Building Social-Ecological System Resilience to Tackle Antimicrobial Resistance Across the One Health Spectrum: Protocol for a Mixed Methods Study.

One Health antimicrobial resistance interventions participatory resilience social-ecological system systems dynamics transdisciplinary

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
10 Jun 2021
Historique:
received: 16 09 2020
accepted: 17 03 2021
revised: 26 02 2021
entrez: 10 6 2021
pubmed: 11 6 2021
medline: 11 6 2021
Statut: epublish

Résumé

Antimicrobial resistance (AMR) is an escalating global crisis with serious health, social, and economic consequences. Building social-ecological system resilience to reduce AMR and mitigate its impacts is critical. The aim of this study is to compare and assess interventions that address AMR across the One Health spectrum and determine what actions will help to build social and ecological capacity and readiness to sustainably tackle AMR. We will apply social-ecological resilience theory to AMR in an explicit One Health context using mixed methods and identify interventions that address AMR and its key pressure antimicrobial use (AMU) identified in the scientific literature and in the gray literature using a web-based survey. Intervention impacts and the factors that challenge or contribute to the success of interventions will be determined, triangulated against expert opinions in participatory workshops and complemented using quantitative time series analyses. We will then identify indicators using regression modeling, which can predict national and regional AMU or AMR dynamics across animal and human health. Together, these analyses will help to quantify the causal loop diagrams (CLDs) of AMR in the European and Southeast Asian food system contexts that are developed by diverse stakeholders in participatory workshops. Then, using these CLDs, the long-term impacts of selected interventions on AMR will be explored under alternate future scenarios via simulation modeling and participatory workshops. A publicly available learning platform housing information about interventions on AMR from a One Health perspective will be developed to help decision makers identify promising interventions for application in their jurisdictions. To date, 669 interventions have been identified in the scientific literature, 891 participants received a survey invitation, and 4 expert feedback and 4 model-building workshops have been conducted. Time series analysis, regression modeling of national and regional indicators of AMR dynamics, and scenario modeling activities are anticipated to be completed by spring 2022. Ethical approval has been obtained from the University of Waterloo's Office of Research Ethics (ethics numbers 40519 and 41781). This paper provides an example of how to study complex problems such as AMR, which require the integration of knowledge across sectors and disciplines to find sustainable solutions. We anticipate that our study will contribute to a better understanding of what actions to take and in what contexts to ensure long-term success in mitigating AMR and its impact and provide useful tools (eg, CLDs, simulation models, and public databases of compiled interventions) to guide management and policy decisions. DERR1-10.2196/24378.

Sections du résumé

BACKGROUND BACKGROUND
Antimicrobial resistance (AMR) is an escalating global crisis with serious health, social, and economic consequences. Building social-ecological system resilience to reduce AMR and mitigate its impacts is critical.
OBJECTIVE OBJECTIVE
The aim of this study is to compare and assess interventions that address AMR across the One Health spectrum and determine what actions will help to build social and ecological capacity and readiness to sustainably tackle AMR.
METHODS METHODS
We will apply social-ecological resilience theory to AMR in an explicit One Health context using mixed methods and identify interventions that address AMR and its key pressure antimicrobial use (AMU) identified in the scientific literature and in the gray literature using a web-based survey. Intervention impacts and the factors that challenge or contribute to the success of interventions will be determined, triangulated against expert opinions in participatory workshops and complemented using quantitative time series analyses. We will then identify indicators using regression modeling, which can predict national and regional AMU or AMR dynamics across animal and human health. Together, these analyses will help to quantify the causal loop diagrams (CLDs) of AMR in the European and Southeast Asian food system contexts that are developed by diverse stakeholders in participatory workshops. Then, using these CLDs, the long-term impacts of selected interventions on AMR will be explored under alternate future scenarios via simulation modeling and participatory workshops. A publicly available learning platform housing information about interventions on AMR from a One Health perspective will be developed to help decision makers identify promising interventions for application in their jurisdictions.
RESULTS RESULTS
To date, 669 interventions have been identified in the scientific literature, 891 participants received a survey invitation, and 4 expert feedback and 4 model-building workshops have been conducted. Time series analysis, regression modeling of national and regional indicators of AMR dynamics, and scenario modeling activities are anticipated to be completed by spring 2022. Ethical approval has been obtained from the University of Waterloo's Office of Research Ethics (ethics numbers 40519 and 41781).
CONCLUSIONS CONCLUSIONS
This paper provides an example of how to study complex problems such as AMR, which require the integration of knowledge across sectors and disciplines to find sustainable solutions. We anticipate that our study will contribute to a better understanding of what actions to take and in what contexts to ensure long-term success in mitigating AMR and its impact and provide useful tools (eg, CLDs, simulation models, and public databases of compiled interventions) to guide management and policy decisions.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
DERR1-10.2196/24378.

