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Social media could help detect pandemics, MD says

German Health Minister Daniel Bahr puts on protective gloves as he visits a lab in the western German city of Muenster on June 18, 2011. The Environment Ministry of the state of Hesse announced that the deadly O 104:H 4 strain of the deadly E. coli bacteria had been found in the "Erlenbach" stream near Frankfurt am Main.


Critics of social media often complain they encourage frivolous recordings of what people are eating for lunch or where they're having drinks after work.

But what if social media could help detect and track global disease outbreaks weeks earlier than traditional surveillance methods, allowing officials to introduce treatment and reduce the spread of a potential pandemic?

A growing segment of the medical community believes that is a realistic possibility and is increasingly looking at ways to harness the power of blogs, news outlets and social-networking websites to detect disease patterns around the world.

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Dozens of researchers gathered Monday at a pandemic conference in Toronto to hear about the progress one expert has made toward achieving those goals.

John Brownstein, an epidemiologist who works as a researcher at Children's Hospital Boston, told researchers instead of relying solely on government-based disease-surveillance systems, they should recognize the power of clues coming from individuals on the ground.

Dr. Brownstein and his colleagues have created HealthMap, an ambitious website and mobile application that constantly trolls the Internet for emerging outbreaks of the flu or a new respiratory illness.

HealthMap uses news sites, eye-witness reports, government disease-tracking systems, wildlife disease-surveillance websites and other sources to identify new patterns in disease and where they are occurring. The scope is impressive; HealthMap automatically scrolls through tens of thousands of websites an hour, Dr. Brownstein said.

"We're constantly mining the Web," he said.

Researchers recently used HealthMap to illustrate on a world map the location of new cases of E. coli infection as they were identified, following a massive illness outbreak that was eventually linked to German sprouts.

Informal online-surveillance methods should never replace traditional public-health disease-tracking systems, Dr. Brownstein told the conference. But they can help enhance data and uncover patterns quickly, especially considering some limitations of traditional surveillance. For instance, many government tracking systems may have geographical limits that could fail to take into account disease patterns in a neighbouring country.

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The system is far from perfect: Dr. Brownstein said HealthMap identified a new pattern of respiratory illness in Mexico in 2009 well before public-health officials realized a new influenza pandemic was emerging. Yet, researchers didn't recognize the seriousness of the threat it posed.

HealthMap often identifies new disease patterns in various countries around the world, but researchers haven't developed a sound method of determining which ones pose serious threats and which are run-of-the-mill pockets of illness.

The possibilities for early detection of emerging infectious diseases are enormous and could allow public-health authorities to identify serious outbreaks or pandemics much faster than they do currently, which could save lives and a significant amount of money.

In fact, Dr. Brownstein wants to see the expansion of non-traditional surveillance methods to place a greater emphasis on social media. One early venture into this territory is Outbreaks Near Me, a smart-phone application created by Dr. Brownstein and his colleagues. It allows people to submit information, such as if a family member falls ill or if there is a lineup at a local vaccination clinic. Such information can allow researchers to detect patterns and possible outbreaks.

"The mass of information can help us to find signals of what is happening in the population," Dr. Brownstein said.

While it's not foolproof and could be vulnerable to errors from individuals who purposefully submit erroneous data, a growing number of researchers believe that taking advantage of the millions of public online conversations that take place daily could yield enormous results.

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