This project addresses the challenge because it satisfies the goal of the challenge which is predicting what areas are likely to be affected by this disease.
Our project came to fruition with the idea that we wanted to write a program that was able to help officials figure out if their city was of a higher risk of being hit with a second wave of COVID-19. We began by researching, talking to officials, and discovering what factors tended to be associated with COVID-19 spread. The next step was figuring out how much these factors affected the spread of COVID-19, as not all factors that affect spread are equal. We gave each factor a rating of 1-5 with 5 being the most drastic. From there, we wrote a code that acted similar to a survey where information about the city is inputted into the code, and the code will output a % match, the higher the percentage, the more likely the city will be to have a COVID-19 outbreak.
https://data.nasa.gov/browse?q=public%20transportation%20usage&sortBy=relevance
https://www.worldpop.org/geodata/summary?id=1276
https://data.world/covid-19-data-resource-hub/covid-19-case-counts
https://www1.nyc.gov/site/opportunity/poverty-in-nyc/poverty-tool.page
https://www.cnn.com/interactive/2020/health/coronavirus-us-maps-and-cases/
https://projects.iq.harvard.edu/covid19/home
https://data.humdata.org/dataset/novel-coronavirus-2019-ncov-cases