Winter 2016 GVMagazine - (Page 31)

RESEARCH Group uses big data to predict spread of Ebola by Leah Twilley A team of students and faculty the simulation system to "The Sims," a members led a study that used big data popular life simulation video game series. to understand how diseases, like Ebola, "In the program, there are essentially 13 spread in West Africa. million agents, representing each person The study was part of the Orange in the country. It models their movements Telecom Data 4 Development Challenge, and interactions, like a big, big version of a competition that provides restricted 'The Sims,'" said Wolffe. access to anonymized mobile phone data Leidig hopes public health policy sets from millions of subscribers living in makers in Senegal and Ivory Coast can Senegal and Ivory Coast. The challenge use the simulation system to conduct aims to make improvements to health, experiments designed to inform policy transportation, energy and agriculture decisions, such as mitigation strategies. by understanding how humans live and "If another outbreak occurs, our hope communicate in the regions. is that the simulation system we create The team was given proprietary data could be used to determine if tactics by the Orange Group and Sonatel, a cell such as public service announcements phone service provider in Senegal, which and closures at country borders, school provided information about the location, time of day and proximity to a cell tower when a call or text message was transmitted or received. The first study on the Ivory Coast took place in 2013; the second study on Senegal was in 2014, around the same time Ebola broke out in West Africa. "The most recent outbreak of Ebola was unprecedented because it took place in an urban environment. Past outbreaks didn't spread as quickly because they took place in rural settings," said Doug Graham, associate professor of biomedical sciences, who advised the team on aspects of Ebola virology and epidemiology. The team of nine students and four faculty members ran experiments on big data using a simulation software system they customized. Big data are large sets of digital information that can be examined to reveal patterns and trends. Jonathan Leidig, assistant professor of computing and information systems, said before the simulation system could be built, the team had to create several models - population, mobility and disease - to understand lifestyle patterns and movements, such as possible home and work locations and weekend trips. The models also helped determine how many people each person may have had contact with. "There is not a lot of data about developing countries because some areas are inaccessible or might not have up-to-date census information, which is also why we created the models," said Leidig. "By understanding where and how the populations live, the simulation system we built could predict how Map of cell phone towers and diseases spread from person-to-person geopolitical borders throughout the countries." in Senegal. Greg Wolffe, professor of computing and information systems, compared Orange Group Antennas and social events would be helpful in alleviating its spread," said Leidig. The study also included Jerry Scripps, assistant professor of computing and information systems, and students Kurt O'Hearn, Christine Sauer, Yuka Kutsumi, Nikko Vogel, Christopher Theisen, Adam Terwilliger, Michael Baldwin, Morgan Oneka and Bishal Chamling. MOVEMENT PATTERNS IN SENEGAL These maps outline movements between locations and provide details about mobility, social contacts and disease transmission pathways. Daily migration between residential areas and economic centers based on antenna locations in Dakar, the capital of Senegal. Home Population Work Population 31 Grand Valley Magazine

Table of Contents for the Digital Edition of Winter 2016 GVMagazine

Campus News
Focal Point
Donor Impact
A Team of Their Own
Meijer Campus
Empowered. Educated. Engineers.
Breathing Life into Historic Sites
Q&A Snell and Stanton
Alumni News
Off the Path

Winter 2016 GVMagazine