One Health drivers of antibacterial resistance: Quantifying the relative impacts of human, animal and environmental use and transmission.
One Health drivers of antibacterial resistance: Quantifying the relative impacts of human, animal and environmental use and transmission.
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DOI：
10.1016/j.onehlt.2021.100220
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发表时间：
2021-06
期刊：
影响因子：
--
通讯作者：
Turner KME
中科院分区：
文献类型：
--
作者：
Booton RD;Meeyai A;Alhusein N;Buller H;Feil E;Lambert H;Mongkolsuk S;Pitchforth E;Reyher KK;Sakcamduang W;Satayavivad J;Singer AC;Sringernyuang L;Thamlikitkul V;Vass L;OH-DART Study Group;Avison MB;Turner KME
抗生素耐药性（ABR）是一个重大的全球卫生安全威胁，对中低收入国家（LMIC）造成了不成比例的负担。目前尚不清楚“一个健康”（人类健康共同依赖于动物健康和环境）如何影响中低收入国家的ABR负担。泰国2017年的“抗菌素耐药性国家战略计划”（NSP-AMR）旨在通过减少20%的人类和30%的动物抗菌素使用（ABU），将AMR发病率降低50%。有必要从“一个健康”的角度理解这一计划的影响。使用泰国产超广谱β-内酰胺酶（ESBL）细菌的流行率估计值校准ABU、产超广谱β-内酰胺酶（ESBL）细菌的肠道定植和传播模型。该模型用于预测20年（2020-2040年）内每个One Health驱动因素的人类ABR降低情况，包括人类，动物和环境之间的个体传播率，并估计NSP-AMR干预措施的长期影响。该模型预测，人类ABU是减少人类耐药细菌定植的最重要因素（最大减少65.7-99.7%）。NSP-AMR预计将人类定植减少6.0- 18.8%，更雄心勃勃的目标（人类ABU减少30%）将其增加到8.5- 24.9%。我们的模型提供了一个简单的框架来解释ABR的基础机制，这表明未来的干预措施，同时减少传输和ABU将有助于更有效地控制ABR在泰国。本文提出了一种新的人、动物和环境ABR传播和ABU的数学模型。人类ABU被确定为人类ABR的主要驱动因素。人类体内的耐药性主要是由人类活动驱动的，而不是动物或环境使用或传播。考虑到人类、动物和环境传播和使用的卫生干预措施可以产生最大的影响。
Antibacterial resistance (ABR) is a major global health security threat, with a disproportionate burden on lower-and middle-income countries (LMICs). It is not understood how ‘One Health’, where human health is co-dependent on animal health and the environment, might impact the burden of ABR in LMICs. Thailand's 2017 “National Strategic Plan on Antimicrobial Resistance” (NSP-AMR) aims to reduce AMR morbidity by 50% through 20% reductions in human and 30% in animal antibacterial use (ABU). There is a need to understand the implications of such a plan within a One Health perspective. A model of ABU, gut colonisation with extended-spectrum beta-lactamase (ESBL)-producing bacteria and transmission was calibrated using estimates of the prevalence of ESBL-producing bacteria in Thailand. This model was used to project the reduction in human ABR over 20 years (2020–2040) for each One Health driver, including individual transmission rates between humans, animals and the environment, and to estimate the long-term impact of the NSP-AMR intervention. The model predicts that human ABU was the most important factor in reducing the colonisation of humans with resistant bacteria (maximum 65.7–99.7% reduction). The NSP-AMR is projected to reduce human colonisation by 6.0–18.8%, with more ambitious targets (30% reductions in human ABU) increasing this to 8.5–24.9%. Our model provides a simple framework to explain the mechanisms underpinning ABR, suggesting that future interventions targeting the simultaneous reduction of transmission and ABU would help to control ABR more effectively in Thailand. We present a novel mathematical model of human, animal and environment ABR transmission and ABU. Human ABU was identified as the main driver of human ABR. Resistance within humans was primarily driven by human activity rather than animal or environmental usage or transmission. One Health interventions which consider human, animal and environmental transmission and usage can yield the highest impact.
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