Why positivity rates are maybe not the best way to report on COVID transmission

Something gets lost in translation when you’re told that a high community COVID positive test rate is evidence of high community transmission.

The issue: COVID testing data, as we’ve been reporting it for the past two years, isn’t, and really never has been, randomized.

Think of how public opinion polling works. The pollster doesn’t throw a post up on social media asking whoever wants to participate to weigh in on their favorite flavor of ice cream; the key to any degree of confidence in accuracy in the poll numbers is that it’s a reflection of a random sample of the population.

For the past two years, we’ve been told about positivity rates that reflect not a random sample of the population, but rather a sample of the population that has felt the need to get a COVID test.

See the issue here?

People who aren’t symptomatic aren’t volunteering to have that wand inserted deep into their noses.

And of late, hospitals had been pleading with the public to only seek out testing if they’re symptomatic and feeling at least somewhat ill to reduce the strain on the health system.

Meaning, not only is the recent resulting data not randomized, but it’s two degrees winnowed down – those who are symptomatic, and then those who are also ill.

For the data to be reflective of what’s going on in the community at large, we would need to have representation from the portion of the population that is neither symptomatic nor ill.

Otherwise, the data is the equivalent of taking to Twitter to ask people what their favorite flavor of ice cream is.

Beware any data that comes from that kind of self-selected sample, basically.

Story by Chris Graham