Taiwan disease simulation system publicly unveiled

TAIPEI, Taiwan — Taiwan has become the third country in the world to publicly unveil a disease simulation system capable of predicting the spread of influenza, Academia Sinica said in a statement.

The refined computer system, presented in the international online journal “PLoS One” earlier this month, represents an upgrade of other slower systems previously developed around the world, said Wang Da-wei, a medical informatics specialist with Academia Sinica’s Institute of Information Science.

Wang said the new system adapted a revised computing algorithm to an updated database containing population and transportation data and public health statistics provided by Taiwan’s Centers for Disease Control (CDC), enabling it to run 1,000 times faster than other simulators in existence and generate more precise results.

The system has a wide range of applications because it can simulate the outcomes of different quarantine policies, the specialist added.

Though the system was only publicly unveiled this month, it had been researched since 2007 and was tested during the outbreak of swine flu (influenza A H1N1) in Taiwan late last year.

CDC deputy director-general Lin Ting said the simulator concluded that with appropriate airport inspection and quarantine measures, the peak date of infection could be postponed by 22 days, a result that served as an important reference to the Department of Health (DOH) in developing disease control and intervention policies at that time.

Reference Link
http://www.chinapost.com.tw/taiwan/national/national-news/2010/11/22/280888/Taiwan-disease.htm

Courtesy
The China Post

Cellphones reveal emerging disease outbreaks

YOUR cellphone could be a key tool in the fight against disease by relaying a telltale signature of illness to doctors and agencies monitoring new outbreaks.

“This technology is an early warning system,” says Anmol Madan of the Massachusetts Institute of Technology, whose team concluded that you can spot cases of flu by looking for changes in the movement and communication patterns of infected people.

This technology could be an early warning system to enable us to spot outbreaks of influenza

Epidemiologists know that disease outbreaks change mobility patterns, but until now have been unable to track these patterns in any detail. So Madan and colleagues gave cellphones to 70 students in an undergraduate dormitory. The phones came with software that supplied the team with anonymous data on the students’ movements, phone calls and text messages. The students also completed daily surveys on their mental and physical health.

A characteristic signature of illness emerged from the data, which was gathered over a 10-week period in early 2009. Students who came down with a fever or full-blown flu tended to move around less and make fewer calls late at night and early in the morning. When Madan trained software to hunt for this signature in the cellphone data, a daily check correctly identified flu victims 90 per cent of the time.

The technique could be used to monitor the health status of individuals who live alone. Madan is developing a smartphone app that will alert a named contact, perhaps a relative or doctor, when a person’s communication and movement patterns suggest that they are ill.

Public health officials could also use the technique to spot emerging outbreaks of illness ahead of conventional detection systems, which today rely on reports from doctors and virus-testing labs. Similar experiments in larger groups and in different communities will have to be done first though.

Leon Danon at the University of Warwick, UK, is negotiating with the ministry of health of a northern European nation about a project that would combine the anonymous cellphone records of around 10,000 people with their health records to produce signatures of disease from a larger population.

Researchers will need to think hard about the causes of the changes they see in the cellphone data, says Nathan Eagle at MIT, who is working with Danon. Eagle looked at cellular data from a series of cholera outbreaks in Rwanda between 2006 and 2009. He saw a clear reduction in people’s movement, which may have been due to the disease. But the outbreak was caused by floods, which also limited mobility. Distinguishing between the two possible causes on the basis of phone data alone was impossible, he says.

Madan presented his paper last month at the International Conference on Ubiquitous Computing in Copenhagen, Denmark.

Reference Link
http://www.newscientist.com/article/mg20827824.800-cellphones-reveal-emerging-disease-outbreaks.html

Courtesy
Reed Business Information Ltd.