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What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature

Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to u...

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Autores principales: Arepeva, Maria, Kolbin, Alexey, Kurylev, Alexey, Balykina, Julia, Sidorenko, Sergey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4413671/
https://www.ncbi.nlm.nih.gov/pubmed/25972847
http://dx.doi.org/10.3389/fmicb.2015.00352
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author Arepeva, Maria
Kolbin, Alexey
Kurylev, Alexey
Balykina, Julia
Sidorenko, Sergey
author_facet Arepeva, Maria
Kolbin, Alexey
Kurylev, Alexey
Balykina, Julia
Sidorenko, Sergey
author_sort Arepeva, Maria
collection PubMed
description Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to understand the pros and cons of currently used approaches and to build our own model. During the analysis, seven articles on mathematical approaches to studying resistance that satisfied the inclusion/exclusion criteria were selected. All models were classified according to the approach used to study resistance in the presence of an antibiotic and were analyzed in terms of our research. Some models require modifications due to the specifics of the research. The plan for further work on model building is as follows: modify some models, according to our research, check all obtained models against our data, and select the optimal model or models with the best quality of prediction. After that we would be able to build a model for the development of resistance using the obtained results.
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spelling pubmed-44136712015-05-13 What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature Arepeva, Maria Kolbin, Alexey Kurylev, Alexey Balykina, Julia Sidorenko, Sergey Front Microbiol Microbiology Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to understand the pros and cons of currently used approaches and to build our own model. During the analysis, seven articles on mathematical approaches to studying resistance that satisfied the inclusion/exclusion criteria were selected. All models were classified according to the approach used to study resistance in the presence of an antibiotic and were analyzed in terms of our research. Some models require modifications due to the specifics of the research. The plan for further work on model building is as follows: modify some models, according to our research, check all obtained models against our data, and select the optimal model or models with the best quality of prediction. After that we would be able to build a model for the development of resistance using the obtained results. Frontiers Media S.A. 2015-04-29 /pmc/articles/PMC4413671/ /pubmed/25972847 http://dx.doi.org/10.3389/fmicb.2015.00352 Text en Copyright © 2015 Arepeva, Kolbin, Kurylev, Balykina and Sidorenko. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Arepeva, Maria
Kolbin, Alexey
Kurylev, Alexey
Balykina, Julia
Sidorenko, Sergey
What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title_full What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title_fullStr What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title_full_unstemmed What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title_short What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature
title_sort what should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? recommendations based on a systematic review of the literature
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4413671/
https://www.ncbi.nlm.nih.gov/pubmed/25972847
http://dx.doi.org/10.3389/fmicb.2015.00352
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