Morrow-Jones HA, Morrow-Jones CR (1991) Mobility due to natural disaster: theoretical considerations and preliminary analyses. Disasters 15(2):126-132

Article
Google Scholar

Myers K (2008) Remembering refugees: then and now by Tony Kushner. Cult Soc Hist 5(3):379-382

Article
Google Scholar

Bissell RA (1983) Delayed-impact infectious disease after a natural disaster. J Emerg Med 1(1):59-66

Article
Google Scholar

Watson JT, Gayer M, Connolly MA (2007) Epidemics after natural disasters. Emerg Infect Dis 13(1):1

Article
Google Scholar

Boyle C, Mudd G, Mihelcic JR, Anastas P, Collins T, Culligan P, Edwards M, Gabe J, Gallagher P, Handy S et al. (2010) Delivering sustainable infrastructure that supports the urban built environment. Environ Sci Technol 44(13):4836-4840

Article
Google Scholar

Sakaki T, Okazaki M, Matsuo Y (2010) Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proc. 19th Int. Conf. on WWW, pp 851-860

Google Scholar

Becker H, Naaman M, Gravano L (2011) Beyond trending topics: real-world event identification on Twitter. In: ICWSM ’11, pp 438-441

Google Scholar

Traag VA, Browet A, Calabrese F, Morlot F (2011) Social event detection in massive mobile phone data using probabilistic location inference. In: IEEE third international conference on social computing, pp 625-628

Google Scholar

The World in 2013, ICT Fact and Figures. http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2013-e.pdf. Accessed 24 Mar. 2016

Cox DR (1955) Some statistical methods connected with series of events. J R Stat Soc, Ser B, Methodol 17:129-164

MathSciNet
MATH
Google Scholar

Ihler A, Hutchins J, Smyth P (2006) Adaptive event detection with time-varying Poisson processes. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining, pp 207-216

Chapter
Google Scholar

Kapoor A, Eagle N, Horvitz E (2010) People, quakes, and communications: inferences from call dynamics about a seismic event and its influences on a population. In: AAAI spring symposium: artificial intelligence for development

Google Scholar

Bagrow JP, Wang D, Barabási A-L (2011) Collective response of human populations to large-scale emergencies. PLoS ONE 6(3):e17680. doi:10.1371/journal.pone.0017680

Article
Google Scholar

Bengtsson L, Lu X, Thorson A, Garfield R, Von Schreeb J (2011) Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti. PLoS Med 8(8):e1001083

Article
Google Scholar

Gething PW, Tatem AJ (2011) Can mobile phone data improve emergency response to natural disasters? PLoS Med 8(8):e1001085. doi:10.1371/journal.pmed.1001085

Article
Google Scholar

Lu X, Bengtsson L, Holme P (2012) Predictability of population displacement after the 2010 Haiti earthquake. Proc Natl Acad Sci 109(29):11576-11581

Article
Google Scholar

Gao L, Song C, Gao Z, Barabási A-L, Bagrow JP, Wang D (2014) Quantifying information flow during emergencies. Sci Rep 4:3997

Google Scholar

Data for Development Challenge. http://www.d4d.orange.com. Accessed 24 Mar. 2016

Blondel VD, Esch M, Chan C, Clérot F, Deville P, Huens E, Morlot F, Smoreda Z, Ziemlicki C (2012) Data for development: the d4d challenge on mobile phone data. arXiv preprint arXiv:1210.0137

Young WC, Blumenstock JE, Fox EB, McCormick TH (2014) Detecting and classifying anomalous behavior in spatiotemporal network data. In: Proceedings of the 2014 KDD workshop on learning about emergencies from social information (KDD-LESI 2014), pp 29-33

Google Scholar

Blondel VD, Decuyper A, Krings G (2015) A survey of results on mobile phone datasets analysis. EPJ Data Sci 4:10

Article
Google Scholar

Gonzalez MC, Hidalgo CA, Barabasi A-L (2008) Understanding individual human mobility patterns. Nature 453(7196):779-782

Article
Google Scholar

Kung KS, Greco K, Sobolevsky S, Ratti C (2014) Exploring universal patterns in human home-work commuting from mobile phone data. PLoS ONE 9(6):e96180

