Many data visualization and model visualization tools have been released in the weeks since the COVID-19 story began to break. Here are a few of my favorites:
- UVA's Biocomplexity Institute dashboard shows the geographic spread of the virus over time.
- 3Blue1Brown presents a video narration examining the effects of various agent-based simulation features.
- Gabriel Goh provides a simple, elegant calculator for illustrating how parameter changes affect trajectory of the infection curve.
- Kevin Simler's blog post introduces and discusses quite a few manipulatives for varying simulation parameters.
- The COVID-19 Forecasting Project gives estimates for current numbers of active cases as well as projections for the future.
- COVID Projections is another forecasting site with positive reviews from experts.
- rt.live tracks state-by-state estimates for the current reproduction number () over time.
A couple notable data sources if you want to explore the data yourself:
- The Johns Hopkins data is perhaps the most canonical source on global COVID-19 data.
- The COVID Tracking Project includes data on negative tests as well positive ones, but it only covers the United States.
Check out this Jupyter notebook if you want to see an example of how to load the Johns Hopkins data into a Python session and perform some data manipulation and visualization tasks with it.