 4 What could collisions represent in the real world? Why do we use probability in models?

Lesson 5 Introduction to Epidemiology. Creating a slider for transmission rate. Using the slider value to determine whether or not to pass a disease from agent to agent. Creating a slider for recovery rate. Using it to determine if a sick agent recovers.

Introduction to Epidemiology Epidemics are the spread of disease Epidemiologists study the spread of disease One way epidemiologists try to study the spread of disease is through running simulations of how a disease spreads. Then they can test different measures to stop and epidemic.

What is MRSA? MRSA is a bacteria called Methicillin resistant Staphylococcus Aureus. Staphylococcus means grape-cluster in Greek. Viewed at 10,000 x magnification.

MRSA 30% of a population has some form of staphylococcus or staph on their skin or nose, which is known as colonization. About 880,000 people are infected with MRSA each year, out of those, 3% die.

How Does it Spread? Direct physical contact

How to treat an infection The infection is usually drained, cleaned, and covered. Treated with an appropriate antibiotic. Keep it covered and don’t share personal items.

Picture of MRSA cycle MRSA transmission Colonized Susceptible (Healthy) Infected

Community-Associated MRSA Modeled as a Complex Adaptive System This is a screen shot from a simplified version of a Community-associated MRSA model developed by the University of Chicago / Argonne National Laboratory. In this model, students go from home to school and back again. The agents can be in one of three states: healthy, infected, or colonized, and can infect others if they are colonized or infected.

New in Lesson 5 CS concepts: Variables and Procedures We are going to turn our colliding turtles model to make it into an epidemic model. Let’s add a new widget called a slider. We will use this slider to hold a value called the transmission rate. This rate is the percentage of time a disease gets passed from one person to another upon collision.

Variables Variables are containers for holding values. Think of a variable as a box with a label. In StarLogo Nova, Sliders can be used to hold values and set values as inputs to the model.

Procedures Procedures are stacks of commands that perform a particular function and can be given a name.

Create a New StarLogo Nova widget

New StarLogo Nova widget Change the max value to 100 by typing in 100 next to max and hitting the return key. Click on “Edit Widgets” again to get out into editing mode and back into play mode.

Use the New Widget We now have a way to set the transmission rate through the user interface with a slider. We can get the value of transmission rate in code. How do we “pass the disease to the healthy agent 40% of the time after a collision?” [hint: remember the dice rolls]

Use the Transmission Rate Widget We are rolling a 100-sided die. If the result is less than the transmission rate, pass the disease on. How often should we roll less than the transmission rate? What kind of distribution does the roll of a single die give us?

Save and Test your Model Try changing the transmission rate? What is missing if you wanted to use your model as an experimental test bed?

Extension: Adding Recovery People sometimes recover from a disease How can we use probability to determine when a sick person recovers?

Adding Recovery Recovery will be a new procedure. At each step a sick person has a chance of recovery.

Adding Recovery Create a new slider for recovery rate. Use that slider in the recover procedure to determine whether the sick agent recovers (becomes healthy again).

Adding Recovery Create a new slider for recovery rate.

Adding Recovery Use that slider in the recover procedure to determine whether the sick agent recovers (becomes healthy again or blue).

Save and Test your Model Try changing the recovery rate? Did you see any new outcomes or patterns?

Review from Lesson 5 What does this model tell you? What is the impact of changing the transmission rate? And recovery rate? What other things move through a population like a disease?

End of Lesson 5