COVID-Symulator is a project developed by the team Orion Wafford and Ethan Vong. We wanted to show how the spread of Covid-19 could impact a group of people occupying a building, such as a school, based on the data from various sites. Below is a screen shot showing the project. Below that is a button you can use to run the project for yourself.
Now, imagine a school, church, or just an office building. People enter those buildings and proceed to rooms. Along the way, they come into contact with other people. It is at these times the virus can be spread. Using numbers from various sites,we set the simulator up to show how the virus might spread. For this first version, we made a floor plan resembling a school.
Now various assumptions have been used to design this simulator. You can see these assumptions below. The numbers, such as "Percentage of transmission occurring prior to symptom onset", is data we used from the reference below, but we welcome more solid numbers or updated numbers from the CDC, WHO or anyone in the scientific community.
So now, we invite you to use the COVID-Symulator project. Setup the school with the follwing: a number of class periods, a number of students from 1-999,and a starting point of 1 or more symptomatic students. You can choose to have them wear a mask or not and practice social distancing. We would recommend running without mask and social distancing first just to see how the virus will spread. Then use masks and social distancing to see the impact of how well they protect the students.
We welcome all comments and feedback. We really hope people find this project useful in this current pandemic. If anyone wishes to give a map of their building, we can integrate that to show how this might impact your own building or school. Using this, you can see where hot spots might occur when people are moving around.
Below are assumptions we used when making the app. These are assumptions and number we pulled from many of the references listed above. If the CDC, WHO, or any othe scientific organization wish to help us refind out number please contact us at firstname.lastname@example.org
Assumption 1: "Potential infected" students cannot spread infection. At the end of a day, "Potential infected" students are then marked either "Non-infected", "Asymptomatic", or "Presymptomatic".
Assumption 2: "Asymptomatic", "Presymptomatic", and "Symptomatic" students always mark non-infected students as "Potential infected" when within close proximity.
Assumption 3: When students are not wearing masks, "Potential infected" students have a 50% chance to become infected and a 50% chance to become non-infected.
Assumption 4: When students are wearing masks, "Potential infected" students have a 35% to become infected and a 65% to become non-infected.
Assumption 5: Infected students have a 40% chance to become "Asymptomatic"(purple) and a 60% chance to become "Presymptomatic"(orange).
Assumption 6: Within 1 to 7 days, an "Asymptomatic" student will be cured.
Assumption 7: Within 1 to 12 days, a "Presymptomatic" student will turn "Symptomatic".
Assumption 8: Students do not use restroom, wander halls, they all take lunch at the same time.
Assumption 9: Students do not obtain infection from people at home.
Assumption 10: Students do not obtain infection from surfaces.
Assumption 11: Students in class will always try to sit as far away from each other as possible.
Assumption 12: Students always attend lunch half-way through the day.
Assumption 13: Students can only be infected within the school premesis. (Within the camera viewport).
Below are links to information we used to find numbers and data to do our Covid-19 calculations
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