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A Surveillance Network We Could Learn to Love

Universal biosensors could save lives by spotting disease outbreaks earlier than ever before
machines that detect disease


We’re not quite there yet, but 21st-century bioengineers have developed a machine that can identify about 1,000 of the most common disease-causing bacteria, viruses and fungi within a few hours of taking a patient’s blood sample.
Credit: NIAID

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In the fictional universe of Star Trek characters use a medical tricorder to scan ailing individuals from any species to figure out what’s making them sick. We’re not quite there yet, but 21st-century bioengineers have developed a machine that can identify about 1,000 of the most common disease-causing bacteria, viruses and fungi within a few hours of taking a patient’s blood sample. The technology is based on rapidly determining the genetic fingerprints of the pathogens and comparing them against a reference database.

David Ecker, who developed one of these machines for Ibis Biosciences, writes about their potential in the June 2014 Scientific American. Local doctors could quickly find out exactly what strain of campylobacter, for example, is making their patient sick as well as which antibiotic treatment would work best for that particular infection.

Early models are likely to come on the market in the next few years and may cost $100,000 or more—less than the price of a CT (or computed tomography) scanner. As with so many computerized devices, the price tag should come down with future modifications. Other companies working on competing sensors include Illumina and PathoGenetix.

Looking ahead, Ecker believes that connecting just a few hundred such universal diagnostic machines so that they share information would allow the creation of the first truly comprehensive early warning system for the detection of emerging epidemics and bioterror attacks as well as garden variety outbreaks of food-poisoning.

Previous ideas for developing a universal health surveillance network included testing blood donors for possible infection. Trouble was, Ecker says, when researchers did the math, they determined that they would need to include samples from far too many people—about 300 million—making the test prohibitively expensive. (Basically, blood donors tend to be healthy in the first place, which means you have to look harder to find germs.) With such large numbers, the results would also produce too many false positives, which would only add to the cost of treatment.

By contrast, the “Threat Net,” as Ecker calls his proposed surveillance network, tests only people who are sick enough to go to the hospital, making it much more efficient because fewer people are needed to trigger a reliable signal. In his June 2014 Scientific American article, Ecker writes about the calculations he performed to find the ideal number of machines necessary to generate a robust network. The total number was surprisingly small:

Linking 200 carefully chosen hospitals across the nation to the network would be sufficient to cover the entire U.S. metropolitan population. Each urban area the size of Washington, D.C., or San Diego would need about five hospitals with universal biosensors on the network; there would be a 95 percent probability of immediately detecting a public health–relevant infectious agent, such as bird flu, anthrax, plague or a food-borne pathogen if only seven patients sought care in an emergency department.

“Everywhere I’ve briefed this notion, including the White House national security staff, everyone has been enthusiastic,” Ecker says. “The problem is this is nobody’s job to think big like this and then find a way to piece it together.” He adds: “I really got a lot of traction from the [Food and Drug Administration] food safety people. In their world, they’re worried about contamination in food, salmonella in peanut butter or whatever. You can’t test the food very deeply—it’s too expensive. You have to test samplings of the food. It’s inherently hard to do. The amount of sampling that actually gets done is infinitesimally small.” Once again, the economics calls for testing the people who get sick from food poisoning—and then backtracking to determine if there’s an outbreak (which might otherwise go unnoticed).

Ecker can seem at times like a one-man band in favor of setting up a Threat Net—or something like it. No doubt, when the next big outbreak of some horrible disease that no one has ever heard of comes out of nowhere, we’ll all wish our leaders had paid closer attention. “The technology is coming,” he says. “If we put a little forethought into it, we can get ahead on the notion. I’ve got to believe that the logic will take hold.”

This article was originally published with the title "Germ Catcher."

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