How to be Careful with Covid-19 Counts
Rex W. Douglass
1
Executive Summary
1.1
Key Takeaways (TLDR)
1.2
Key Caveats
2
Empirical Background
3
Day Zero
4
COVID-19 Measurement
4.1
Executive Summary
4.1.1
Unit of Analysis and Definition of Measurements
4.1.2
Fist Order Cleaning Steps
4.2
COVID-19 Survailance
4.2.1
Sources of Data
4.2.2
County District Level Data Availability
4.2.3
What is their temporal coverage?
4.2.4
Where and How do they Disagree?
4.3
Influenza Survailance
4.4
Motaility Survailance
5
COVID-19 Inference
5.1
Confirmed Cases
5.2
Confirmed Case Fatality Rate (CCFR)
5.3
Tests
5.4
Tested People versus Tested Samples
5.5
Interpolate Within Observed
5.6
Interplate Prior to Observed
5.7
Interpolate Subnationally
5.8
Explaining Variation in Testing
6
COVID-19 Causal-Inference
7
COVID-19 Prediction
8
Conclusion
References
How to be Careful with Covid-19 Counts: A Practical Guide for Data Scientists
Chapter 7
COVID-19 Prediction