chl@article{vazquez2013using,
  title = {{Using GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment}},
  author = {Vazquez-Prokopec, Gonzalo M and Bisanzio, Donal and Stoddard, Steven T and Paz-Soldan, Valerie and Morrison, Amy C and Elder, John P and Ramirez-Paredes, Jhon and Halsey, Eric S and Kochel, Tadeusz J and Scott, Thomas W and others},
  journal = {PloS one},
  volume = {8},
  number = {4},
  pages = {e58802},
  year = {2013},
  publisher = {Public Library of Science},
}


@article{balcan2009multiscale,
  title = {{Multiscale mobility networks and the spatial spreading of infectious diseases}},
  author = {Balcan, Duygu and Colizza, Vittoria and Gon{\c{c}}alves, Bruno and Hu, Hao and Ramasco, Jos{\'e} J and Vespignani, Alessandro},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {106},
  number = {51},
  pages = {21484--21489},
  year = {2009},
  publisher = {National Acad Sciences},
}


@article{bajardi2011human,
  title = {{Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic}},
  author = {Bajardi, Paolo and Poletto, Chiara and Ramasco, Jose J and Tizzoni, Michele and Colizza, Vittoria and Vespignani, Alessandro},
  journal = {PloS one},
  volume = {6},
  number = {1},
  pages = {e16591},
  year = {2011},
  publisher = {Public Library of Science},
}


@article{Kamp2010,
  title = {{Untangling the interplay between epidemic spread and transmission network dynamics}},
  author = {Kamp, Christel},
  journal = {PLoS Computational Biology},
  volume = {6},
  number = {11},
  pages = {e1000984},
  year = {2010},
  publisher = {Public Library of Science},
}


@article{Rizzo2014,
  title = {{Effect of individual behavior on epidemic spreading in activity-driven networks}},
  author = {Rizzo, Alessandro and Frasca, Mattia and Porfiri, Maurizio},
  journal = {Physical Review E},
  volume = {90},
  number = {4},
  pages = {042801},
  year = {2014},
  publisher = {APS},
}


@article{Wang2012,
  title = {{Safety-information-driven human mobility patterns with metapopulation epidemic dynamics}},
  author = {Wang, Bing and Cao, Lang and Suzuki, Hideyuki and Aihara, Kazuyuki},
  journal = {Scientific reports},
  volume = {2},
  year = {2012},
  publisher = {Nature Publishing Group},
}


@article{Meloni2011,
  title = {{Modeling human mobility responses to the large-scale spreading of infectious diseases}},
  author = {Meloni, Sandro and Perra, Nicola and Arenas, Alex and G{\'o}mez, Sergio and Moreno, Yamir and Vespignani, Alessandro},
  journal = {Scientific reports},
  volume = {1},
  year = {2011},
  publisher = {Nature Publishing Group},
}


@article{Merler2010,
  title = {{The role of population heterogeneity and human mobility in the spread of pandemic influenza}},
  author = {Merler, Stefano and Ajelli, Marco},
  journal = {Proceedings of the Royal Society B: Biological Sciences},
  volume = {277},
  number = {1681},
  pages = {557--565},
  year = {2010},
  publisher = {The Royal Society},
}


@article{Buscarino2014,
  title = {{Local and global epidemic outbreaks in populations moving in inhomogeneous environments}},
  author = {Buscarino, Arturo and Fortuna, Luigi and Frasca, Mattia and Rizzo, Alessandro},
  journal = {Physical Review E},
  volume = {90},
  number = {4},
  pages = {042813},
  year = {2014},
  publisher = {APS},
}


@article{Funk2010,
  title = {{Modelling the influence of human behaviour on the spread of infectious diseases: a review}},
  author = {Funk, Sebastian and Salath{\'e}, Marcel and Jansen, Vincent AA},
  journal = {Journal of the Royal Society Interface},
  volume = {7},
  number = {50},
  pages = {1247--1256},
  year = {2010},
  publisher = {The Royal Society},
}


@article{Eames2009,
  title = {{Epidemic prediction and control in weighted networks}},
  author = {Eames, Ken T. D. and Read, Jonathan M. and Edmunds, W. John},
  journal = {Epidemics},
  volume = {1},
  number = {1},
  pages = {70--76},
  year = {2009},
  publisher = {Elsevier},
}


@article{Aral2000,
  title = {{Behavioral aspects of sexually transmitted diseases: core groups and bridge populations}},
  author = {Aral, Sevgi Okten},
  journal = {Sexually transmitted diseases},
  volume = {27},
  number = {6},
  pages = {327--328},
  year = {2000},
  publisher = {LWW},
}


