Science
28 November 2014 vol 346, issue 6213, pages 1029-1148
http://www.sciencemag.org/current.dtl

In Depth
Infectious Diseases
A new phase in the Ebola war
Kai Kupferschmidt*
Summary
The number of new Ebola cases in Liberia, one of the hardest hit countries in the current epidemic, has come down to about 20 per day, far fewer than models predicted a few months ago. Ebola treatment units now have hundreds of empty beds, and the fight against the virus is entering a new phase. Back in September, the key job was building clinics, removing the dead, and keeping as many patients as possible isolated. Now, it’s about setting up a flexible system to respond to new outbreaks, identifying patients quickly, and tracing their contacts to prevent more infections. Meanwhile, outbreaks are still flaring up in the remote districts, making it unlikely that Liberia can put a stop to the epidemic anytime soon

Perspective
Medicine
Big data meets public health
Muin J. Khoury1,2, John P. A. Ioannidis3
Author Affiliations
1Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
2Epidemiology and Genomics Research Program, National Cancer Institute, Bethesda, MD 20850, USA.
3Stanford Prevention Research Center and Meta-Research Innovation Center at Stanford, Stanford University, Palo Alto, CA 94305, USA.
Summary
In 1854, as cholera swept through London, John Snow, the father of modern epidemiology, painstakingly recorded the locations of affected homes. After long, laborious work, he implicated the Broad Street water pump as the source of the outbreak, even without knowing that a Vibrio organism caused cholera. “Today, Snow might have crunched Global Positioning System information and disease prevalence data, solving the problem within hours” (1). That is the potential impact of “Big Data” on the public’s health. But the promise of Big Data is also accompanied by claims that “the scientific method itself is becoming obsolete” (2), as next-generation computers, such as IBM’s Watson (3), sift through the digital world to provide predictive models based on massive information. Separating the true signal from the gigantic amount of noise is neither easy nor straightforward, but it is a challenge that must be tackled if information is ever to be translated into societal well-being.