Inspiration
Health inequity plagues the United States, despite health equity seeming achievable with our given resources. However, societal norms and institutional processes have created a system that has normalized discrimination and stereotyping on the basis of ethnicity, gender, age, disability, and other factors, perpetuating these inequities. These inequities have affected our everyday lives, from the air quality in the town we grew up in to the availability of supermarkets within walking distance, to our ability to get diagnosed with diseases (aka social determinants of health).
What it does
By creating a simple and interactive platform to visualize 28 comprehensive measurements overlaid with 600+ social determinants of health (SDOH), we can more easily map correlations and potentially form conclusions between factors surrounding our cities and its population's health outcomes.
Features:
- Fully interactive: Zoom into your home county, click on the data point, and learn about where it compares to other parts of the state/country!
- Toggle state view or county view: see the data points for a state overall or for its individual counties
- 28 different health-related measurements + 675 determinants of health
- Color-coded by values (with a very nice gradient!)
How we built it
- Python Flask backend
- JavaScript/HTML/CSS frontend
- Leaflet.js interactive map
Challenges we ran into
The size of the initial dataset (cities instead of counties) was a challenge to wrangle and display on the map, which is why switched to a counties dataset instead. In addition, overlaying SDOH and CDC health measures required finding two publicly available datasets that would map 1-to-1, which took up a significant portion of time. We eventually found two datasets, and mapped them together with county (FIPS) code.
Accomplishments that we're proud of
- The interactive map works smoothly without lag (given the crazy data sizes we encountered initially!)
- Finding a SDOH dataset that corresponded 1-to-1 with the locations on the CDC dataset
- The data wrangling that was done!
What we learned
The base of this project was built using Cursor, in which we learned how to prompt engineer the interface, before going in manually to adjust components of the UI.
Bonus: Aleutians West has the wrong latitude listed on the specific CDC dataset we used, causing its data point to appear in the middle of Canada. We fixed it (obviously) and potentially may reach out about this minor error.
What's next for Health Equity Heatmap
We hope to improve the UI to show state/county borders instead of a dot representing each one. In addition, given the documentation for the SDOH, we will update the SDOH names to its full name rather than the column name on the data file.
Log in or sign up for Devpost to join the conversation.