AI Article Synopsis

  • * Mathematical models can help understand and predict how antibiotic resistance spreads and how policies can effectively address it.
  • * Despite advances, our knowledge of antibiotic resistance is still incomplete, highlighting the need for further research to inform better policy decisions.

Article Abstract

Background: Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base.

Main Text: One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy.

Conclusions: We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884858PMC
http://dx.doi.org/10.1186/s12879-019-4630-yDOI Listing

Publication Analysis

Top Keywords

antibiotic resistance
16
mathematical modelling
12
resistance mathematical
8
mathematical models
8
resistance
6
mathematical
5
antibiotic
5
modelling antibiotic
4
resistance control
4
control policy
4

Similar Publications

An effective drug-free hydrogel for accelerating the whole healing process of bacteria-infected wounds.

Biomater Sci

December 2024

Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, 300070, China.

Wound healing is a dynamic and complex process involving hemostasis, inflammation, fibroblast proliferation, and tissue remodeling. This process is highly susceptible to bacterial infection, which often leads to impaired and delayed wound repair. While antibiotic therapy remains the primary clinical approach for treating bacteria-infected wounds, its widespread use poses a significant risk of developing bacterial resistance.

View Article and Find Full Text PDF

Antifungal Properties of Polycephalomyces nipponicus (Ascomycetes) against Candida albicans: Potential for Novel Therapeutic Development.

Int J Med Mushrooms

December 2024

Department of Biology, Faculty of Science, Mahasarakham University, Kantarawichai District, Maha Sarakham, Thailand; Microbiology and Applied Microbiology Research Unit, Faculty of Science, Mahasarakham University, Kantarawichai District, Maha Sarakham, Thailand.

Candida albicans has the potential to turn pathogenic and cause mild to severe infections, particularly in people with weakened immune systems. Novel therapeutics are required due to its morphological alterations, biofilm development, and resistance to antifungal drugs. Polycephalomyces nipponicus, a traditional East Asian medicinal fungus, has shown potential as an antifungal agent.

View Article and Find Full Text PDF

The Bacterial Biofilms: Formation, Impacts, and Possible Management Targets in the Healthcare System.

Can J Infect Dis Med Microbiol

December 2024

Department of Applied Health Sciences, School of Health Sciences, Kisii University, Kisii, Kenya.

The persistent increase in multidrug-resistant pathogens has catalyzed the creation of novel strategies to address antivirulence and anti-infective elements. Such methodologies aim to diminish the selective pressure exerted on bacterial populations, decreasing the likelihood of resistance emergence. This review explores the role of biofilm formation as a significant virulence factor and its impact on the development of antimicrobial resistance (AMR).

View Article and Find Full Text PDF

Introduction: Antimicrobial resistance (AMR) is a global health crisis that is predicted to worsen in the coming years. While improper antibiotic usage is an established driver, less is known about the impact of other endogenous and exogeneous environmental factors, such as metals, on AMR. One metal of interest is zinc as it is often used as a supplement for diarrhea treatment prior to antibiotics.

View Article and Find Full Text PDF

Neonatal calf diarrhea (NCD) remains a significant contributor to calf mortality within the first 3 weeks of life, prompting widespread antibiotic use with associated concerns about antimicrobial resistance and disruption of the calf gut microbiota. Recent research exploring NCD treatments targeting gut microbiota dysbiosis has highlighted probiotic supplementation as a promising and safe strategy for gut homeostasis. However, varying treatment outcomes across studies suggest the need for efficient treatment options.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!

A PHP Error was encountered

Severity: Notice

Message: fwrite(): Write of 34 bytes failed with errno=28 No space left on device

Filename: drivers/Session_files_driver.php

Line Number: 272

Backtrace:

A PHP Error was encountered

Severity: Warning

Message: session_write_close(): Failed to write session data using user defined save handler. (session.save_path: /var/lib/php/sessions)

Filename: Unknown

Line Number: 0

Backtrace: