AVOID-19

Optimize your essential travel to avoid COVID using real-time transit, population and infection information.

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Inspiration

The Google Map API has features that display the crowdedness of locations. But it does not provide an efficient way to explore the alternative trip plans, nor does it take into account regional COVID cases. We hope this tool provides a safe and quick way to minimize COVID exposure for people who need to make essential trips.

Despite our best efforts to stay safe, essential travel comes with risk. This includes trips to the grocery store, convenience store trips, and more. When carrying out these everyday tasks, we need a way to stay safe as possible. What better way to do this than proactively? Effective trip planning can massively decrease risk of COVID exposure, so we developed a tool to do this automatically.

What it does

By providing your location and a desired destination, AVOID-19 determines the risk of your entire trip, from the moment you step out of your house to the moment you return. This risk is represented by a risk score, which will be calculated based on the number of people you are expected to encounter on your trip, and the risk of exposure from each encounter. The number of people you are expected to encounter will be calculated using both population density and transit information, alongside how many people are anticipated to be at your destination. The risk of exposure from each encounter will be calculated using the number of active infections in your area and your proximity to known public exposure sites.

Taking this risk score into account, AVOID-19 provides alternative destinations if the risk is high, and tips for your travel like times at which your location is least busy. By following this advice, you are able to minimize the risk of your essential travel.

How we built it

Front-end

  • React.js, Next.js, Vercel

Back-end

  • Firebase
  • Folium, OSMnx, Google Maps API, BestTime API

Data Source

  • Canadian Census Data: Census Subdivision Boundaries Census Subdivision Population
  • BC COVID-19 Public Exposures (web-scraping using Python BeautifulSoup)
  • BC COVID-19 Dashboard (manually collected regional cases)

Challenges we ran into

  • Designing the layout from scratch; small layout issues like flexbox took a lot of time
  • When trying to build the choropleth map we had to download the census data from the Canadian government and struggled for a while to convert the projection that the boundary file uses

What we learned

  • Time-management and team-coordination is crucial to the outcome

What's next

  • Incorporating more data with finer granularity
  • Improve the COVID risk calculation to incorporate: cases per capita, transit/location crowdedness, etc.
  • Integrate an intelligent trip recommender

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