Some time in the past week, Johns Hopkins changed the way they report positivity rates for Massachusetts. (Since I don’t check the site every day, I’m not sure exactly when this occurred, but it did occur recently). Formerly, Johns Hopkins used a method that focused on individuals – taking total new cases (confirmed and suspected) and dividing that by the number of new individuals tested with a molecular test. They performed this calculation on a “reported day” basis – updating their numbers as new data is reported and adjusted by the Commonwealth. This is different than a calculation on a “as-of-date” basis, which looks at the date that the test is performed, not when it is reported. More on that later.
With the new method, Hopkins still uses total new cases (including suspected) as the numerator in the calculation. However, they are now using total molecular tests performed as the denominator. This has greatly reduced Hopkins’ calculated and reported positivity rate. As of September 14, Hopkins now shows a 7 day positivity rate of 0.74% in Massachusetts – 2,289 new cases divided by 310,742 molecular tests https://coronavirus.jhu.edu/region/us/massachusetts.
This is even lower than that reported by the Commonwealth (0.83%). Why is that? First, the state uses “as-of-date” calculations, looking back over the past seven days at the number of tests performed on each day for which results have been reported. This is 2,279 new confirmed cases divided by 275,565 molecular test results. Second, as just noted, the state only uses confirmed cases in the numerator (this lowers the positivity rate). Finally, the state lags the data one day. While 32,467 cases were reported on September 14th, there were only 20 tests performed on September 14 for which results had been reported in time to be included in the September 14th report – hence the state uses the 7 days ending September 13th for reporting positivity rates.
From Hopkins directly, summarizing their calculation (emphasis added). Note Hopkins’ preference for a measure based on individuals, not tests.
“Positivity Rates: Our calculation, which is applied consistently across the site and predates most states’ test positivity tracking efforts, looks at number of cases divided by number of negative tests plus number of cases. We feel that the ideal way to calculate positivity would be number of people who test positive divided by number of people who are tested. We feel this is currently the best way to track positivity because some states include in their testing totals duplicative tests obtained in succession on the same individual, as well as unrelated antibody tests. However, many states are unable to track number of people tested, so they only track number of tests. Because states do not all publish number of positive and number of negative tests per day, we have no choice but to calculate positivity via our approach. We describe our methodology as well as our data source (COVID Tracking Project) clearly on the site.”