Choropleth Map Visualization of the Zika Disease Epidemic within the US

Alt Text

Link below provides slideshow:


Whenever there is a disease epidemic, CDC specialists track the origins of the disease and try to understand how it migrated over time. How can we provide a visual aspect to understanding how a disease migrates among the human population over time?

Proposed Solution

The goal would be to provide a disease tracker to record real-time occurrences and updates. If we could visualize where there's a influx of occurrences we could potentially contain the disease and prevent it from spreading.


The dataset is from Kaggle: The dataset consists of the Zika virus migration across the world. I took the data concerned with Zika disease occurrences within the United States.


1) Pre-processed the US Zika Disease occurrences to identify and provide state abbreviations so that the Plotly API understands where to plot a data point 2) For every date, an image is produced showing all the Zika occurrences within the US.

Technologies/APIs used

  • Python (Juypter notebook) - curate the data for each report date, feed the curated data for a Plotly API call to generate the Choropleth map.
  • Plotly API - generate the Choropleth map
  • Javascript/HTML/CSS - used for rendering the slideshow


  • Fix image generation

Issues faced

  • There exists geographic mapping libraries however due to the many different varibles you can have, there are a lot of geographic mapping libraries to search thru in order to find the one that suits your dataset.

Other applications

Human Trafficking - Track when and where human trafficking activity happens and send law enforcers to arrest criminals. Crime - Track when and where crime happens across the world and send law enforcers to those areas. Finance - Where and when did somebody make a transaction?

Built With

Share this project: