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So some researchers have been focusing their efforts on faster overall detection: If they can identify a new strain of the virus early enough, and if enough antiviral medication can be produced in time, there’s at least a chance of stemming a pandemic’s tide. One particularly promising area is search-engine and social-network data. This information flows in a constant torrent, and researchers can examine it for indications of disease hot spots. “We’ve developed algorithms that crawl the Web, looking for specific words of disease or warnings of disease,” says John Brownstein, an epidemiologist at Children’s Hospital in Boston. “It’s low-cost and highly geographically specific.”

In fact, a recent study by Brownstein and his colleagues showed that as Internet-based reporting of all diseases has increased, the time between a disease’s first occurrence and its discovery by public health officials has decreased at a rate of 7.3 percent a year. Early reporting systems can help pharmaceutical companies get the right vaccines to the right places in time to prevent widespread disaster.

But for influenza pandemics, early detection is sometimes not conclusive enough. Brownstein says that his system picked up a signal of unusual respiratory activity in Mexico when the H1N1 swine flu first erupted in 2009, but that it was just one of a number of unusual events occurring at the same time. “How do you differentiate [the strain in] Mexico from the others, and how do you know that’s the one that will turn into a global pandemic?”

To answer that, scientists are developing model after model of viral evolution and mutation, and they’re increasing their surveillance of the virus in wildlife and livestock, trying to keep up with the changes—or possibly get a step ahead. “We have an extraordinary amount of information on the evolution of influenza, with a large sample of genetic data. We know what the viruses look like going all the way back to 1918,” says Oliver Pybus, an evolutionary biologist at the University of Oxford. “If it were obvious and simple, we’d have found it by now.”

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Credit: HealthMap

Tagged: Business, Business Impact, Predictive Modeling, H1N1, influenza, flu virus

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