Science
Research
Projects
Publications
News
Team
Explorables
Contact
human mobility
Biases in human mobility data impact epidemic modeling
F Schlosser
,
Vedran Sekara
,
D Brockmann
,
Manuel Garcia-Herranz
arXiv:2112.12521
Large-scale human mobility data is a key resource in data-driven policy making and across many scientific fields. Most recently, mobility data was …
PDF
View
Finding disease outbreak locations from human mobility data
F Schlosser
,
D Brockmann
EPJ Data Science
Finding the origin location of an infectious disease outbreak quickly is crucial in mitigating its further dissemination. Current methods to identify …
PDF
Cite
DOI
View
New paper out: Finding disease outbreak locations from human mobility data
F Schlosser
,
D Brockmann
COVID-19 lockdown induces disease-mitigating structural changes in mobility networks
F Schlosser
,
B F Maier
,
O Jack
,
D Hinrichs
,
A Zachariae
,
D Brockmann
Proceedings of the National Academy of Sciences 117 (52), 32883-32890
In the wake of the COVID-19 pandemic many countries implemented containment measures toreduce disease transmission. Studies using digital data sources …
PDF
Cite
DOI
View
Human mobility, networks and disease dynamics on a global scale
D Brockmann
Bunde A., Caro J., Kärger J., Vogl G. (eds) Diffusive Spreading in Nature, Technology and Society. Springer, Cham.
Disease dynamics is a complex phenomenon and in order to address these questions expertises from many disciplines need to be integrated. One method …
Cite
DOI
View
A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin--destination demand networks
M Saberi
,
H S Mahmassani
,
D Brockmann
,
A Hosseini
Transportation 44, pages1383–1402
Urban travel demand, consisting of thousands or millions of origin–destination trips, can be viewed as a large-scale weighted directed graph. The …
PDF
Cite
DOI
View
Effective distances for epidemics spreading on complex networks
F Iannelli
,
A Koher
,
D Brockmann
,
P Hövel
,
I M Sokolov
Phys. Rev. E 95, 012313
We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general …
PDF
Cite
DOI
View
Understanding and predicting the global spread of emergent infectious diseases
D Brockmann
Public Health Forum | Band 22: Heft 3
The emergence and global spread of human infectious diseases has become one of the most serious public health threats of the 21st century. …
Cite
DOI
Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2
P Lemey
,
A Rambaut
,
T Bedford
,
N Faria
,
F Bielejec
,
G Baele
,
C A Russell
,
D J Smith
,
O G Pybus
,
D Brockmann
,
M A Suchard
PLoS Pathog 10(2): e1003932
What explains the geographic dispersal of emerging pathogens? Reconstructions of evolutionary history from pathogen gene sequences offer qualitative …
Cite
DOI
View
The hidden geometry of complex, network-driven contagion phenomena
D Brockmann
,
D Helbing
Science 342 (6164), 1337-1342
The global spread of epidemics, rumors, opinions, and innovations are complex, network-driven dynamic processes. The combined multiscale nature and …
PDF
Cite
DOI
View
»
Cite
×