Influenza A(H1N1) Outbreak 2009 ("Swine Flu")
We are using high performance computational
techniques and multi-layer, large scale computer
simulations to project the time course of the H1N1 flu
epidemic in the United States. Our simulations yield
projections and risk assessments of the epidemic outbreak
in a worst case scenario, in which no containment measures
are taken to mitigate the spread. Our modeling is based on
the current knowledge of the disease parameters and takes
into account the backbone of spatial spread: A precise
estimate of human mobility on spatial scales between a few
and a few thousand kilometers.
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Tour de Sys: The Traveler's View of a Network
Tomography is a procedure long used in the biological
and physical sciences to study an object by producing
images of many thin slices of it, rather than trying to
study a picture of the entire object all at one. In this
project, we apply this idea to complex networks. Using
shortest-path trees to organize the network into a series
of slices allows us to measure global properties of the
system conditioned on location.
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Community Structure in Multi-Scale Transportation
Networks
Large scale communities and their geographical
boundaries are key determinants of various human mediated
spatially extended dynamical phenomena. The geographic
spread of emergent human infectious diseases such as SARS
(severe acute respiratory system) and seasonal and pandemic
influenza A are prime examples.
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Travel Bugs, Geocaching and European Traffic
Networks
In this project we investigate the behavior of over
900,000 travel bugs. These tagged items play a role in a
popular international game known as geocaching (see e.g.
www.geocaching.com), a modern type of
GPS treasure hunt. Travel bugs travel long distances
across political, national and regional boundaries and
their position is known with very high precision.
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Impact of Social Heterogeneities in Epidemic
Outbreaks
Typical epidemiological models rest on two key
assumptions: That a population is well mixed and that
transmission is triggered by a population-averaged contact
rate. However, experimental evidence shows that contact
rates vary substantially, and it has been shown that this
variability can change the dynamics of a disease.
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Panic Reactions and Global Disease Dynamics
When a disease is spreading through a population, a
single person can certainly safe herself from getting
infected by running away from affected areas. However, when
a large part of the population is responding to a
forthcoming disease by changing their dispersal behavior,
the disease spread can be severely impacted, leading to
qualitatively different dynamics.
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