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Fulltext Unpacking factors influencing antimicrobial use in global aquaculture and their implication for management: a review from a systems perspective

Henriksson PJG, Rico A, Troell M, Klinger DH, Buschmann AH, Saksida S, et al.

Sustain Sci, 2018;13(4):1105-1120.
PMID: 30147798 DOI: 10.1007/s11625-017-0511-8

Global seafood provides almost 20% of all animal protein in diets, and aquaculture is, despite weakening trends, the fastest growing food sector worldwide. Recent increases in production have largely been achieved through intensification of existing farming systems, resulting in higher risks of disease outbreaks. This has led to increased use of antimicrobials (AMs) and consequent antimicrobial resistance (AMR) in many farming sectors, which may compromise the treatment of bacterial infections in the aquaculture species itself and increase the risks of AMR in humans through zoonotic diseases or through the transfer of AMR genes to human bacteria. Multiple stakeholders have, as a result, criticized the aquaculture industry, resulting in consequent regulations in some countries. AM use in aquaculture differs from that in livestock farming due to aquaculture's greater diversity of species and farming systems, alternative means of AM application, and less consolidated farming practices in many regions. This, together with less research on AM use in aquaculture in general, suggests that large data gaps persist with regards to its overall use, breakdowns by species and system, and how AMs become distributed in, and impact on, the overall social-ecological systems in which they are embedded. This paper identifies the main factors (and challenges) behind application rates, which enables discussion of mitigation pathways. From a set of identified key mechanisms for AM usage, six proximate factors are identified: vulnerability to bacterial disease, AM access, disease diagnostic capacity, AMR, target markets and food safety regulations, and certification. Building upon these can enable local governments to reduce AM use through farmer training, spatial planning, assistance with disease identification, and stricter regulations. National governments and international organizations could, in turn, assist with disease-free juveniles and vaccines, enforce rigid monitoring of the quantity and quality of AMs used by farmers and the AM residues in the farmed species and in the environment, and promote measures to reduce potential human health risks associated with AMR.
Fulltext Factors impacting antimicrobial resistance in the South East Asian food system and potential places to intervene: A participatory, one health study

Lambraki IA, Chadag MV, Cousins M, Graells T, Léger A, Henriksson PJG, et al.

Front Microbiol, 2022;13:992507.
PMID: 36687632 DOI: 10.3389/fmicb.2022.992507

BACKGROUND: With AMU projected to increase, South East Asia (SEA) is at high risk of experiencing disproportionate health, social, and economic burdens due to antimicrobial resistance (AMR). Our objective was to identify factors influencing AMR in SEA's food system and places for intervention by integrating the perspectives of experts from the region to inform policy and management decisions.
MATERIALS AND METHODS: We conducted two 6.5 h workshops and two 90-min interviews involving 18 AMR and other disciplinary experts from human, animal, and environment sectors who brainstormed the factors influencing AMR and identified leverage points (places) for intervention. Transcripts and workshop materials were coded for factors and their connections and transcribed into a causal loop diagram (CLD). Thematic analysis described AMR dynamics in SEA's food system and leverage points for intervention. The CLD and themes were confirmed via participant feedback.
RESULTS: Participants constructed a CLD of AMR in the SEA food system that contained 98 factors interlinked by 362 connections. CLD factors reflected eight sub-areas of the SEA food system (e.g., government). Seven themes [e.g., antimicrobial and pesticide use and AMR spread (n = 40 quotes)], six "overarching factors" that impact the entire AMR system [e.g., the drive to survive (n = 12 quotes)], and 10 places for intervention that target CLD factors (n = 5) and overarching factors (n = 2) emerged from workshop discussions.
CONCLUSION: The participant derived CLD of factors influencing AMR in the SEA food system demonstrates that AMR is a product of numerous interlinked actions taken across the One Health spectrum and that finding solutions is no simple task. Developing the model enabled the identification of potentially promising leverage points across human, animal, and environment sectors that, if comprehensively targeted using multi-pronged interventions, could evoke system wide changes that mitigate AMR. Even targeting some leverage points for intervention, such as increasing investments in research and capacity building, and setting and enforcing regulations to control antimicrobial supply, demand, and use could, in turn, shift mindsets that lead to changes in more difficult to alter leverage points, such as redefining the profit-driven intent that drives system behavior in ways that transform AMU and sustainably mitigate AMR.

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