We're excited to be sharing our first OC Civic Coder's project to help easily visualize where Corona Virus is spreading in Orange County using data provided by the OC Health Care Agency. This open source app uses visualization charts, and bubble maps to show where Covid-19 is in Orange County, and how it is spreading over time.
The goal of this app is to provide tracking data to the general public that's easy to understand, in efforts to help slow the spread and see if our preventative measures are working. This app is hosted on the OC Civic Coders site (check it out)!
How Corona Virus has spread in Orange County over time by city
Case counts have been gradually on the rise from mid March through April, however hospitalizations and ICU counts have been relatively flat. The dropdown menu provides individual case counts by city, thus allowing locals to track and encourage preventative measures close to home. The app additionally breaks down Covid-19 case ratios by gender and age.
A bubble map for where Covid-19 is occurring in Orange County
This bubble map displays visual representations for the amount of Corina Virus cases by city in Orange County. The dropdown menu additionally lets you visualize by case counts per population, which in turn displays some interesting results as opposed to visualizing by counts alone. The sidebar to the right sorts case counts from largest to smallest and points out the location when hovered over.
In addition, the app shows how the spread initially began, trending data by travel related, vs locally spread. Data related to travel is no longer being tracked as most cases now are locally spread within the community.
Built open source by local civic coders
The Orange County Covid-19 tracker is an open source project made by local residents. It's an interesting example of coding for causes together to help the local community. The code uses Cheerio, Axios, and Node to get the data from the city website. It then uses Chartjs and Mapbox and D3js to visualize the data. You can view, download, and contribute to this code on GitHub.