Our goal is to find how human movement (human factor) affects the number of COVID-19 cases on a global scale.
We figured it was be extremely interesting to discover what human factors contributed to the spread of COVID-19 globally. Our approach was find relevant datasets to recent human factors and confirmed COVID-19 cases and combine them to see if there were any significance. We found out that a lot of the human factor datasets are extremely difficult to find (maybe there is none or only for purchase?). We had a challenging time incorporating space agency data into the project as it appears more so atmospheric and geographic. We used Python, Jupyter Notebook, R, RStudio, git, GitHub, Discord, Microsoft Excel, and Microsoft PowerPoint to develop our project.
We discovered that we needed more human factor features from other areas and as said previously it was extremely hard to find these needed datasets. We discovered human mobility alone doesn't have much significance on COVID-19 cases. We feel the dataset that we developed has a lot of potential if the adequate human factors features can be joined with it (it's a start for now). It was a great experience and hopefully our little contribution helps in some way!