Lambraki Irene Anna, Chadag Mohan Vishnumurthy, Cousins Melanie, Graells Tiscar, Léger Anaïs, Henriksson Patrik John Gustav, Troell Max Fredrik, Harbarth Stephan, Wernli Didier, Jørgensen Peter Søgaard, Carson Carolee Anne, Parmley Elizabeth Jane, Majowicz Shannon E
School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.
WorldFish, Penang, Malaysia.
Front Microbiol. 2023 Jan 5;13:992507. doi: 10.3389/fmicb.2022.992507. eCollection 2022.
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.
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 participant feedback.
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 ( = 40 quotes)], six "overarching factors" that impact the entire AMR system [e.g., the drive to survive ( = 12 quotes)], and 10 places for intervention that target CLD factors ( = 5) and overarching factors ( = 2) emerged from workshop discussions.
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.
随着抗菌药物使用预计会增加,东南亚因抗菌药物耐药性(AMR)面临健康、社会和经济负担不成比例的高风险。我们的目标是通过整合该地区专家的观点来确定影响东南亚食品系统中抗菌药物耐药性的因素以及干预点,为政策和管理决策提供信息。
我们举办了两次6.5小时的研讨会和两次90分钟的访谈,涉及来自人类、动物和环境领域的18位抗菌药物耐药性及其他学科的专家,他们集思广益探讨了影响抗菌药物耐药性的因素,并确定了干预的杠杆点(位置)。对访谈记录和研讨会材料进行编码,分析因素及其联系,并转化为因果循环图(CLD)。主题分析描述了东南亚食品系统中的抗菌药物耐药性动态以及干预的杠杆点。因果循环图和主题通过参与者反馈得到确认。
参与者构建了东南亚食品系统中抗菌药物耐药性的因果循环图,其中包含98个因素,由362个联系相互关联。因果循环图因素反映了东南亚食品系统的八个子领域(如政府)。研讨会讨论产生了七个主题[如抗菌药物和农药使用与抗菌药物耐药性传播( = 40条引用)]、六个影响整个抗菌药物耐药性系统的“总体因素”[如生存驱动力( = 12条引用)]以及10个针对因果循环图因素( = 5)和总体因素( = 2)的干预点。
参与者得出的影响东南亚食品系统中抗菌药物耐药性的因素因果循环图表明,抗菌药物耐药性是“同一健康”范围内众多相互关联行动的产物,找到解决方案并非易事。开发该模型有助于确定人类、动物和环境领域潜在的有前景的杠杆点,如果使用多管齐下的干预措施全面针对这些杠杆点,可能引发全系统的变化,减轻抗菌药物耐药性。即使针对一些干预杠杆点,如增加研究和能力建设投资,以及制定和执行控制抗菌药物供应、需求和使用的法规,反过来也可能改变思维方式,导致在更难改变的杠杆点上发生变化,如重新定义驱动系统行为的利润驱动意图,从而改变抗菌药物使用并可持续减轻抗菌药物耐药性。