ArticlePLoS computational biology2017
Modeling antibiotic treatment in hospitals: A systematic approach shows benefits of combination therapy over cycling, mixing, and mono-drug therapies.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.
- The effect of combining antibiotics on resistance: A systematic review and meta-analysis.eLife · 2024Pooled it
- Modelling the role of the microbiome in antimicrobial resistance across scales.Nature microbiology · 2026Review
- Sequential Phage Delivery Can Outperform Cocktails by Delaying Cross-Resistance Evolution.Viruses · 2026Article
- One Earth-One Health (OE-OH): Antibacterial Effects of Plant Flavonoids in Combination with Clinical Antibiotics with Various Mechanisms.Antibiotics (Basel, Switzerland) · 2024Article
- The impact of treatment strategies on the epidemiological dynamics of plasmid-conferred antibiotic resistance.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Modelling the implementation of narrow versus broader spectrum antibiotics in the empiric treatment of E. coli bacteraemia.Scientific reports · 2024Article
- The effect of combining antibiotics on resistance: A systematic review and meta-analysis.medRxiv : the preprint server for health sciences · 2024Article
- Building pyramids against the evolutionary emergence of pathogens.Proceedings. Biological sciences · 2024Article
- An agent-based model on antimicrobial de-escalation in intensive care units: Implications on clinical trial design.PloS one · 2024Article
- Taxation of veterinary antibiotics to reduce antimicrobial resistance.One health (Amsterdam, Netherlands) · 2023Article
- Resistance-minimising strategies for introducing a novel antibiotic for gonorrhoea treatment: a mathematical modelling study.The Lancet. Microbe · 2023Article
- 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
- Controlling the Mean Time to Extinction in Populations of Bacteria.Entropy (Basel, Switzerland) · 2023Article
- Resistance-minimizing strategies for introducing a novel antibiotic for gonorrhea treatment: a mathematical modeling study.medRxiv : the preprint server for health sciences · 2023Article
- Delaying quantitative resistance to pesticides and antibiotics.Evolutionary applications · 2022Article
- Drug Combinations to Prevent Antimicrobial Resistance: Various Correlations and Laws, and Their Verifications, Thus Proposing Some Principles and a Preliminary Scheme.Antibiotics (Basel, Switzerland) · 2022Article
- A theory of resistance to multiplexed gene drive demonstrates the significant role of weakly deleterious natural genetic variation.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Plasmid co-infection: linking biological mechanisms to ecological and evolutionary dynamics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Review
- Design principles of collateral sensitivity-based dosing strategies.Nature communications · 2021Article
- Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple treatment strategies are available for empiric antibiotic therapy in hospitals, but neither clinical studies nor theoretical investigations have yielded a clear picture when which strategy is optimal and why. Extending earlier work of others and us, we present a mathematical model capturing treatment strategies using two drugs, i.e the multi-drug therapies referred to as cycling, mixing, and combination therapy, as well as monotherapy with either drug. We randomly sample a large parameter space to determine the conditions determining success or failure of these strategies. We find that combination therapy tends to outperform the other treatment strategies. By using linear discriminant analysis and particle swarm optimization, we find that the most important parameters determining success or failure of combination therapy relative to the other treatment strategies are the de novo rate of emergence of double resistance in patients infected with sensitive bacteria and the fitness costs associated with double resistance. The rate at which double resistance is imported into the hospital via patients admitted from the outside community has little influence, as all treatment strategies are affected equally. The parameter sets for which combination therapy fails tend to fall into areas with low biological plausibility as they are characterised by very high rates of de novo emergence of resistance to both drugs compared to a single drug, and the cost of double resistance is considerably smaller than the sum of the costs of single resistance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.