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dc.contributor.authorMartinecz, Antal
dc.contributor.authorAbel zur Wiesch, Pia
dc.date.accessioned2019-02-06T11:47:42Z
dc.date.available2019-02-06T11:47:42Z
dc.date.issued2018-08-09
dc.description.abstractTreatment of infectious diseases is often long and requires patients to take drugs even after they have seemingly recovered. This is because of a phenomenon called persistence, which allows small fractions of the bacterial population to survive treatment despite being genetically susceptible. The surviving subpopulation is often below detection limit and therefore is empirically inaccessible but can cause treatment failure when treatment is terminated prematurely. Mathematical models could aid in predicting bacterial survival and thereby determine sufficient treatment length. However, the mechanisms of persistence are hotly debated, necessitating the development of multiple mechanistic models. Here we develop a generalized mathematical framework that can accommodate various persistence mechanisms from measurable heterogeneities in pathogen populations. It allows the estimation of the relative increase in treatment length necessary to eradicate persisters compared to the majority population. To simplify and generalize, we separate the model into two parts: the distribution of the molecular mechanism of persistence in the bacterial population (e.g. number of efflux pumps or target molecules, growth rates) and the elimination rate of single bacteria as a function of that phenotype. Thereby, we obtain an estimate of the required treatment length for each phenotypic subpopulation depending on its size and susceptibility.en_US
dc.description.sponsorshipUiT The Arctic University of Norwayen_US
dc.identifier.citationMartinecz, A. & Abel zur Wiesch, P. (2018). Estimating treatment prolongation for persistent infections. <i>Pathogens and Disease, 76</i>(6). https://doi.org/10.1093/femspd/fty065en_US
dc.identifier.cristinIDFRIDAID 1608107
dc.identifier.doihttps://doi.org/10.1093/femspd/fty065
dc.identifier.issn2049-632X
dc.identifier.urihttps://hdl.handle.net/10037/14629
dc.language.isoengen_US
dc.publisherOxford University Press (OUP)en_US
dc.relation.ispartofMartinecz, A. (2020). Mathematical Models of Optimal Antibiotic Treatment. (Doctoral thesis). <a href=https://hdl.handle.net/10037/18291>https://hdl.handle.net/10037/18291</a>
dc.relation.journalPathogens and Disease
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/JPIAMR/271176/Norway/Using collateral sensitivity to reverse the selection and transmission of antibiotic resistance//en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710::Pharmacology: 728en_US
dc.subjectVDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Farmakologi: 728en_US
dc.subjectpersistenceen_US
dc.subjectantimicrobialen_US
dc.subjecttreatment lengthen_US
dc.subjectmathematical modelen_US
dc.subjectbacteriaen_US
dc.subjectantibioticen_US
dc.titleEstimating treatment prolongation for persistent infectionsen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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