We saw a bunch of COVID maps and decided that their information was limited when it came to the prediction of the virus. As such, we decided to make our own visualization tool for the case data that includes a prediction algorithm for the virus and where it will go next.

What it does

It visualizes the spread of any given pandemic.

How we built it

Before we started the project, we wanted to analyze what factors mattered the most for the spread of the pandemic. We decided on these four factors:

  • Population
  • Population Density
  • Daily Increase in Cases
  • Amount of Current Cases

With these factors in mind, we started working on collecting all of this information. First we looked at US Census Data for the state populations and area, and collected data by county. Then we looked at the COVID-19 API and took the cases and daily cases. After throwing it all into the formula, we tested some examples and were happy with the results. Afterwards, we started working on visualizing the data. The tools we used were Folium in combination with Flask.

Challenges we ran into

The United States Census Data was formatted in an unknown way, so the data processing was a little difficult. It was also a little hard to find a COVID API that tracked county data.

Accomplishments that we're proud of

The visualization of the information on a map of the United States.

The Mobile Application that was built alongside the website.

What we learned

We learned how to visualize information with Folium.

One of our more novice teammates learned how to connect frontend with backend.

What's next for Pandemic Assistant

One thing we could add to the mobile app is a GPS program that detects if you enter a potential spreadzone and notifies you if that occurs.

Add more specific data for cities instead of counties.

Fix some of the missing information in states like Utah, Alaska and parts of New York.

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