For those trying to prevent outbreaks of infectious diseases, there may be no more powerful tool than a mobile phone to identify “superspreaders” of viruses.

“There are more cell phones than people, and, in most urban areas, network coverage is close to 100 percent, hence we can get very accurate measurement and sampling of the population,” Jon Crowcroft, a professor of networked systems at the University of Cambridge in England says in a story published by the university.

“How people behave could limit or exacerbate their risk of infection,” Crowcroft explains. “Patterns of social interaction that worsen the spread of disease pose a significant risk. On the other hand, if people stay at home rather than work, the cost to the economy may be greater than the cost incurred through actual illness.”

Crowcroft and colleague Eiko Yoneki are co-leading the FluPhone study, a smartphone-based project at the Cambridge Computer Laboratory to investigate how influenza viruses spread as people interact with each other. The Java-based app, designed for Nokia’s Symbian OS and compatible with various Nokia Series 40 and Series 60 smartphones, asks questions of study participants to look for flu-like symptoms.

“It also captures physical proximity information between individuals by recording other devices nearby via Bluetooth communication,” Yoneki says in the Cambridge article. The researchers cited ethical considerations for ruling out using GPS to track people’s movement.

The Cambridge team recently opened up FluPhone participation to the public after running a pilot among volunteers in the university community that happened to coincide with a rash of swine flu. “In this particular outbreak it’s now known that some people carried the disease yet were asymptomatic. Our system is capable of identifying these asymptomatic ‘superspreaders’ because they show up by virtue of the contacts who develop the disease,” according to Crowcroft.

“A post-facto analysis of these data [from the pilot] will yield valuable insight into how human communities are formed, how much time people spend together and how frequently they meet. Such data show complex network-like structures, which is very useful for understanding the spread of diseases,” Yoneki adds.

The researchers also have developed a prototype of a “virtual-disease epidemic” app that simulates the transmission of disease when two study participants are in Bluetooth range of each other, usually about 30 feet. “This has proved to be a fantastic tool,” Crowcroft says. “You can run a ‘what-if’ experiment on the live population based on their contacts, simply by randomly choosing some of the mobile phones to be infectious. We can then model the effect of behavior on disease spread.”

In partnership with six other universities and government agencies, Crowcroft and Yoneki plan on extending FluPhone to track population health in seven African countries. Yoneki also has funding to convene a multidisciplinary team of epidemiologists, psychologists, economists and computer scientists to search for new ways of responding to public-health events.

Here stateside, the Centers for Disease Control and Prevention is offering $35,000 in prizes for apps that draw on CDC flu data to promote healthy behavior that helps prevent flu outbreaks. The CDC Flu App Challenge runs through May 27.