Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin
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...
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fthighwire:oai:open-archive.highwire.org:cid:33/Supplement_3/S174 2023-05-15T16:49:52+02:00 Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin Kristinsson, Karl G. 2001-09-15 00:00:00.0 text/html http://cid.oxfordjournals.org/cgi/content/short/33/Supplement_3/S174 https://doi.org/10.1086/321845 en eng Oxford University Press http://cid.oxfordjournals.org/cgi/content/short/33/Supplement_3/S174 http://dx.doi.org/10.1086/321845 Copyright (C) 2001, Infectious Diseases Society of America Supplement Articles TEXT 2001 fthighwire https://doi.org/10.1086/321845 2013-05-27T11:23:07Z 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. Text Iceland HighWire Press (Stanford University) Levin ENVELOPE(43.352,43.352,66.332,66.332) Clinical Infectious Diseases 33 s3 S174 S179 |
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HighWire Press (Stanford University) |
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English |
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Supplement Articles |
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Supplement Articles Kristinsson, Karl G. Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
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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. |
format |
Text |
author |
Kristinsson, Karl G. |
author_facet |
Kristinsson, Karl G. |
author_sort |
Kristinsson, Karl G. |
title |
Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
title_short |
Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
title_full |
Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
title_fullStr |
Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
title_full_unstemmed |
Mathematical Models as Tools for Evaluating the Effectiveness of Interventions: A Comment on Levin |
title_sort |
mathematical models as tools for evaluating the effectiveness of interventions: a comment on levin |
publisher |
Oxford University Press |
publishDate |
2001 |
url |
http://cid.oxfordjournals.org/cgi/content/short/33/Supplement_3/S174 https://doi.org/10.1086/321845 |
long_lat |
ENVELOPE(43.352,43.352,66.332,66.332) |
geographic |
Levin |
geographic_facet |
Levin |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
http://cid.oxfordjournals.org/cgi/content/short/33/Supplement_3/S174 http://dx.doi.org/10.1086/321845 |
op_rights |
Copyright (C) 2001, Infectious Diseases Society of America |
op_doi |
https://doi.org/10.1086/321845 |
container_title |
Clinical Infectious Diseases |
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33 |
container_issue |
s3 |
container_start_page |
S174 |
op_container_end_page |
S179 |
_version_ |
1766040047581134848 |