@article{Bengtsson2011,
  title = {{Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti}},
  author = {Bengtsson, Linus and Lu, Xin and Thorson, Anna and Garfield, Richard and Von Schreeb, Johan},
  journal = {PLoS medicine},
  volume = {8},
  number = {8},
  pages = {e1001083},
  year = {2011},
  publisher = {Public Library of Science},
}


@article{Candia2008,
  title = {{Uncovering individual and collective human dynamics from mobile phone records}},
  author = {Candia, Juli{\'a}n and Gonz{\'a}lez, Marta C and Wang, Pu and Schoenharl, Timothy and Madey, Greg and Barab{\'a}si, Albert-L{\'a}szl{\'o}},
  journal = {Journal of Physics A: Mathematical and Theoretical},
  volume = {41},
  number = {22},
  pages = {224015},
  year = {2008},
  publisher = {IOP Publishing},
}


@misc{ebola_forbes,
  author = {JV Chamary},
  title = {{Ebola Is Coming. A Travel Ban Won't Stop Outbreaks}},
  url = {http://www.forbes.com/sites/jvchamary/2014/10/13/ebola-travel/},
  abstract = {Outbreaks begin with imported cases of Ebola, which has led Americans to ask: Why don't we just ban flights from Africa?},
  urldate = {2014-10-15},
  journal = {Forbes},
  year = {2014},
  keywords = {Health, healthcare, Healthcare Innovation, Innovation and Science, Innovation \& Science, Pharma and Health, Pharma \& Healthcare, Tech},
}


@misc{gates_gis,
  author = {Bill Gates},
  title = {{{GIS} Mapping \& {GPS} Tracking for Polio in Nigeria}},
  url = {http://www.gatesnotes.com/Health/GIS-Mapping-GPS-Tracking-for-Polio-in-Nigeria},
  abstract = {A digital mapping system is being used in Nigeria to help health workers target specific areas for immunization efforts in the fight or eradicate polio.},
  urldate = {2014-10-27},
  journal = {gatesnotes},
  year = {2014},
}


@article{Zhong_2013,
  doi = {10.1016/j.pmcj.2013.07.009},
  url = {http://dx.doi.org/10.1016/j.pmcj.2013.07.009},
  year = {2013},
  month = {dec},
  publisher = {Elsevier {BV}},
  volume = {9},
  number = {6},
  pages = {823--837},
  author = {Erheng Zhong and Ben Tan and Kaixiang Mo and Qiang Yang},
  title = {{User demographics prediction based on mobile data}},
  journal = {Pervasive and Mobile Computing},
}


@article{de_montjoye_d4d-senegal:_2014,
  title = {{D4D-Senegal: The Second Mobile Phone Data for Development Challenge}},
  shorttitle = {D4D-Senegal},
  url = {http://arxiv.org/abs/1407.4885},
  abstract = {The D4D-Senegal challenge is an open innovation data challenge on anonymous call patterns of Orange's mobile phone users in Senegal. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Senegalese population. Participants to the challenge are given access to four mobile phone datasets. This paper describes the three datasets. The datasets are based on Call Detail Records ({CDR}) of phone calls and text exchanges between more than 9 million of Orange's customers in Senegal between January 1, 2013 to December 31, 2013. The datasets are: (1) antenna-to-antenna traffic for 1666 antennas on an hourly basis, (2) fine-grained mobility data on a rolling 2-week basis for a year with bandicoot behavioral indicators at individual level for about 300,000 randomly sampled users, (3) one year of coarse-grained mobility data at arrondissement level with bandicoot behavioral indicators at individual level for about 150,000 randomly sampled users},
  urldate = {2014-07-21},
  journal = {{arXiv}:1407.4885 [physics]},
  author = {de Montjoye, Yves-Alexandre and Smoreda, Zbigniew and Trinquart, Romain and Ziemlicki, Cezary and Blondel, Vincent D.},
  month = {jul},
  year = {2014},
  note = {{arXiv}: 1407.4885},
  keywords = {Computer Science - Computers and Society, Computer Science - Social and Information Networks, Physics - Physics and Society},
  file = {arXiv.org Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/QGW488RX/1407.html:text/html;de Montjoye et al. - 2014 - D4D-Senegal The Second Mobile Phone Data for Deve.pdf:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/69FWGIVI/de Montjoye et al. - 2014 - D4D-Senegal The Second Mobile Phone Data for Deve.pdf:application/pdf},
}