Identifiants

pubmed: 34110296
pii: v10i6e24378
doi: 10.2196/24378
pmc: PMC8262547
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e24378

Informations de copyright

©Irene Anna Lambraki, Shannon Elizabeth Majowicz, Elizabeth Jane Parmley, Didier Wernli, Anaïs Léger, Tiscar Graells, Melanie Cousins, Stephan Harbarth, Carolee Carson, Patrik Henriksson, Max Troell, Peter Søgaard Jørgensen. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 10.06.2021.

Références

Antimicrob Resist Infect Control. 2012 Feb 13;1(1):9
pubmed: 22958336
Health Res Policy Syst. 2018 Dec 29;16(1):126
pubmed: 30594203
J Hosp Infect. 2009 Dec;73(4):305-15
pubmed: 19720430
Epidemiol Infect. 2019 Nov 04;147:e296
pubmed: 31679543
Infect Dis Poverty. 2018 Aug 17;7(1):76
pubmed: 30115132
Sci Rep. 2020 Dec 14;10(1):21878
pubmed: 33318576
Trans R Soc Trop Med Hyg. 2016 Jul;110(7):377-80
pubmed: 27475987
Trends Ecol Evol. 2020 Jun;35(6):484-494
pubmed: 32396815
Zoonoses Public Health. 2017 Feb;64(1):63-74
pubmed: 27362766
PLoS Med. 2017 Aug 17;14(8):e1002378
pubmed: 28817562
Emerg Infect Dis. 2005 Jun;11(6):794-801
pubmed: 15963271
BMJ Glob Health. 2019 Aug 31;4(4):e001710
pubmed: 31543995
Nature. 2016 Sep 07;537(7619):159-61
pubmed: 27604934
Emerg Themes Epidemiol. 2011 Jan 20;8(1):2
pubmed: 21247500
Epidemiology. 1999 Jan;10(1):37-48
pubmed: 9888278
J Antimicrob Chemother. 2021 Jan 1;76(1):1-21
pubmed: 33057678
J Med Internet Res. 2004 Sep 29;6(3):e34
pubmed: 15471760
Lancet Infect Dis. 2015 Dec;15(12):1438-49
pubmed: 26411518
J Med Internet Res. 2018 May 28;20(5):e10059
pubmed: 29807882
J Law Med Ethics. 2015 Summer;43 Suppl 3:12-6
pubmed: 26243237
J Travel Med. 2019 Dec 23;26(8):
pubmed: 31115466
Sustain Sci. 2018;13(4):1105-1120
pubmed: 30147798
BMJ. 2004 Jun 19;328(7454):1490
pubmed: 15205295
Lancet Infect Dis. 2020 Dec;20(12):e307-e311
pubmed: 32853549
Antimicrob Resist Infect Control. 2020 Nov 7;9(1):181
pubmed: 33160396
Lancet Planet Health. 2018 Sep;2(9):e398-e405
pubmed: 30177008
J Antimicrob Chemother. 2003 Aug;52(2):159-61
pubmed: 12837737
Lancet Infect Dis. 2019 Jan;19(1):56-66
pubmed: 30409683
Antibiotics (Basel). 2020 Dec 17;9(12):
pubmed: 33348801
Proc Natl Acad Sci U S A. 2015 May 5;112(18):5649-54
pubmed: 25792457
BMC Res Notes. 2018 Mar 12;11(1):170
pubmed: 29530079
Lancet Planet Health. 2018 Jul;2(7):e279-e282
pubmed: 30074886
Lancet Infect Dis. 2008 Dec;8(12):785-95
pubmed: 19022193
Antibiotics (Basel). 2020 Jul 01;9(7):
pubmed: 32630353

Auteurs

Irene Anna Lambraki (IA)

School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada.

Shannon Elizabeth Majowicz (SE)

School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada.

Elizabeth Jane Parmley (EJ)

Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.

Didier Wernli (D)

Global Studies Institute, University of Geneva, Geneva, Switzerland.

Anaïs Léger (A)

Global Studies Institute, University of Geneva, Geneva, Switzerland.

Tiscar Graells (T)

Global Economic Dynamics and the Biosphere, Royal Swedish Academy of Sciences, Stockholm, Sweden.
Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.

Melanie Cousins (M)

School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada.

Stephan Harbarth (S)

Infection Control Programme and WHO Collaborating Centre on Patient Safety, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.

Carolee Carson (C)

Canadian Integrated Program for Antimicrobial Resistance Surveillance, Public Health Agency of Canada, Guelph, ON, Canada.

Patrik Henriksson (P)

Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Stockholm, Sweden.
WorldFish, Penang, Malaysia.

Max Troell (M)

Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
Beijer Institute of Ecological Economics, Royal Swedish Academy of Sciences, Stockholm, Sweden.

Peter Søgaard Jørgensen (PS)

Global Economic Dynamics and the Biosphere, Royal Swedish Academy of Sciences, Stockholm, Sweden.
Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.

Classifications MeSH