The idea here is to determine how many new COVID-19 cases are detected AFTER you account for the change in new test numbers. All else being equal, if you double your testing, you will double your positive cases.
I consider those cases to be 'expected'. The difference--the cases that can't be explained by the change in number of tests--are the 'unexpected cases', which are plotted in red. Essentially, we are plotting the
change in positivity rate versus a 14-day average and converting that into number of cases.
Latest update: 2020-11-30 Data Source: The Covid Tracking Project.
Unexpected cases below zero indicate that the positivity rate is decreasing. This must happen in a scenario in which things are getting better.
Unexpected cases above zero indicate that the positivity rate is increasing. This can mean many things, including testing only those with severe symptoms, but it is likely indicative of things getting worse, especially if the number of tests is increasing.
Unexpected cases hovering around zero indicate little change in direction, and could be good or bad depending on the current situation.
These data are reported by individual states, with different reporting standards (I'm looking at you, South Carolina). For this reason, expected case calculations use a 7-day moving average of both the reported testing and case numbers.
23 states have a positive number of unexpected cases over the last week. During that time, the top five states with the most unexpected cases:
New York (3492)
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14-day average positivity rate: 11.7% (Two weeks ago: 10.8%)