Mathematical models as tools for evaluating the effectiveness of interventions: a comment on Levin.

Kristinsson, KG

dc.contributor.author	Kristinsson, KG
dc.date.accessioned	2008-07-29T11:32:21Z
dc.date.available	2008-07-29T11:32:21Z
dc.date.issued	2001-09-15
dc.date.submitted	2008-07-29
dc.identifier.citation	Clin. Infect. Dis. 2001, 33 Suppl 3:S174-9	en
dc.identifier.issn	1058-4838
dc.identifier.pmid	11524716
dc.identifier.doi	10.1086/321845
dc.identifier.uri	http://hdl.handle.net/2336/33573
dc.description	To access full text version of this article. Please click on the hyperlink "View/Open" at the bottom of this page	en
dc.description.abstract	Possible interventions to minimize resistance rates are numerous and can involve reduction and/or change in antimicrobial use, infection control, and vaccinations. As mathematical models are becoming more realistic they can be useful to quantitatively evaluate the relative contribution of individual risk factors and for the planning of future intervention strategies. The fitness cost associated with resistance is an important parameter and small differences can have a profound effect on the results. The mathematical models presented for communities predicted that even with cessation of antibiotic use, the decline in resistance frequency would be slow. This contrasts with successful interventions in Finland and Iceland. Future models have to include important variables such as herd immunity and take into account the heterogeneity of open communities. Provision of susceptible strains from areas with low resistance rates to areas with high resistance rates can have a profound effect on the success of interventions to minimize resistance.
dc.language.iso	en	en
dc.publisher	The University of Chicago Press	en
dc.relation.url	http://www.journals.uchicago.edu/doi/abs/10.1086/321845	en
dc.subject.mesh	Anti-Bacterial Agents	en
dc.subject.mesh	Drug Resistance, Bacterial	en
dc.subject.mesh	Hospitals	en
dc.subject.mesh	Humans	en
dc.subject.mesh	Mathematical Computing	en
dc.subject.mesh	Models, Biological	en
dc.subject.mesh	Residence Characteristics	en
dc.title	Mathematical models as tools for evaluating the effectiveness of interventions: a comment on Levin.	en
dc.type	Article	en
dc.contributor.department	Department of Microbiology, National University Hospital, Reykjavik, Iceland. karl@rsp.is	en
dc.identifier.journal	Clinical infectious diseases : an official publication of the Infectious Diseases Society of America	en
refterms.dateFOA	2018-09-12T13:55:42Z
html.description.abstract	Possible interventions to minimize resistance rates are numerous and can involve reduction and/or change in antimicrobial use, infection control, and vaccinations. As mathematical models are becoming more realistic they can be useful to quantitatively evaluate the relative contribution of individual risk factors and for the planning of future intervention strategies. The fitness cost associated with resistance is an important parameter and small differences can have a profound effect on the results. The mathematical models presented for communities predicted that even with cessation of antibiotic use, the decline in resistance frequency would be slow. This contrasts with successful interventions in Finland and Iceland. Future models have to include important variables such as herd immunity and take into account the heterogeneity of open communities. Provision of susceptible strains from areas with low resistance rates to areas with high resistance rates can have a profound effect on the success of interventions to minimize resistance.