K. Eames, S. Bansal, S. Frost, and S. Riley, Six challenges in measuring contact networks for use in modelling, Epidemics, vol.10, pp.72-77, 2015.
DOI : 10.1016/j.epidem.2014.08.006

N. Voirin, CONCLUSIONS, Infection Control & Hospital Epidemiology, vol.1, issue.03, p.254, 2015.
DOI : 10.1371/journal.pone.0079906

T. Obadia, Detailed Contact Data and the Dissemination of Staphylococcus aureus in Hospitals, PLOS Computational Biology, vol.74, issue.3, p.1004170, 2015.
DOI : 10.1371/journal.pcbi.1004170.s002
URL : https://hal.archives-ouvertes.fr/hal-01134050

J. Mossong, Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases, PLoS Medicine, vol.19, issue.3, p.74, 2008.
DOI : 10.1371/journal.pmed.0050074.sd001

R. T. Mikolajczyk, M. K. Akmatov, S. Rastin, and M. Kretzschmar, Social contacts of school children and the transmission of respiratory-spread pathogens, Epidemiology and Infection, vol.12, issue.06, pp.813-822, 2008.
DOI : 10.1017/S0950268805004528

A. Pentland, Honest signals, Proceedings of the 19th ACM international conference on Multimedia, MM '11, 2008.
DOI : 10.1145/2072298.2072374

C. Cattuto, Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks, PLoS ONE, vol.41, issue.7, p.11596, 2010.
DOI : 10.1371/journal.pone.0011596.s007
URL : https://hal.archives-ouvertes.fr/hal-00503275

M. Salathé, A high-resolution human contact network for infectious disease transmission, Proceedings of the National Academy of Sciences, vol.74, issue.1 Pt 2, pp.22020-22025, 2010.
DOI : 10.1103/PhysRevE.74.016110

A. J. Conlan, Measuring social networks in British primary schools through scientific engagement, Proceedings of the Royal Society B: Biological Sciences, vol.40, issue.11, pp.1467-75, 2011.
DOI : 10.1111/j.1440-1754.2004.00486.x
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3081745

T. Hornbeck, Using Sensor Networks to Study the Effect of Peripatetic Healthcare Workers on the Spread of Hospital-Associated Infections, Journal of Infectious Diseases, vol.206, issue.10, p.1549, 2012.
DOI : 10.1093/infdis/jis542

T. Smieszek, E. U. Burri, R. Scherzinger, and R. W. Scholz, Collecting close-contact social mixing data with contact diaries: reporting errors and biases, Epidemiology and Infection, vol.140, issue.04, pp.744-752, 2012.
DOI : 10.1371/journal.pone.0011596

J. M. Read, W. J. Edmunds, S. Riley, J. Lessler, and D. A. Cummings, Close encounters of the infectious kind: methods to measure social mixing behaviour, Epidemiology and Infection, vol.5, issue.12, pp.2117-2130, 2012.
DOI : 10.3201/eid1211.060426

A. Stopczynski, Measuring Large-Scale Social Networks with High Resolution, PLoS ONE, vol.28, issue.4, p.9597, 2014.
DOI : 10.1371/journal.pone.0095978.g015
URL : http://doi.org/10.1371/journal.pone.0095978

R. Mastrandrea, J. Fournet, and A. Barrat, Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys, PLOS ONE, vol.14, issue.6, p.136497, 2015.
DOI : 10.1371/journal.pone.0136497.s005
URL : https://hal.archives-ouvertes.fr/hal-01238308

D. J. Toth, The role of heterogeneity in contact timing and duration in network models of influenza spread in schools, Journal of The Royal Society Interface, vol.12, issue.108, p.20150279, 2015.
DOI : 10.1017/S0950268812000842

H. Guclu, Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA, PLOS ONE, vol.5, issue.7, p.151139, 2016.
DOI : 10.1371/journal.pone.0151139.s002
URL : http://doi.org/10.1371/journal.pone.0151139

