COVID Safety Sim (ALPHA)

Source of Data: The New York Times
Range 0 → 50k
Range 0 → 50k
Range 30 → 300
Slide the above bars to make a prediction.


About this Sim

The Embodied Games lab in Psychology is creating two COVID-19 simulations: a Simple and a more Complex one.

Simple Goal. In the simple sim, we want to reinforce the concept of physical distancing and to encourage the wearing of masks.

For the Simple Sim:

For the first three sim variations: 1) watch a mask simulation over time, then 2) you can control the distance of people from each other. Finally in 3) called BOTH, you can control both masks and the distance between various people.

What is R naught?

R(0) is reproducibility. It is a ratio. On average, it is the number of new cases that an existing case (single person) generates over a certain amount of time.

R(0) = new cases/existing cases

For example:

If 4 new cases show up for every 2 known cases, the R(0) will be 4/2 = 2.0.

If 7 new cases show up for every 2 known cases, the R(0) will be 7/2 = 3.5.

The R(0) is really a range of numbers. In the U.S. it varies by location, but a good estimate (as of the summer of 2020) is 2.0. Every infected person will probably infect two other people, thus, these sims run with an R(0) of 2.

What is Quarantine level?

To show how humans have some control over transmissibility you can choose three levels for quarantine.

High - The door to the house on top never opens and those people never become infected.

Mid - The door in the middle quarantine house opens half way. This implies that people leave later, and one or two will stay inside.

Use the GRAPH. Notice how the curve on the graph is affected when you change quarantine levels.

Low – The door to the low quarantine house opens fully and all people leave quickly. Notice how the graphs of your last two sims are saved for a comparison.

For Complex Sim.

Complex Goal. In the up-coming (release in fall) complex model/sim, learners will have control over more parameters and comparison charts. They can run through many sims and can compare outcomes. It will be a teaching tool for R(0) and the SEIR equation.

Team Leader:

Lead Programmer:

  • Rick Cheng-Yu Chung (CIDSE)

Faculty Advisors:

Industry Advisors:

  • Xavier Apostol
  • Dennis Bonilla at Baltu


  • Hannah Bartolomea (AR focus)
  • Jude Rayan (AR focus)
  • Lawrence Hu (Edson CONHI)
  • Man Su
  • Ricardo Nieland
  • Vannessa Ly
  • Tian


Contact Us: Contact[at]

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