Article
Google Scholar

Miritello G, Lara R, Cebrian M, Moro E (2013) Limited communication capacity unveils strategies for human interaction. Sci Rep 3:1950

Article
Google Scholar

Schläpfer M, Bettencourt LM, Grauwin S, Raschke M, Claxton R, Smoreda Z, West GB, Ratti C (2014) The scaling of human interactions with city size. J R Soc Interface 11(98):20130789

Article
Google Scholar

Louail T, Lenormand M, Cantú OG, Picornell M, Herranz R, Frias-Martinez E, Ramasco JJ, Barthelemy M (2014) From mobile phone data to the spatial structure of cities. Sci Rep 4:5276

Article
Google Scholar

De Nadai M, Staiano J, Larcher R, Sebe N, Quercia D, Lepri B (2016) The death and life of great Italian cities: a mobile phone data perspective. In: Proceedings of the 25th international conference on world wide web. WWW ’16, Switzerland, pp 413-423

Google Scholar

Wesolowski A, Eagle N, Tatem AJ, Smith DL, Noor AM, Snow RW, Buckee CO (2012) Quantifying the impact of human mobility on malaria. Science 338(6104):267-270

Article
Google Scholar

Tizzoni M, Bajardi P, Decuyper A, King GKK, Schneider CM, Blondel V, Smoreda Z, González MC, Colizza V (2014) On the use of human mobility proxies for modeling epidemics. PLoS Comput Biol 10(7):e1003716

Article
Google Scholar

Deville P, Linard C, Martin S, Gilbert M, Stevens FR, Gaughan AE, Blondel VD, Tatem AJ (2014) Dynamic population mapping using mobile phone data. Proc Natl Acad Sci 111(45):15888-15893

Article
Google Scholar

Bogomolov A, Lepri B, Larcher R, Antonelli F, Pianesi F, Pentland A (2016) Energy consumption prediction using people dynamics derived from cellular network data. EPJ Data Sci 5:13

Article
Google Scholar

Eagle N, Macy M, Claxton R (2010) Network diversity and economic development. Science 328(5981):1029-1031

Article
MathSciNet
MATH
Google Scholar

Bogomolov A, Lepri B, Staiano J, Oliver N, Pianesi F, Pentland A (2014) Once upon a crime: towards crime prediction from demographics and mobile data. In: Proc. 16th ICMI. ACM, New York, pp 427-434

Google Scholar

Toole JL, Lin Y-R, Muehlegger E, Shoag D, González MC, Lazer D (2015) Tracking employment shocks using mobile phone data. J R Soc Interface 12(107):20150185

Article
Google Scholar

Altshuler Y, Fire M, Shmueli E, Elovici Y, Bruckstein A, Pentland AS, Lazer D (2013) Detecting anomalous behaviors using structural properties of social networks. In: Social computing, behavioral-cultural modeling and prediction. Springer, Berlin, pp 433-440

Chapter
Google Scholar

Gibson M (2006) Order from chaos: responding to traumatic events. The Policy Press, Bristol

Google Scholar

Akoglu L, Faloutsos C (2010) Event detection in time series of mobile communication graphs. In: Army science conference

Google Scholar

Dong Y, Pinelli F, Gkoufas Y, Nabi Z, Calabrese F, Chawla NV (2015) Inferring unusual crowd events from mobile phone call detail records. In: Machine learning and knowledge discovery in databases. Springer, Berlin, pp 474-492

Chapter
Google Scholar

Dobra A, Williams NE, Eagle N (2015) Spatiotemporal detection of unusual human population behavior using mobile phone data. PLoS ONE 10:0120449

Article
Google Scholar

Calabrese F, Pereira FC, Di Lorenzo G, Liu L, Ratti C (2010) The geography of taste: analyzing cell-phone mobility and social events. In: Pervasive computing. Springer, Berlin, pp 22-37

Chapter
Google Scholar

Paraskevopoulos P, Dinh T, Dashdorj Z, Palpanas T, Serafini L (2013) Identification and characterization of human behavior patterns from mobile phone data. In: International conference the analysis of mobile phone datasets (NetMob 2013). Special session on the data for development (D4D) challenge

