Visit additional Tabor Communication Publications
December 17, 2009
BLOOMINGTON, Ind., Dec. 17 -- The interplay of human mobility patterns like those between local metropolitan commuters and long-range airline travelers during a global epidemic can be modeled in such detail so as to offer refined views of epidemics that could aid in public health emergency decision making, according to new research published by a team led by informaticists at Indiana University.
The findings, published this week in the Proceedings of the National Academy of Sciences' Online Early Edition, also note that with these refined computational strategies, new levels of accuracy about the behavior of targeted mobility networks and epidemic progression can be imagined.
The research team, led by IU informaticist and physicist Alessandro Vespignani, also found that with these strategies a better balance could be struck during a real-time public health emergency between needed computational time and refining the flexibility of human mobility and infectious disease models.
"The present analysis opens the path to quantitative approximation schemes that calibrate the level of data resolution and the needed computational resources with respect to the accuracy in the description of the epidemics," said Vespignani, Rudy Professor in the School of Informatics and Computing. "These results already have contributed to the improvement of the computational models we use to provide estimates and projections of the H1N1 pandemic."
Using population data centered around the locations of 220 International Air Transport Association-indexed airports, the group identified a data set of 3,363 subpopulations that was put into a model along with commuting data from 29 countries in five continents. Once the two data sets were mapped into the model, commuting networks were constructed at the subpopulation level, and a third data layer for a hypothetical pandemic influenza was included.
Simulations were then conducted that allowed the researchers to discriminate between the main contributions of both the long- (air traffic) and short-range (commuter) mobility flows to the pandemic spread.
"The global epidemic behavior is governed by the long-range airline traffic that determines the arrival of infectious individuals on a worldwide scale," Vespignani said. "At the local level, however, the short-range epidemic coupling induced by commuting flows creates a synchrony between neighboring regions and a local diffusive pattern with the epidemic flowing from subpopulations with major hubs into the neighboring subpopulations."
From a computational modeling perspective, Vespignani said the research is important in that it helps determine two things -- whether or not there may be one mobility scale most relevant toward defining a global epidemic pattern, and at which level of resolution of the epidemic's behavior does any given mobility scale become relevant.
When the researchers removed commuting flows from the worldwide air traffic model, the large scale pattern of the epidemic showed only small variations. On the other hand, the team found short-range mobility in the model increases the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of major transportation hubs.
"This approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework," Vespignani said. "These results clearly show that the level of detail on the mobility networks can be chosen according to the scale of interest."
Contributing with Vespignani on the paper were research scientists Duygu Balcan and Bruno Goncalves of the IU School of Informatics and Computing, and the Pervasive Technology Institute, IU Physics Department graduate student Hao Hu and research scientists Vittoria Colizza and Jose Ramasco of the Institute for Scientific Interchange Foundation in Torino, Italy.
Vespignani, who also holds joint appointments at IU in physics and statistics, is director of the School of Informatics and Computing's Center for Complex Networks and Systems Research and is associate director of the IU Pervasive Technology Institute's Digital Science Center.
This research was partially funded with grants from the National Institutes of Health, the Defense Threat Reduction Agency and the Lilly Endowment.
"Multiscale mobility networks and the spatial spreading of infectious diseases," PNAS Online Early Edition, http://www.eurekalert.org/pio/tipsheetdoc.php/237/zpq0500.pdf.
Source: Indiana University
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.