title: Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases.
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.
authors.affiliation: Department of Mathematics, University College London, London, United Kingdom; MTA-SZTE Analysis and Stochastic Research Group, University of Szeged, Szeged, Hungary.
authors.forename: Diána
authors.initials: D
authors.lastname: Knipl
authors.affiliation: Bolyai Institute, University of Szeged , Szeged , Hungary.
authors.forename: Gergely
authors.initials: G
authors.lastname: Röst
authors.affiliation: Agent-Based Modelling Laboratory, York University , Toronto , Canada.
authors.forename: Seyed M
authors.initials: SM
authors.lastname: Moghadas
keywords: Delay treatment; Drug-resistance; Epidemic and endemic states; Reproduction numbers