Active one health surveillance in LMICs to monitor and predict Antimicrobial Resistance Using Metagenomics (ALARUM)

在中低收入国家中开展主动单一健康监测，利用宏基因组学 (ALARUM) 监测和预测抗菌药物耐药性

• 批准号: MR/Y034287/1
• 负责人: Nicole Stoesser
• 金额: $ 46.66万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FY034287%2F1
• 关键词: Active; health; surveillance; LMICs; monitor

Infections caused by bacteria that are resistant to antibiotics are estimated to be associated with 5 million human deaths each year, with the highest death rates attributable to antibiotic resistance in sub-Saharan Africa. Conventionally, microbiology laboratories are used to identify bacteria causing human infections, monitor the spread of antibiotic resistance in these bacteria, and collect data to inform decisions about how to best use antibiotics. However, such laboratories are in short supply in much of sub-Saharan Africa and are expensive to build and run. Alternative lower-cost approaches to classical microbiological surveillance are needed. Many of the bacteria causing life-threatening infections are carried by patients in the gut prior to causing infections. In previous work, we have shown that for certain species of bacteria, by looking at the DNA from bacteria in pooled stool samples from hospital patients, we can accurately predict drug-resistance in serious infections. Working in Kenya and Burkina Faso, we plan to extend this work to other bacterial species, and also to determine whether samples from human stool in the community and household environment can help predict drug-resistance in serious infections. This work will also enable us to find out more about how the bacterial genes that cause drug-resistance are spreading between humans, animals and the environment in the community. Our proposed work includes an economic evaluation to determine under what circumstances the proposed surveillance system represents an efficient use of resources.

据估计，每年有500万人死于对抗生素具有耐药性的细菌引起的感染，其中撒哈拉以南非洲的抗生素耐药性导致的死亡率最高。传统上，微生物实验室用于鉴定引起人类感染的细菌，监测这些细菌中抗生素耐药性的传播，并收集数据以告知如何最好地使用抗生素的决定。然而，在撒哈拉以南非洲的大部分地区，这种实验室供不应求，而且建造和运营费用昂贵。需要替代传统微生物监测的低成本方法。许多导致危及生命的感染的细菌在引起感染之前就被患者携带在肠道中。在以前的工作中，我们已经证明，对于某些细菌物种，通过观察医院患者合并粪便样本中细菌的DNA，我们可以准确预测严重感染的耐药性。在肯尼亚和布基纳法索，我们计划将这项工作扩展到其他细菌物种，并确定社区和家庭环境中的人类粪便样本是否有助于预测严重感染的耐药性。这项工作还将使我们能够更多地了解导致耐药性的细菌基因是如何在人类、动物和社区环境之间传播的。我们提议的工作包括经济评估，以确定在什么情况下提议的监控系统代表了资源的有效利用。