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Networks in epidemiology

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Networks in epidemiology. / Eames, Ken T. D.; Read, Jonathan M.

Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers. ed. / Pietro Lio; Eiko Yoneki; Jon Crowcroft; Dinesh C. Verma. Berlin : Springer Verlag, 2008. p. 79-90 (Lecture Notes in Computer Science; Vol. 5151).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Eames, KTD & Read, JM 2008, Networks in epidemiology. in P Lio, E Yoneki, J Crowcroft & DC Verma (eds), Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers. Lecture Notes in Computer Science, vol. 5151, Springer Verlag, Berlin, pp. 79-90, 1st Workshop on Bio-Inspired Design of Networks, United Kingdom, 2/04/07. https://doi.org/10.1007/978-3-540-92191-2_8

APA

Eames, K. T. D., & Read, J. M. (2008). Networks in epidemiology. In P. Lio, E. Yoneki, J. Crowcroft, & D. C. Verma (Eds.), Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers (pp. 79-90). (Lecture Notes in Computer Science; Vol. 5151). Springer Verlag. https://doi.org/10.1007/978-3-540-92191-2_8

Vancouver

Eames KTD, Read JM. Networks in epidemiology. In Lio P, Yoneki E, Crowcroft J, Verma DC, editors, Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers. Berlin: Springer Verlag. 2008. p. 79-90. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-540-92191-2_8

Author

Eames, Ken T. D. ; Read, Jonathan M. / Networks in epidemiology. Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers. editor / Pietro Lio ; Eiko Yoneki ; Jon Crowcroft ; Dinesh C. Verma. Berlin : Springer Verlag, 2008. pp. 79-90 (Lecture Notes in Computer Science).

Bibtex

@inproceedings{f84311cb501846e5bd3dfffabb2a49a4,
title = "Networks in epidemiology",
abstract = "We discuss the uses of networks as epidemiological tools to describe the interactions taking place within populations. The difficulties of accurate measurement of real-world social networks are discussed, along with modelling approaches designed to require only incomplete data. Properties of human contact networks such as clustering and variable strengths of interactions are seen to he important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.",
keywords = "Infectious disease, social contact, epidemic, mathematical model, evolution, SEXUALLY-TRANSMITTED DISEASES, SOCIAL NETWORKS, INFECTIOUS-DISEASES, HIV TRANSMISSION, COMPLEX NETWORKS, GREAT-BRITAIN, SPREAD, MODELS, RISK, EVOLUTION",
author = "Eames, {Ken T. D.} and Read, {Jonathan M.}",
year = "2008",
doi = "10.1007/978-3-540-92191-2_8",
language = "English",
isbn = "9783540921905",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "79--90",
editor = "Pietro Lio and Eiko Yoneki and Jon Crowcroft and Verma, {Dinesh C.}",
booktitle = "Bio-inspired computing and communication",
note = "1st Workshop on Bio-Inspired Design of Networks ; Conference date: 02-04-2007 Through 05-04-2007",

}

RIS

TY - GEN

T1 - Networks in epidemiology

AU - Eames, Ken T. D.

AU - Read, Jonathan M.

PY - 2008

Y1 - 2008

N2 - We discuss the uses of networks as epidemiological tools to describe the interactions taking place within populations. The difficulties of accurate measurement of real-world social networks are discussed, along with modelling approaches designed to require only incomplete data. Properties of human contact networks such as clustering and variable strengths of interactions are seen to he important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.

AB - We discuss the uses of networks as epidemiological tools to describe the interactions taking place within populations. The difficulties of accurate measurement of real-world social networks are discussed, along with modelling approaches designed to require only incomplete data. Properties of human contact networks such as clustering and variable strengths of interactions are seen to he important factors in the spread of an epidemic. We consider the evolution of a pathogen spreading through a dynamic network and show that the pattern of contacts within a host population determines the evolutionary pressures that a pathogen experiences.

KW - Infectious disease

KW - social contact

KW - epidemic

KW - mathematical model

KW - evolution

KW - SEXUALLY-TRANSMITTED DISEASES

KW - SOCIAL NETWORKS

KW - INFECTIOUS-DISEASES

KW - HIV TRANSMISSION

KW - COMPLEX NETWORKS

KW - GREAT-BRITAIN

KW - SPREAD

KW - MODELS

KW - RISK

KW - EVOLUTION

U2 - 10.1007/978-3-540-92191-2_8

DO - 10.1007/978-3-540-92191-2_8

M3 - Conference contribution/Paper

SN - 9783540921905

T3 - Lecture Notes in Computer Science

SP - 79

EP - 90

BT - Bio-inspired computing and communication

A2 - Lio, Pietro

A2 - Yoneki, Eiko

A2 - Crowcroft, Jon

A2 - Verma, Dinesh C.

PB - Springer Verlag

CY - Berlin

T2 - 1st Workshop on Bio-Inspired Design of Networks

Y2 - 2 April 2007 through 5 April 2007

ER -