Some of the leading causes of death in the United States include heart disease, cancer, alcoholism and injuries caused by accidents. Many of these are preventable, and being able to visualize the numbers could help us develop improved strategies to avoid and alleviate their occurrence. We expect our application to be useful for the general public. It will make them more aware of the diseases they are susceptible to based on their location and other demographic traits. Medical students could also benefit from knowing which fields require their interest the most. Finally, policymakers would greatly benefit from a tool that would help identify major health problems in their region and so they can draft effective policies. The detailed study of Historical data on Mortality Rates and Causes of Deaths from the year 1950-2016 show interesting trends.
Using various visualizations that we’ve learned this semester through the course Information Visualization taught by Dr. Luciano Nocera, we try to represent various statistics related to Mortality Rate, and the causes of Deaths. We’ve used the Pandas library in Python to read data of multiple years and combine them to find their average values and store them as a CSV file. We’ve also used tools such as Microsoft Excel to read the data and get the required values from it using its pivot table functionality. The visualizations that we’ve created are using d3.js and the website is created in Vue.js. We’ve used different node modules such as topojson, bootstrap to make the website more interactive and visually appealing.
- PROJECT TITLE: Disease Control and Prevention Analysis
- TEAM MEMBERS:
- Shraddha Kulkarni (email@example.com)
- Seher Khan (firstname.lastname@example.org)
- Demonstration URL: (http://pdms.usc.edu/~seherkha/proj/)
- Article [Overleaf URL]: https://www.overleaf.com/read/vxfjcwjhhzcp
- YouTube video: https://youtu.be/9LY0rr_nhG0
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