Consider this the antidote to Donald Trump’s campaign-trail quip about slowing COVID-19 testing due to the optics of the results. Trump complained that media outlets reported the rise in cases out of context of the vastly increased rate of testing, and made it look like reopening commerce in states had created a second wave. While the core of that complaint was true — media outlets didn’t exactly emphasize the fact that increased testing had generated more positives — it also turned out to be somewhat irrelevant.

In fact, Florida just hit a record high again yesterday, with nearly nine thousand new cases, as Allahpundit noted. Cases have spiked upward in the Sunshine State for two weeks now, and Republican Sen. Rick Scott and Gov. Ron DeSantis acknowledge that it’s not just an artifact of expanded testing. Texas has begun locking down again, at least incrementally, and other states are doing the same. The problem isn’t that we’re doing too much testing — and now it looks like we need to find ways to test faster and more efficiently.

NIAID chief Dr. Anthony Fauci unveiled a new Trump administration strategy designed to deliver both — “pool” testing:

Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, told me in an interview last night that health officials are having “intense discussions” about what’s known as “pool testing.” The idea is that by testing samples from many people all together, officials could test more people with fewer resources. And those who are infected could be more quickly found and isolated.

Pool testing would allow officials to cast a much broader net to find cases faster. It would represent a dramatic shift from how coronavirus testing is currently being carried out in the United States – but one that may be sorely needed as virus hot spots worsen and new ones appear. …

The approach works this way: Samples from, say, 20 people are combined into a single pool. One coronavirus test is used on the entire pool. If the test comes back negative, researchers know they can move on to another pool of samples. If it comes back positive, only then would each individual be tested.

“What you need to do is find the penetration of infected people in your society,” Fauci said. “And the only way you know that is by casting a broad net.”

If that seems counterintuitive — why not just test everyone? — it’s because of the numbers of uninfected. Individual tests are inefficient for checking the spread of a pandemic in its early stages especially. Labs are getting tied up with unnecessary work that might have to be repeated later as people eventually get exposed to COVID-19.

Scientific American explained last month why this approach makes more sense now, and may have made even more sense then when tests were still in low supply:

Now dozens of researchers in the U.S., Israel and Germany are pursuing a strategy to dramatically increase diagnostic capacity: group tests. By pooling samples from many people into a few groups and evaluating pools rather than individuals, the scientists think they can use fewer tests on more people. This approach could lead to the faster detection of individuals who are unwitting carriers of the disease and an ability to quickly clear others who have not been infected. The strategy has been used in the past to successfully detect cases of HIV, chlamydia, malaria and influenza, and was originally conceived during World War II to test thousands of military personnel for syphilis. …

Group testing is a numbers game. Let’s say you are examining 100 people, and one of them is positive. Normally you would do 100 diagnostic tests, searching for genetic material from the virus in each individual. But with group testing, you can divide those 100 people into five groups of 20. That gives you five pools with 20 samples, and you use one test per pool. If the first four sample pools test negative, you have eliminated 80 people with four tests. If the last pool tests positive, you retest each sample in that last pool individually to identify the one with the disease. In the end, you did 25 tests instead of 100.

That means four times more capacity in the end, at least in the earlier stages of an epidemic or pandemic. It won’t work later, however, because a greater community prevalence means more duplication:

The biggest limitation of the batch approach, however it is done, has less to do with the test itself and more with the nature of the disease. Group testing works well as long as the prevalence of a pathogen remains low. But if there are too many positive cases in the tested specimens, most of the pools will come up positive and will have to be followed up with individual tests anyway. Hertz’s combinatorial approach works best when the prevalence of the disease in a community is no higher than 5 percent, with around 1 percent being ideal. More straightforward approaches, such as those employed by Iwen and CIesek, work when the prevalence is below 10 percent. In fact, the FDA’s message to Iwen stated that he could test pools as long as the positive test rate was below that percentage.

It would work best now for the White House for another reason. They want to maintain the momentum of reopening the economy, but the spikes are potentially jeopardizing that. The best way to contain the spread outside of another general shutdown would be to initiate aggressive contact tracing and quarantining on individual bases, as well as pushing for stronger participation in mask-wearing. This pool-testing approach allows for much more rapid and efficient assignment of contact tracers in order to contain outbreaks before they expand rapidly across a population.

The goal here is rapid containment, which necessarily means more aggressive testing. If this works, the numbers of individual tests might actually flatten out, but we’ll get a much better picture of the population status in cities and regions.