@article{lloyd-smith_superspreading_2005,
  title = {{Superspreading and the effect of individual variation on disease emergence}},
  volume = {438},
  copyright = {© 2005 Nature Publishing Group},
  issn = {0028-0836},
  url = {http://www.nature.com/nature/journal/v438/n7066/abs/nature04153.html},
  doi = {10.1038/nature04153},
  abstract = {Population-level analyses often use average quantities to describe heterogeneous systems, particularly when variation does not arise from identifiable groups. A prominent example, central to our current understanding of epidemic spread, is the basic reproductive number, R 0, which is defined as the mean number of infections caused by an infected individual in a susceptible population. Population estimates of R 0 can obscure considerable individual variation in infectiousness, as highlighted during the global emergence of severe acute respiratory syndrome ({SARS}) by numerous 'superspreading events' in which certain individuals infected unusually large numbers of secondary cases. For diseases transmitted by non-sexual direct contacts, such as {SARS} or smallpox, individual variation is difficult to measure empirically, and thus its importance for outbreak dynamics has been unclear. Here we present an integrated theoretical and statistical analysis of the influence of individual variation in infectiousness on disease emergence. Using contact tracing data from eight directly transmitted diseases, we show that the distribution of individual infectiousness around R 0 is often highly skewed. Model predictions accounting for this variation differ sharply from average-based approaches, with disease extinction more likely and outbreaks rarer but more explosive. Using these models, we explore implications for outbreak control, showing that individual-specific control measures outperform population-wide measures. Moreover, the dramatic improvements achieved through targeted control policies emphasize the need to identify predictive correlates of higher infectiousness. Our findings indicate that superspreading is a normal feature of disease spread, and to frame ongoing discussion we propose a rigorous definition for superspreading events and a method to predict their frequency.},
  language = {en},
  number = {7066},
  urldate = {2014-10-15},
  journal = {Nature},
  author = {Lloyd-Smith, James O. and Schreiber, Sebastian J. and Kopp, P. Ekkehard and Getz, Wayne M.},
  month = {nov},
  year = {2005},
  pages = {355--359},
  file = {Lloyd-Smith et al_2005_Superspreading and the effect of individual variation on disease emergence.pdf:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/VB8NRNX5/Lloyd-Smith et al_2005_Superspreading and the effect of individual variation on disease emergence.pdf:application/pdf;Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/DE5X4X9Z/nature04153.html:text/html},
}


@article{kitsak_identification_2010,
  title = {{Identification of influential spreaders in complex networks}},
  volume = {6},
  copyright = {© 2010 Nature Publishing Group},
  issn = {1745-2473},
  url = {http://www.nature.com/nphys/journal/v6/n11/abs/nphys1746.html},
  doi = {10.1038/nphys1746},
  abstract = {Networks portray a multitude of interactions through which people meet, ideas are spread and infectious diseases propagate within a society. Identifying the most efficient ‘spreaders’ in a network is an important step towards optimizing the use of available resources and ensuring the more efficient spread of information. Here we show that, in contrast to common belief, there are plausible circumstances where the best spreaders do not correspond to the most highly connected or the most central people. Instead, we find that the most efficient spreaders are those located within the core of the network as identified by the k-shell decomposition analysis, and that when multiple spreaders are considered simultaneously the distance between them becomes the crucial parameter that determines the extent of the spreading. Furthermore, we show that infections persist in the high-k shells of the network in the case where recovered individuals do not develop immunity. Our analysis should provide a route for an optimal design of efficient dissemination strategies.},
  language = {en},
  number = {11},
  urldate = {2014-09-24},
  journal = {Nature Physics},
  author = {Kitsak, Maksim and Gallos, Lazaros K. and Havlin, Shlomo and Liljeros, Fredrik and Muchnik, Lev and Stanley, H. Eugene and Makse, Hernan A.},
  month = {nov},
  year = {2010},
  pages = {888--893},
  file = {Kitsak et al_2010_Identification of influential spreaders in complex networks.pdf:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/SV45WU9E/Kitsak et al_2010_Identification of influential spreaders in complex networks.pdf:application/pdf;Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/QU5NWRZV/nphys1746.html:text/html},
}


@article{murphy_contact_2014,
  title = {{Contact Tracing Is Called Pivotal in Fighting Ebola}},
  issn = {0362-4331},
  url = {http://www.nytimes.com/2014/10/03/us/tracing-ebola-contacts-can-stop-virus-in-its-tracks-experts-say.html},
  abstract = {Although Ebola is new to the United States, the goal of contact tracing is the same in any disease: Track down those who could have been exposed.},
  urldate = {2014-10-15},
  journal = {The New York Times},
  author = {Murphy, Heather},
  month = {oct},
  year = {2014},
  keywords = {Centers for Disease Control and Prevention, Duncan, Thomas Eric, Ebola Virus, Frieden, Thomas R, Texas},
  file = {New York Times Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/CWQQ27S8/tracing-ebola-contacts-can-stop-virus-in-its-tracks-experts-say.html:text/html},
}


