Measuring contact patterns with wearable sensors: Methods, data characteristics and applications to data-driven simulations of infectious diseases

Clinical Microbiology and Infection

Volumn 20, Issue 1, 2014, Pages 10-16

  Barrat, A ^a,b,c   Cattuto, C ^c   Tozzi, A E ^d   Vanhems, P ^e,f   Voirin, N ^e  

^a CENTRE DE PHYSIQUE THÉORIQUE   (France)

^b UNIVERSITÉ DE TOULON   (France)

^c ISI FOUNDATION   (Italy)

^d BAMBINO GESÙ CHILDREN S HOSPITAL   (Italy)

^e EDOUARD HERRIOT HOSPITAL   (France)

^f UNIVERSITÉ LYON 1   (France)

Author keywords

Contact patterns; Data driven; Infectious diseases; Modelling; Numerical simulations; Wearable sensors

Indexed keywords

DATA COLLECTION METHOD; DISEASE TRANSMISSION; EPIDEMIC; HUMAN; INFECTION; INFECTION CONTROL; MATHEMATICAL MODEL; PRIORITY JOURNAL; REVIEW; STATISTICAL ANALYSIS;

CONTACT PATTERNS; DATA-DRIVEN; INFECTIOUS DISEASES; MODELLING; NUMERICAL SIMULATIONS; WEARABLE SENSORS;

COMMUNICABLE DISEASE CONTROL; COMMUNICABLE DISEASES; DATA COLLECTION; DISEASE OUTBREAKS; EPIDEMIOLOGICAL MONITORING; HUMANS; MODELS, STATISTICAL; RADIO FREQUENCY IDENTIFICATION DEVICE;

EID: 84890672722     PISSN: 1198743X     EISSN: 14690691     Source Type: Journal    
DOI: 10.1111/1469-0691.12472     Document Type: Review

References (31)

1. Chowel G, Viboud C. A practical method to target individuals for outbreak detection and control. BMC Med 2013; 11: 36.
2. Smieszek T, Salathe M. A low-cost method to assess the epidemiological importance of individuals in controlling infectious disease outbreaks. BMC Med 2013; 11: 35.
3. Salathe M, Kazandjieva M, Lee JW, Levis P, Feldman MW, Jones JH. A high-resolution human contact network for infectious disease transmission. Proc Natl Acad Sci USA 2010; 107: 22020-22025.
4. Cauchemez S, Bhattarai A, Marchbanks TL et al. Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza. Proc Natl Acad Sci USA 2011; 108: 2825-2830.
5. Temime L, Opatowski L, Pannet Y, Brun-Buisson C, Boelle PY, Guillemot D. Peripatetic health-care workers as potential superspreaders. Proc Natl Acad Sci USA 2009; 106: 18420-18425.
6. Read JM, Edmunds WJ, Riley S, Lessler J, Cummings DA. Close encounters of the infectious kind: methods to measure social mixing behaviour. Epidemiol Infect 2012; 140: 2117-2130.
7. Beutels P, Shkedy Z, Aerts M, Van Damme P. Social mixing patterns for transmission models of close contact infections: exploring self-evaluation and diary-based data collection through a web-based interface. Epidemiol Infect 2006; 134: 1158-1166.
8. McCaw JM, Forbes K, Nathan PM et al. Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks. BMC Infect Dis 2010; 10: 166.
9. Mikolajczyk RT, Akmatov MK, Rastin S, Kretzschmar M. Social contacts of school children and the transmission of respiratory-spread pathogens. Epidemiol Infect 2008; 136: 813-822.
10. Mossong J, Hens N, Jit M et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med 2008; 5: e74.
11. Zagheni E, Billari FC, Manfredi P, Melegaro A, Mossong J, Edmunds WJ.Using time-use data to parameterize models for the spread of close-contact infectious diseases. Am J Epidemiol 2008; 168: 1082-1090.
12. Smieszek T, Burri EU, Scherzinger R, Scholz RW. Collecting close-contact social mixing data with contact diaries: reporting errors and biases. Epidemiol Infect 2012; 140: 744-752.
13. Danon L, Read JM, House TA, Vernon MC, Keeling MJ. Social encounter networks: characterizing Great Britain. Proc R Soc B 2013; 280: 20131037.
14. Read JM, Eames KT, Edmunds WJ. Dynamic social networks and the implications for the spread of infectious disease. J R Soc Interface 2008; 5: 1001-1007.
15. Smieszek T, Fiebig L, Scholz RW. Models of epidemics: when contact repetition and clustering should be included. Theor Biol Med Model 2009; 6: 11.
16. Stehlé J, Voirin N, Barrat A et al. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees. BMC Med 2011; 9: 87.
17. O'Neill E, Kostakos V, Kindberg T et al. Instrumenting the city: developing methods for observing and understanding the digital cityscape. Lect Notes Comput Sci (2006)4206: 315-332.
18. Pentland A. Honest signals: how they shape our world. Cambridge, MA: MIT Press, 2008.
19. Cattuto C, Van den Broeck W, Barrat A, Colizza V, Pinton JF, Vespignani A. Dynamics of person-to-person interactions from distributed RFID sensor networks. PLoS One 2010; 5: e11596.
20. Stehlé J, Voirin N, Barrat A et al. High-resolution measurements of face-to-face contact patterns in a primary school. PLoS One 2011; 6: e23176.
21. Isella L, Romano M, Barrat A et al. Close encounters in a pediatric ward: measuring face-to-face proximity and mixing patterns with wearable sensors. PLoS One 2011; 6: e17144.
22. Barabasi A-L. Bursts: the hidden pattern behind everything we do. Dutton Adult. (2010)
23. Vanhems P, Barrat A, Cattuto C et al. Estimating potential infection transmission routes in hospital wards using wearable proximity sensors. PLoS One 2013; 8: 73970.
24. Anderson RM, May RM. Infectious diseases of humans: dynamics and control. Oxford: Oxford University Press, 1992.
25. Pastor-Satorras R, Vespignani A. Epidemic spreading in scale-free networks. Phys Rev Lett 2001; 86: 3200-3203.
26. Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature 2005; 438: 355-359.
27. Machens A, Gesualdo F, Rizzo C, Tozzi AE, Barrat A, Cattuto C. An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices. BMC Infect Dis 2013; 13: 185.
28. Blower S, Go MH. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy? BMC Med 2011; 9: 88.
29. Gemmetto V, Barrat A, Cattuto C Mitigation of infectious diseases at school: targeted class closures vs school closures, to be submitted.(2013)
30. Curtis DE, Hlady C, Pemmaraju SV, Polgreen P, Segre AM Modeling and estimating the spatial distribution of healthcare workers. Proceedings of the 1st ACM International Health Informatics Symposium IHI'(2010) 10: 287-296.
31. Gardy JL, Johnston JC, Ho Sui SJ et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med 2011; 364: 730-739.