JustWearIt.FYI visualizes how wearing a mask reduces the spread of COVID-19. The simulation is built using p5.js and vanilla HTML / CSS.
Important: While our simulation accounts for basic factors in COVID-19 spread, it is intended to raise awareness and should not be treated as a scientific model. You can learn more from the experts here.
The simulation takes into account the following factors when modeling COVID-19 spread:
maskPercentage: Percentage of population that wear a mask.maskEffectiveness: How effective a mask is at stopping a sick particle from spreading COVID.recoveryPercentage: Likelyhood of a particle recovering after getting sick.avgIllnessDuration: Average illness duration in weeks of the sickness. Slightly randomized for each particle.secondsPerWeek: How long a week takes to pass.transmissionRate: Likelyhood of a sick particle transmitting the virus when in range of another particle.transmissionDistanceScale: Minimum transmission distance. Transmission is attempted only once when a particle comes within range. Scaled for window size.populationHealth: The initial percentage of healthy people.isHealthyproperty is randomly assigned for each particle according to this probability.speedPercentage: Average speed of a particle. Scaled for window size. Randomized for each particle.sizePercentage: Size of a particle. Unrelated to simulation dynamics. Scaled for window size.densityScale: Density of particles. Scaled for window size.
When a healthy particle comes within range of a sick particle, the sick particle transmits as follows:
var likelyhood = transmissionRate;
if (this.isWearingMask) {
likelyhood *= (1 - maskEffectiveness);
}
Note that infection likelyhood is dependent on if the sick particle is wearing a mask, not the healthy particle. This is because masks do more to prevent sick people from spreading the virus than healthy people from getting it.
The transmission is attempted a single time when a healthy particle comes within range of a sick particle, instead of continously while the two are in-range. While both strategies could work, the later means that slowing the speed of the particles would increase transmission rate, as they would now be in-range for longer. This doesn't work great in practice, so a single tranmission attempt is used instead. Once two particles move out of range, another transmission attempt will occur if they move back in range at a later point.
Here's a quick overview of features we'd like to add. See Issues for more details. If you're able to help, that would be much appreciated :)
- City Picker: The site would pull in city data for mask usage, population density, population health, etc. and let you pick a city to simulate.
- Localizations: Translate the website into different languages.
- Custom Donation Box: Collect donations through Stripe and split between several COVID-related charities. Haven't found a great framework for this, so currently the site links out to Omaze.
This website was created by Matt Moss and Maas Lalani. It was inspired by this article in The Atlantic and this interactive essay by Kevin Simler (the project is not associated with any of the inspirations mentioned).
If you've got any feedback or questions, email us or reach out on Twitter!