Identification of the elements of models of antimicrobial resistance of bacteria for assessing their usefulness and usability in One Health decision making: a protocol for scoping review

Kamal Raj Acharya; Jhoana P Romero-Leiton; Elizabeth Jane Parmley; Bouchra Nasri

doi:10.1136/bmjopen-2022-069022

Identification of the elements of models of antimicrobial resistance of bacteria for assessing their usefulness and usability in One Health decision making: a protocol for scoping review

BMJ Open. 2023 Mar 16;13(3):e069022. doi: 10.1136/bmjopen-2022-069022.

Authors

Kamal Raj Acharya¹, Jhoana P Romero-Leiton², Elizabeth Jane Parmley³, Bouchra Nasri⁴

Affiliations

¹ Département de médecine sociale et préventive, École de Santé Publique, University of Montreal, Montreal, Quebec, Canada.
² Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada.
³ Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada.
⁴ Département de médecine sociale et préventive, École de Santé Publique, University of Montreal, Montreal, Quebec, Canada bouchra.nasri@umontreal.ca.

Abstract

Introduction: Antimicrobial resistance (AMR) is a complex problem that requires the One Health approach, that is, a collaboration among various disciplines working in different sectors (animal, human and environment) to resolve it. Mathematical and statistical models have been used to understand AMR development, emergence, dissemination, prediction and forecasting. A review of the published models of AMR will help consolidate our knowledge of the dynamics of AMR and will also facilitate decision-makers and researchers in evaluating the credibility, generalisability and interpretation of the results and aspects of AMR models. The study objective is to identify and synthesise knowledge on mathematical and statistical models of AMR among bacteria in animals, humans and environmental compartments.

Methods and analysis: Eligibility criteria: Original research studies reporting mathematical and statistical models of AMR among bacteria in animal, human and environmental compartments that were published until 2022 in English, French and Spanish will be included in this study.

Sources of evidence: Database of PubMed, Agricola (Ovid), Centre for Agriculture and Bioscience Direct (CABI), Web of Science (Clarivate), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and MathScinet. Data charting: Metadata of the study, the context of the study, model structure, model process and reporting quality will be extracted. A narrative summary of this information, gaps and recommendations will be prepared and reported in One Health decision-making context.

Ethics and dissemination: Research ethics board approval was not obtained for this study as neither human participation nor unpublished human data were used in this study. The study findings will be widely disseminated among the One Health Modelling Network for Emerging Infections network and stakeholders by means of conferences, and publication in open-access peer-reviewed journals.

Keywords: MICROBIOLOGY; PUBLIC HEALTH; STATISTICS & RESEARCH METHODS.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Anti-Bacterial Agents* / pharmacology
Anti-Bacterial Agents* / therapeutic use
Bacteria
Decision Making
Drug Resistance, Bacterial
Humans
One Health*
Research Design
Review Literature as Topic

Substances

Anti-Bacterial Agents