Suicide has grown to epidemic proportions among U.S. veterans of Iraq and Afghanistan, and the Pentagon and U.S. Department of Veterans Affairs is hoping that social media and big data can help them identify at-risk veterans and get them the care they need.
Last year, more active-duty servicemen and servicewomen took their own lives than were killed combat. In February 2013, the Iraq and Afghanistan Veterans of America (IAVA) conducted its 2013 Member Survey of 4,104 veterans of Iraq and Afghanistan.
IAVA reported that 30 percent of respondents had considered taking their own lives, 45 percent said they knew an Iraq or Afghanistan veteran who had attempted suicide and 37 percent knew an Iraq or Afghanistan veteran who had committed suicide. And 50 percent of respondents said someone close to them had suggested they seek care for a mental health injury.
Identifying people who are at risk of committing suicide is a tricky thing. Often, the people who are the most in need of help are the least likely to seek it. But Chris Poulin, principal partner of predictive analytics specialist Patterns and Predictions, started wondering: What if he took the tools for event-driven risk analytics used by Wall Street financial firms and applied them to the problem?