Google Scholar

Zhang Y, Meratnia N, Havinga P (2010) Outlier detection techniques for wireless sensor networks: a survey. IEEE Commun Surv Tutor 12(2):159-170

Article
Google Scholar

Chib S (1998) Estimation and comparison of multiple change-point models. J Econom 86(2):221-241

Article
MathSciNet
MATH
Google Scholar

Raftery A, Akman V (1986) Bayesian analysis of a Poisson process with a change-point. Biometrika 73(1):85-89

Article
MathSciNet
MATH
Google Scholar

Gardner W, Mulvey EP, Shaw EC (1995) Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. Psychol Bull 118(3):392-404

Article
Google Scholar

Rodriguez-Avi J, Olmo-Jiménez MJ, Conde-sánchez A, Martínez-Rodríguez AM (2013) A new regression model for overdispersed count data. In: The 29th European meeting of statisticians, p 256

Google Scholar

Cameron AC, Trivedi PK (2013) Regression analysis of count data, vol 53. Cambridge University Press, Cambridge

Book
MATH
Google Scholar

White GC, Bennetts RE (1996) Analysis of frequency count data using the negative binomial distribution. Ecology 77(8):2549-2557

Article
Google Scholar

Zhang H, Dantu R, Cangussu JW (2009) Change point detection based on call detail records. In: IEEE international conference on intelligence and security informatics, 2009. ISI ’09. IEEE, New York, pp 55-60

Chapter
Google Scholar

Luong TM, Perduca V, Nuel G (2012) Hidden markov model applications in change-point analysis. arXiv preprint arXiv:1212.1778

Witayangkurn A, Horanont T, Sekimoto Y, Shibasaki R (2013) Anomalous event detection on large-scale gps data from mobile phones using hidden Markov model and cloud platform. In: Proceedings of the 2013 ACM conference on pervasive and ubiquitous computing adjunct publication. ACM, New York, pp 1219-1228

Chapter
Google Scholar

Scott SL, Smyth P (2003) The Markov modulated Poisson process and Markov Poisson cascade with applications to web traffic data. In: Bayesian statistics, vol 7, pp 671-680

Google Scholar

Chib S, Winkelmann R (2001) Markov chain Monte Carlo analysis of correlated count data. J Bus Econ Stat 19:4

Article
MathSciNet
Google Scholar

Scott SL (1999) Bayesian analysis of a two-state Markov modulated Poisson process. J Comput Graph Stat 8(3):662-670

Google Scholar

Yoshihara T, Kasahara S, Takahashi Y (2001) Practical time-scale fitting of self-similar traffic with Markov-modulated Poisson process. Telecommun Syst 17(1-2):185-211

Article
MATH
Google Scholar

African Mobile Observatory 2011. http://www.gsma.com/spectrum/wp-content/uploads/2011/12/Africa-Mobile-Observatory-2011.pdf. Accessed 24 Mar. 2016

Armed Conflict Location and Event Data Project. http://www.acleddata.com. Accessed 24 Mar. 2016

United Nations Refugee Agency. http://www.unhcr.org/pages/4d831f586.html

Shapiro JN, Weidmann NB (2011) Talking about killing: cell phones, collective action, and insurgent violence in Iraq. Technical report, DTIC Document

Pierskalla JH, Hollenbach FM (2013) Technology and collective action: the effect of cell phone coverage on political violence in Africa. Am Polit Sci Rev 107(2):207-224

Article
Google Scholar

Le Figaro Newspaper. http://www.lefigaro.fr/flash-actu/2012/02/13/97001-20120213FILWWW00689-cote-d-ivoire-3-morts-dans-des-violences.php. Accessed 24 Mar. 2016

United Nations Security Council Reports. http://www.securitycouncilreport.org/un-documents/cote-divoire/. Accessed 24 Mar. 2016

International Crisis Group Crisis Watch Database. http://www.crisisgroup.org/en/publication-type/crisiswatch/. Accessed 24 Mar. 2016