ArticlePLoS computational biology2019
Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Mapping the landscape of mathematical models for antimicrobial resistance: a scoping review.BMC public health · 2026Article
- A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance.PLoS computational biology · 2023Article
- In Vitro Culture ofPharmaceuticals (Basel, Switzerland) · 2021Article
- Nanomaterials as Novel Cardiovascular Theranostics.Pharmaceutics · 2021Review
- Nano-Medicines a Hope for Chagas Disease!Frontiers in molecular biosciences · 2021Review
- Nanotechnological strategies for systemic microbial infections treatment: A review.International journal of pharmaceutics · 2020Review
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.
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Registered trials
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