@book{vapnik1998statistical,
  title = {{Statistical learning theory}},
  author = {Vladimir Vapnik},
  year = {1998},
  publisher = {Wiley New York},
}


@article{fasina2014transmission,
  title = {{Transmission dynamics and control of Ebola virus disease outbreak in Nigeria, July to September 2014}},
  author = {{Folorunso Oludayo} Fasina and Adebayo Shittu and David Lazarus and Oyewale Tomori and Lone Simonsen and Cecile Viboud and Gerardo Chowell},
  journal = {Eurosurveillance},
  volume = {19},
  issue = {40},
  month = {October},
  year = {2014},
}


@article{Colizza_2007,
  doi = {10.1103/physrevlett.99.148701},
  url = {http://dx.doi.org/10.1103/PhysRevLett.99.148701},
  year = {2007},
  month = {oct},
  publisher = {American Physical Society ({APS})},
  volume = {99},
  number = {14},
  author = {Vittoria Colizza and Alessandro Vespignani},
  title = {{Invasion Threshold in Heterogeneous Metapopulation Networks}},
  journal = {Phys. Rev. Lett.},
}


@misc{economist_call_2014,
  title = {{Call for help}},
  issn = {0013-0613},
  url = {http://www.economist.com/news/leaders/21627623-mobile-phone-records-are-invaluable-tool-combat-ebola-they-should-be-made-available},
  abstract = {Mobile-phone records are an invaluable tool to combat Ebola. They should be made available to researchers},
  urldate = {2014-10-27},
  author = {The Economist},
  month = {oct},
  year = {2014},
  file = {The Economist Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/VVCSHD8P/21627623-mobile-phone-records-are-invaluable-tool-combat-ebola-they-should-be-made-available.html:text/html},
}


@inproceedings{Leontiadis_2014,
  doi = {10.1145/2674005.2674982},
  url = {http://dx.doi.org/10.1145/2674005.2674982},
  year = {2014},
  publisher = {{ACM} Press},
  author = {Ilias Leontiadis and Antonio Lima and Haewoon Kwak and Rade Stanojevic and David Wetherall and Konstantina Papagiannaki},
  title = {{From Cells to Streets}},
  booktitle = {Proceedings of the 10th {ACM} International on Conference on emerging Networking Experiments and Technologies - {CoNEXT} {\textquotesingle}14},
}


@article{Balcan_2009,
  doi = {10.1073/pnas.0906910106},
  url = {http://dx.doi.org/10.1073/pnas.0906910106},
  year = {2009},
  month = {dec},
  publisher = {Proceedings of the National Academy of Sciences},
  volume = {106},
  number = {51},
  pages = {21484--21489},
  author = {Duygu Balcan and Vittoria Colizza and Bruno Goncalves and Hao Hu and Jose J. Ramasco and Alessandro Vespignani},
  title = {{Multiscale mobility networks and the spatial spreading of infectious diseases}},
  journal = {Proceedings of the National Academy of Sciences},
}


@article{Althaus_2014,
  doi = {10.1371/currents.outbreaks.91afb5e0f279e7f29e7056095255b288},
  url = {http://dx.doi.org/10.1371/currents.outbreaks.91afb5e0f279e7f29e7056095255b288},
  year = {2014},
  publisher = {Public Library of Science ({PLoS})},
  author = {Christian L. Althaus},
  title = {{Estimating the Reproduction Number of Ebola Virus ({EBOV}) During the 2014 Outbreak in West Africa}},
  journal = {{PLoS} Current Outbreaks},
}


@article{dalziel2013human,
  title = {{Human mobility patterns predict divergent epidemic dynamics among cities}},
  author = {Dalziel, Benjamin D and Pourbohloul, Babak and Ellner, Stephen P},
  journal = {Proceedings of the Royal Society B: Biological Sciences},
  volume = {280},
  number = {1766},
  pages = {20130763},
  year = {2013},
  publisher = {The Royal Society},
}


@misc{who_senegal_2014,
  title = {{WHO} congratulates {Senegal} on ending {Ebola} transmission}},
  url = {http://www.who.int/mediacentre/news/statements/2014/senegal-ends-ebola/en/},
  abstract = {WHO officially declares the Ebola outbreak in Senegal over and commends the country on its diligence to end the transmission of the virus.},
  urldate = {2015-02-12},
  author = {WHO},
  year = {2014},
  file = {Snapshot:/Users/anto/Library/Application Support/Zotero/Profiles/hjngmax6.default/zotero/storage/8WAMIPFA/en.html:text/html},
}