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
Athletics
Donor Impact
A Team of Their Own
Meijer Campus
Empowered. Educated. Engineers.
Breathing Life into Historic Sites
Sustainability
Research
Q&A Snell and Stanton
Alumni News
Off the Path
Winter 2016 GVMagazine
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