This model simulates the impact of social distancing (SD) on infectious disease outbreak dynamics in a population. In particular, it allows users to explore the effects of different social distancing spaces and the percentage of people who practice SD on the infectious disease outbreak dynamics.
Grades: 9-12;
The model starts with a human population of 600 persons in which one person (orange color) is infected, and the rest of the people are susceptible (green color). The infected case passes the disease to one of the susceptible people within a radius of 1.5 at a transmission rate of 90%. The infected people are able to transmit the disease for 14 days. By the 15th day of being infected, the infected people either die (disappear from the model) at mortality of 20% or recover and become immunized (blue color).
Buttons, Sliders, and Switches:
The “Set up/Reset” button is self-explanatory. So are the buttons of “Run/Pause” and “Run a day”.
The “Watch 1 Infected Case” button allows you to focus on a single infected person. You may see this person eventually recover or die.
The slider " social distancing" determines the space that people need to maintain when practicing SD. People do not practice social distancing when “social distancing” is 0.0. When “social distancing” is greater than 0, people who practice SD maintain a corresponding distance from another person, if possible.
The slider “%-People-practicing-SD” determines the likelihood that people practice SD. No one practices SD when “%-People-practicing-SD” is 0.0.
First, choose the desired value for "social distancing" and "%-People-practicing-SD".
Click on "Set up/Reset", then "Run/Pause".The model is initially set to stop on the 180th day. Change the number in "Time" if you want to run the model for a longer or shorter time.
Observe the infection changes in the population in the plot and monitors.
Use "Run one day" to run the model in a controlled way and collecting day-by-day data.
THINGS TO TRY
There are so many things you can try in this model. Here are only very a few quick ideas:
How far should people stay away from each other to decrease infection if the disease is passed to other people within a radius of 1.5?
How many percent of people should practice social distancing to significantly flatten the infection curve?
Dr. Lin Xiang creates this module at the University of Kentucky in 2019. If you mention this model in a publication, we ask that you include the citations below.
Xiang, L. (2020). Infectious Disease Outbreak-Social Distancing. Department of STEM Education, University of Kentucky, Lexington, KY.
Questions? Comments? Email us.