Plus, the number that tells whether a city, county, or state is safe to reopen.
As the rate of new coronavirus cases and deaths in the US slows down, many states and cities are encouraging businesses to open again, easing the lockdowns that have been in place since March. But some of those places might be doing so prematurely, according to an important metric that public health experts say signals when a place has tested enough, and in the right way: the test-positivity rate.
The test-positivity rate is the percentage of Covid-19 tests that come back positive relative to the total number of tests performed. Public health experts say it can be understood as a measure of how well a place has tested its population and to what degree it has identified a significant number of asymptomatic cases. A place with a high test-positivity rate has most likely focused its testing diagnostically, prioritizing the testing of people showing up to hospitals with severe symptoms. That’s what happened in the first several weeks of the coronavirus outbreak in the US, because of testing shortages and CDC guidelines advising health care workers to focus on testing the symptomatic.
As of May 25, the US’s cumulative test-positivity rate was at 11 percent, one percentage point higher than the 10 percent adequate-testing benchmark the World Health Organization proposed in March. That’s the lowest it has ever been, and it’s a sign that the US is ramping up testing. (This video uses cumulative data as of May 16, which had the US at 13 percent.) But the fact that it remains high is a sign of past shortcomings.
Contrast that with South Korea, which as of May 25 had a cumulative test-positivity rate of only 1 percent. That low rate is a sign that the country ramped up testing early, and that it tested not only the severely symptomatic but those who had mild symptoms or no symptoms at all: people found through contact tracing and through random testing efforts.
The US’s test-positivity rate as a whole also obscures a significant degree of variation among the testing efforts of different US states. (This video uses May 6 data from the Harvard Global Health Institute, and many states have improved their testing rates since then.)
One big disclaimer for drawing conclusions from testing data in the US is that there is evidence that the CDC-reported testing numbers may be artificially inflated due to mixing data from diagnostic (who is sick right now) and serology (who has coronavirus antibodies) tests. But because the reported testing numbers are almost certainly not lower than the actual numbers, we can still use the test-positivity rate to infer that the US has a long way to go before it has tested enough of the right people to be able to contain its outbreak effectively.
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Author: Laura Bult
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