Tracking Illness to Stop an Outbreak

by  Josh O’Leary,   Iowa City Press-Citizen

In what has been called the “Age of Big Data,” when corporations are finding new ways to mine information to boost profits, University of Iowa professor Alberto Segre and a team of colleagues are channeling their work in data science to achieve something greater.

Segre is among the leaders of an interdisciplinary group of UI experts known as CompEpi, short for computational epidemiology, which conducts sophisticated data-driven research that probes how diseases spread. The team has put together studies as varied as tracking flu outbreaks using Twitter, to determining who should be vaccinated first among hospital staff to prevent the spread of an illness. 

With studies showing that the failure of health care workers to perform proper hand hygiene is one of the leading causes of health care associated infection such as MRSA, of particular interest to the research group has been how technology can be used to monitor and improve hand washing practices in hospitals.  ……

Since CompEpi was launched about five years ago, the researchers have conducted several studies through Iowa hospitals and clinics, starting with hiring graduate students to observe and record workers’ movements and interactions. Then the researchers used medical record system log-ins to track the workers’ movements throughout the hospital. The researchers also developed wearable computers consisting of a repurposed pager case that holds a processor and radio that broadcasts a worker’s location every 13 seconds. “One of our overarching goals is to develop computational approaches to help understand why and in what situations health care workers do not practice appropriate hand hygiene and to use our findings to help model and understand other behaviors in order to make hospitals safer,” says Iowa professor Phil Polgreen.

Other CompEpi research projects include a program that uses Twitter to monitor influenza proliferation by analyzing keywords and then uses the geo-tagged tweet locations to map cases of illness.  ….. Article

DCL:  Automated or Semi-automated (with humans in the loop) tracking of disease outbreaks using Social Networks has been going on since the 1990′s. The Canadians were among the first in the field, uncovering the SARS outbreak in rural China where the local authorities were trying to hide it. Good to see things are progressing in this particularly important area of real time event processing.