- Max Dupont
- Loïc Niederhauser
- Lucille Niederhauser
- Valentin Borgeaud
- Lucie Castella
- Isis Bou Jaoude
- ThibaultNiederhauser Niederhauser
- Amaia Soubelet
Those past days we have seen masses of people going out, meeting, and showing incredible ingenuity to sneak pass government regulations.
As a team we have come up with two solutions for that.
Informations first: We know that people are not evil. Thus if they don't respect the recommendations it might just be that they don't understand how they put people in danger. The logical solution is to help them understand which behavior can make a difference.
Positive reinforcement: All measures that have been take aim to oppresse the user. We want to help reward them instead of punishing them.
What it does
Informs users: it shows and explains why measures/recommendations are taken through the use of interactive pandemic spread simulations where users can change different parameters (type of restrictions, how well people apply them, social distancing, shops/schools closed or open, etc.). The simulations models the evolution of the epidemics in a chosen country from today into the future. This allows the users to have a better grasp and understanding of the impact of restrictions and of their behaviors. The users can also access to a quiz page, that informs them about Covid19 in an interactive way. In addition, the webapp shows the current state of the propagation of the virus in the world.
Positive reinforcement: it encourages people to apply the recommended measures by rewarding users when they record their good habits on the app. The reward is implemented through gamification (trophies, points, competition with other users, ...) in order to highlight the positive impact of users’ behaviors
How we built it
The webapp is developed with js, css and html. The webapp can simulate the spread of the epidemics based on users' chosen parameters. The epidemics evolution is computed on python.
Challenges we ran into
Modeling and simulating the effect of restrictions and individual behaviors on the spread of the epidemics was not an easy task, since many parameters/behaviors can only be simplified or estimated. The team had no great experience with webapp design, this was a big challenge to overcome.
Accomplishments that we are proud of
We developed a tool that is different from many other Covid-19 information applications. We do not only inform people about the dynamics of the epidemics and the taken mesures, but we encourage the users to have good behaviors through reward and positive reinforcement. We are convinced that such a positive approach could have better impact on the population than imposed restrictions.
What we learned
How to build a webapp, how to model an epidemics, how to apply the mathematical theory behind epidemics spreading in a realistic way.
If the team wants to pursue the project, here are some improvements that can be done:
- Add some features: display how the epidemic would spread if everyone had the same behavior as the user, estimate the number of infections/deaths avoided by the users (compared to a "normal" behavior), add trophies, etc.
- Work on the visual aspect of the webapp
- Link app pages together
- Model new parameters that can affect the epidemics spread
If you want to see our project find on github
Try It out