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Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases

Knipl, D; Rost, G; Moghadas, SM; (2017) Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases. PeerJ , 5 , Article e2817. 10.7717/peerj.2817. Green open access

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Abstract

The emergence and spread of drug-resistance during treatment of many infectious diseases continue to degrade our ability to control and mitigate infection outcomes using therapeutic measures. While the coverage and efficacy of treatment remain key factors in the population dynamics of resistance, the timing for the start of the treatment in infectious individuals can significantly influence such dynamics. We developed a between-host disease transmission model to investigate the short-term (epidemic) and long-term (endemic) states of infections caused by two competing pathogen subtypes, namely the wild-type and resistant-type, when the probability of developing resistance is a function of delay in start of the treatment. We characterize the behaviour of disease equilibria and obtain a condition to minimize the fraction of population infectious at the endemic state in terms of probability of developing resistance and its transmission fitness. For the short-term epidemic dynamics, we illustrate that depending on the likelihood of resistance development at the time of treatment initiation, the same epidemic size may be achieved with different delays in start of the treatment, which may correspond to significantly different treatment coverages. Our results demonstrate that early initiation of treatment may not necessarily be the optimal strategy for curtailing the incidence of resistance or the overall disease burden. The risk of developing drug-resistance in-host remains an important factor in the management of resistance in the population.

Type: Article
Title: Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases
Open access status: An open access version is available from UCL Discovery
DOI: 10.7717/peerj.2817
Publisher version: https://doi.org/10.7717/peerj.2817
Language: English
Additional information: © 2017 Knipl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
Keywords: Drug-resistance, Delay treatment, Epidemic and endemic states, Reproduction numbers
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1536154
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