%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}, citeulike-article-id = {3015075}, 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 }