SynthesisAntimicrobial resistance and infection control2018
Send more data: a systematic review of mathematical models of antimicrobial resistance.
Synthesis in Antimicrobial resistance and infection control, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Antibacterial and Antioxidant Effects of Grape Seed Varieties in Iran: A Systematic Review.Veterinary medicine and science · 2026Pooled it
- One health perspective of antibiotic resistance in enterobacterales from Southeast Asia: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- The neglected model validation of antimicrobial resistance transmission models - a systematic review.Antimicrobial resistance and infection control · 2025Pooled it
- Infectious Disease Modelling of HIV Prevention Interventions: A Systematic Review and Narrative Synthesis of Compartmental Models.PharmacoEconomics · 2023Pooled it
- Population-level mathematical modeling of antimicrobial resistance: a systematic review.BMC medicine · 2019Pooled it
- Modelling the role of the microbiome in antimicrobial resistance across scales.Nature microbiology · 2026Review
- Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- A systematic review of data sources used for socioeconomic impact assessment of antimicrobial resistance from a One Health perspective: a lack of representative data.Cost effectiveness and resource allocation : C/E · 2026Review
- Optimal Multi-Drug Therapies for Antimicrobial Resistance with Horizontal Transfer.Journal of optimization theory and applications · 2026Article
- One Health antimicrobial resistance modelling: from science to policy.Science in One Health · 2026Review
- Invariant set theory for predicting potential failure of antibiotic cycling.Infectious Disease Modelling · 2025Article
- Estimated undertreatment of carbapenem-resistant Gram-negative bacterial infections in eight low-income and middle-income countries: a modelling study.The Lancet. Infectious diseases · 2025Article
- Cost-effectiveness of screening, decolonisation and isolation strategies for carbapenem-resistant Enterobacterales and methicillin-resistantLancet regional health. Americas · 2025Article
- Poor hypotheses and research waste in biology: learning from a theory crisis in psychology.BMC biology · 2025Review
- Characterization of antibiotic resistance development ofbioRxiv : the preprint server for biology · 2024Article
- Contagious acquisition of antimicrobial resistance is critical for explaining emergence in western Canadian feedlots-insights from an agent-based modelling tool.Frontiers in veterinary science · 2024Article
- Modelling antimicrobial resistance transmission to guide personalized antimicrobial stewardship interventions and infection control policies in healthcare setting: a pilot study.Scientific reports · 2023Review
- Article
- Antifungal alternation can be beneficial for durability but at the cost of generalist resistance.Communications biology · 2023Article
- Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research.PloS one · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed. Objective: The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models. Methods: The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines. Results: None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation. Conclusion: Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models.
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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.