单选题 We live in a world that"s more connected than ever before, one where humans—and the viruses hitchhiking inside us—can circle the planet in a day. As a result, we"re at greater risk from new infectious diseases than ever before. But there"s an upside to our interconnectedness as well. Thanks to the Internet and cell phones, we can know what"s happening in nearly every corner of the globe almost instantaneously—and that"s a boon for epidemiology. In the arms race between us and the viruses, communication is our advantage. By analyzing the Internet"s everyday wealth of data, we can catch new diseases before they"ve emerged—and stop them before they become a deadly threat.
That"s what John Brownstein, a digital epidemiologist at Children"s Hospital Boston, is working to do with his HealthMap project. HealthMap automatically search for news sites, eyewitness reports, government data, even wildlife-disease cases to identify new patterns in outbreaks, presenting the results on a clickable map. Want to know about an ongoing polio outbreak in Angola? HealthMap will show you where it"s occurring and who"s dying.
HealthMap first launched about five years ago, but it has just relaunched with a new focus toward what Brownstein calls "participatory epidemiology." HealthMap will tap the wealth of potential information on social media—think tweets about flu outbreaks and Facebook postings about contaminated food. The result is more finely tuned intelligence about emerging outbreaks, presented in a personalized format. HealthMap already has a related mobile app called Outbreaks Near Me, which gives users news about public health around their location—and allows them to report information as well. "It"s really taking the local-weather-forecast idea and making it applicable to disease," says Brownstein. "We"re trying to make these ideas that much more relevant to the general population."
The challenge with HealthMap and other digital epidemiology projects is the same one that all intelligence experts face. separating the signal from the noise. Brownstein points out that HealthMap could show unusual cases of respiratory illness in Mexico in the early spring of 2009, before what would become the H1N1 flu burst onto the global stage, but it"s still difficult to separate truly dangerous events from run-of-the-mill outbreaks. The hope is that sharper data collection will allow future digital epidemiologists to identify the patterns that indicate a potentially deadly new disease in time to actually do something to stop it.
One way to do that might be to get more people participating in participatory epidemiology. "We want to get people talking about this threat, so they can take it seriously without being scared," says Brownstein. Fighting new infectious diseases is no different than any other war—the first step is good intelligence.

【正确答案】 D

【答案解析】[解析] 第四段提到了HealthMap尚存的一个不足，即不能把真实信息与非真实的信息区分开来(这里separating the signal from the noise是一个比喻，所谓“噪音”当然指干扰信息)。文章举例说，HealthMap成功地预测了墨西哥流感的爆发，但是它仍然无法区分真正危险的传染病的爆发和普通疾病的爆发(run-of-the-mill意为“普通的，没什么特殊的”)，因此作者说HealthMap有待找到更敏锐的数据收集方式(sharper data collection)。