Networks and the epidemiology of directly transmitted infectious diseases are fundamentally linked. The foundations of epidemiology and early epidemiological models were based on population wide random-mixing, but in practice each individual has a finite set of contacts to whom they can pass infection; the ensemble of all such contacts forms a 'mixing network'. Knowledge of the structure of the network allows models to compute the epidemic dynamics at the population scale from the individual-level behaviour of infections. Therefore, characteristics of mixing networks—and how these deviate from the random-mixing norm—have become important applied concerns that may enhance the understanding and prediction of epidemic patterns and intervention measures.
%0 Journal Article
%1 Keeling2005Networks
%A Keeling, Matt J.
%A Eames, Ken T. D.
%B Journal of The Royal Society Interface
%C Department of Biological Sciences & Mathematics, University of Warwick, Institute Gibbet Hill Road, Coventry CV4 7AL, UK. m.j.keeling@warwick.ac.uk
%D 2005
%I The Royal Society
%J Journal of The Royal Society Interface
%K epidemiology networks sir
%N 4
%P 295--307
%R 10.1098/rsif.2005.0051
%T Networks and epidemic models
%U http://dx.doi.org/10.1098/rsif.2005.0051
%V 2
%X Networks and the epidemiology of directly transmitted infectious diseases are fundamentally linked. The foundations of epidemiology and early epidemiological models were based on population wide random-mixing, but in practice each individual has a finite set of contacts to whom they can pass infection; the ensemble of all such contacts forms a 'mixing network'. Knowledge of the structure of the network allows models to compute the epidemic dynamics at the population scale from the individual-level behaviour of infections. Therefore, characteristics of mixing networks—and how these deviate from the random-mixing norm—have become important applied concerns that may enhance the understanding and prediction of epidemic patterns and intervention measures.
@article{Keeling2005Networks,
abstract = {Networks and the epidemiology of directly transmitted infectious diseases are fundamentally linked. The foundations of epidemiology and early epidemiological models were based on population wide random-mixing, but in practice each individual has a finite set of contacts to whom they can pass infection; the ensemble of all such contacts forms a 'mixing network'. Knowledge of the structure of the network allows models to compute the epidemic dynamics at the population scale from the individual-level behaviour of infections. Therefore, characteristics of mixing networks—and how these deviate from the random-mixing norm—have become important applied concerns that may enhance the understanding and prediction of epidemic patterns and intervention measures.},
added-at = {2018-12-02T16:09:07.000+0100},
address = {Department of Biological Sciences \& Mathematics, University of Warwick, Institute Gibbet Hill Road, Coventry CV4 7AL, UK. m.j.keeling@warwick.ac.uk},
author = {Keeling, Matt J. and Eames, Ken T. D.},
biburl = {https://www.bibsonomy.org/bibtex/2493799344e6cb8f60825bbe4b2023c4d/karthikraman},
booktitle = {Journal of The Royal Society Interface},
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citeulike-linkout-0 = {http://dx.doi.org/10.1098/rsif.2005.0051},
citeulike-linkout-1 = {http://rsif.royalsocietypublishing.org/content/2/4/295.abstract},
citeulike-linkout-2 = {http://rsif.royalsocietypublishing.org/content/2/4/295.full.pdf},
citeulike-linkout-3 = {http://rsif.royalsocietypublishing.org/cgi/content/abstract/2/4/295},
citeulike-linkout-4 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1578276/},
citeulike-linkout-5 = {http://view.ncbi.nlm.nih.gov/pubmed/16849187},
citeulike-linkout-6 = {http://www.hubmed.org/display.cgi?uids=16849187},
day = 22,
doi = {10.1098/rsif.2005.0051},
interhash = {34ce581194e2ac9e116adaa81bc567b6},
intrahash = {493799344e6cb8f60825bbe4b2023c4d},
issn = {1742-5662},
journal = {Journal of The Royal Society Interface},
keywords = {epidemiology networks sir},
month = sep,
number = 4,
pages = {295--307},
pmcid = {PMC1578276},
pmid = {16849187},
posted-at = {2015-11-10 09:28:31},
priority = {2},
publisher = {The Royal Society},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Networks and epidemic models},
url = {http://dx.doi.org/10.1098/rsif.2005.0051},
volume = 2,
year = 2005
}