
Are “Positivity Rates” a Useful Statistic for an Epidemic - giardini
What are your opinions about the &quot;positivity rate&quot; 
 statistic?<p>As I understand it, positivity rate is defined as<p>(Positive Tests)&#x2F;(Total Tests)<p>for some sampling period (day,  week, etc).<p>Since tests are:<p>1. not given to individuals on any basis other than<p>a) showing up at a testing site voluntarily or<p>b) possibly being given a test as a result of a physician&#x27;s exam or hospitalization [note how different these two cases are].<p>and<p>2. results are grouped arbitrarily (sometimes by facility, sometimes by county, sometimes by city, etc., in other words, no consistent grouping)<p>I fail to see that positivity rate is useful for any purpose.<p>No control appears to be present at all. That is, there is little to prevent someone from being tested repeatedly day after day, or even several times per day, although honestly I believe that uncommon. Many factors can influence who is  tested: day of week, holidays, special events, just got home from France, I&#x27;m off today and have nothing else to do, someone has a cough, someone else has a fever, my back hurts, etc.<p>Using positivity rate as a reliable predictor of <i>anything</i> appears to be an abandonment of standard statistics and assumes that (in the case of daily sampling) each day&#x27;s sample is representative of the whole population, a surely flawed assumption.<p>While &quot;positivity rate&quot; is indeed easy to compute, are there not better methods available (e.g., random sampling of the population) that would provide truly useful information?
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giardini
There is an article in "The Atlantic" titled "A New Statistic Reveals Why
America’s COVID-19 Numbers Are Flat":

[https://www.theatlantic.com/technology/archive/2020/04/us-
co...](https://www.theatlantic.com/technology/archive/2020/04/us-coronavirus-
outbreak-out-control-test-positivity-rate/610132/)

the article discusses the use of "positivity rate" by doctors and
epidemiologists, whom in recent months I have come to view as charlatans. To
the good, the article at least _tries_ to justify the statistic "positivity
rate" somewhat.

My conclusion is that it is both more honest and more enlightening simply to
provide to the public the _two_ numbers (total tests, positive tests) rather
than a quantity derived from the two, such as "positivity rate" which can be
easily misunderstood, misinterpreted or misused.