T. Smieszek, How should social mixing be measured: comparing web-based survey and sensor-based methods, BMC Infectious Diseases, vol.8, issue.Suppl 5, p.136, 2014.
DOI : 10.1186/1471-2458-8-61
URL : http://doi.org/10.1186/1471-2334-14-136

T. Smieszek, Contact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants??? attitudes, BMC Infectious Diseases, vol.7, issue.6, p.341, 2016.
DOI : 10.1371/journal.pmed.1000291
URL : https://hal.archives-ouvertes.fr/hal-01348309

A. Stopczynski, P. Sapiezynski, and S. Lehmann, Temporal fidelity in dynamic social networks, The European Physical Journal B, vol.13, issue.10, p.249, 2015.
DOI : 10.1145/2509352.2509399
URL : http://arxiv.org/abs/1507.01484

S. H. Lee, P. Kim, and H. Jeong, Statistical properties of sampled networks, Physical Review E, vol.6, issue.1, p.16102, 2006.
DOI : 10.1103/PhysRevLett.87.258701
URL : http://arxiv.org/abs/cond-mat/0505232

G. Kossinets, Effects of missing data in social networks, Social Networks, vol.28, issue.3, pp.247-268, 2006.
DOI : 10.1016/j.socnet.2005.07.002

A. C. Ghani, C. A. Donnelly, and G. P. Garnett, Sampling biases and missing data in explorations of sexual partner networks for the spread of sexually transmitted diseases, Statistics in Medicine, vol.17, issue.18, pp.2079-2097, 1998.
DOI : 10.1002/(SICI)1097-0258(19980930)17:18<2079::AID-SIM902>3.0.CO;2-H

M. Génois, C. Vestergaard, C. Cattuto, and A. Barrat, Compensating for population sampling in simulations of epidemic spread on temporal contact networks, Nature Communications, vol.05, p.9860, 2015.
DOI : 10.1103/PhysRevE.83.066113

C. Vestergaard, E. Valdano, M. Génois, C. Poletto, V. Colizza et al., Impact of spatially constrained sampling of temporal contact networks on the evaluation of the epidemic risk, European Journal of Applied Mathematics, vol.1, issue.06, p.941, 2016.
DOI : 10.1209/0295-5075/89/38009
URL : https://hal.archives-ouvertes.fr/hal-01342800

C. A. Bliss, C. M. Danforth, and P. S. Dodds, Estimation of Global Network Statistics from Incomplete Data, PLoS ONE, vol.28, issue.10, p.108471, 2014.
DOI : 10.1371/journal.pone.0108471.s001

Y. Zhang, E. D. Kolaczyk, and B. D. Spencer, Estimating network degree distributions under sampling: An inverse problem, with applications to monitoring social media networks, The Annals of Applied Statistics, vol.9, issue.1, p.166, 2015.
DOI : 10.1214/14-AOAS800
URL : http://arxiv.org/abs/1305.4977

T. Squartini, G. Cimini, A. Gabrielli, and D. Garlaschelli, Network reconstruction via density sampling, Applied Network Science, vol.7, issue.3, p.3, 2017.
DOI : 10.1016/j.jfs.2010.12.001
URL : http://doi.org/10.1007/s41109-017-0021-8

R. Mastrandrea and A. Barrat, How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?, PLOS Computational Biology, vol.11, issue.8, p.1005002, 2016.
DOI : 10.1371/journal.pcbi.1005002.s001
URL : https://hal.archives-ouvertes.fr/hal-01337298

J. Fournet and A. Barrat, Epidemic risk from friendship network data: an equivalence with a non-uniform sampling of contact networks, Scientific Reports, vol.1509, issue.1, p.24593, 2016.
DOI : 10.1016/j.physa.2003.06.002
URL : https://hal.archives-ouvertes.fr/hal-01303335

J. Stehlé, Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees, BMC Medicine, vol.6, issue.Suppl 5, 2011.
DOI : 10.1371/journal.pone.0017144

A. Machens, An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices, BMC Infectious Diseases, vol.5, issue.1, p.185, 2013.
DOI : 10.1371/journal.pcbi.1001109
URL : https://hal.archives-ouvertes.fr/hal-00817269