The histogram for Alabama is skewed to the right (more small values on the right), which means that, in general, they have lower R-values.
The histogram for Alaska is skewed to the left (more small values on the left), which means that, in general, they have higher R-Values.
The histogram for Arizona is skewed to the right (more small values on the right), which means that, in general, they have lower R-values.
The histogram for Arkansas is skewed to the right (more small values on the right), which means that, in general, they have lower R-values.
I first aligned the two datasets, the R-Values per state and the State Social Distancing Actions. With the State Social Distancing Actions dataset, I quantified the policy actions with values from http://epidemicforecasting.org/containment-calculator. The percentages, for example, -9% for masks became an integer value of 9 on the strictness scale. To match the policies from the State Social Distancing Actions, I used the reduction data of stay-at-home order = 18, symptomatic testing = 10, gatherings limited to 100 people = 5, gatherings limited to 10 people = 24, some businesses suspended = 34, and schools and universities closed = 33, and over 60% of the population wears masks = 9. These integers were added up per data point to produce the final strictness index with a minimum of 0 and a maximum of 133. This calculation was made under the assumption that a stricter set of policies would make the policies for that state more effective in lowering the R-Value of COVID-19.
The percentage values were turned into integers than represented the strictness of each policy.
The integer values of each policy taken into account in my code.
This is one of the datasets listing the different policy actions taken by each state on a specific date.
Because there are only so many combinations of policy strictness based on the method of quantification, the data points ended up showing up in lines on those values.
If you would like to see all of the scattergrams, please download my code from GitHub and run it!
Theoretical reduction of R-value
Data
My python code
Thank you to ISB, specifically Claudia Ludwig and Rachel Calder for running the Computational Modeling Workgroup and guiding me on my project and Brooke Ury for completing the external review on my project.