全球微生物水质数据和预测分析:健康和实现可持续发展目标6的关键

J. Rose, N. Hofstra, Erica Hollmann, P. Katsivelis, G. Medema, H. Murphy, C. Naughton, M. Verbyla
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引用次数: 0

摘要

微生物水质是水安全的组成部分,与人类健康、食品安全和生态系统服务直接相关。然而,具体而言,病原体数据甚至粪便指标数据(如大肠杆菌)都是稀疏和分散的,而且它们在不同水体(如地下水)和不同社会经济背景(如低收入和中等收入国家)中的可得性是不公平的。随着到2030年实现可持续发展目标(SDG) 6的时间越来越短,迫切需要评估和整理世界各地的微生物数据,以评估全球环境水质、水处理和健康风险状况。本文的总体目标是说明并倡导在全球范围内建立一个强大而有用的微生物水质数据库和联盟,以帮助实现可持续发展目标6。我们总结了微生物水质的可用数据和现有数据库,讨论了产生微生物水质新数据的方法,并确定了利用微生物数据支持决策的模型和分析工具。本综述确定了全球数据集(7个数据库),以及非洲(3个数据库)、澳大利亚/新西兰(6个数据库)、亚洲(3个数据库)、欧洲(7个数据库)、北美(12个数据库)和南美(1个数据库)的区域数据集。低收入和中等收入国家的数据缺失。实验室能力的增强(由于COVID-19大流行)和分子工具可以识别潜在的污染源并直接监测病原体。模型和分析工具可以通过在缺乏数据的地方进行地理空间和时间推断来支持微生物水质评估。基因组学、信息技术(IT)和数据革命正在向我们袭来,为开发实时记录、自动化分析、标准化和微生物数据建模的软件和设备提供了前所未有的机会,以加强对全球水质的了解。应利用这些机会在世界各地实现可持续发展目标6。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global microbial water quality data and predictive analytics: Key to health and meeting SDG 6
Microbial water quality is an integral to water security and is directly linked to human health, food safety, and ecosystem services. However, specifically pathogen data and even faecal indicator data (e.g., E. coli), are sparse and scattered, and their availability in different water bodies (e.g., groundwater) and in different socio-economic contexts (e.g., low- and middle-income countries) are inequitable. There is an urgent need to assess and collate microbial data across the world to evaluate the global state of ambient water quality, water treatment, and health risk, as time is running out to meet Sustainable Development Goal (SDG) 6 by 2030. The overall goal of this paper is to illustrate the need and advocate for building a robust and useful microbial water quality database and consortium worldwide that will help achieve SDG 6. We summarize available data and existing databases on microbial water quality, discuss methods for producing new data on microbial water quality, and identify models and analytical tools that utilize microbial data to support decision making. This review identified global datasets (7 databases), and regional datasets for Africa (3 databases), Australia/New Zealand (6 databases), Asia (3 databases), Europe (7 databases), North America (12 databases) and South America (1 database). Data are missing for low- and middle-income countries. Increased laboratory capacity (due to COVID-19 pandemic) and molecular tools can identify potential pollution sources and monitor directly for pathogens. Models and analytical tools can support microbial water quality assessment by making geospatial and temporal inferences where data are lacking. A genomics, information technology (IT), and data revolution is upon us and presents unprecedented opportunities to develop software and devices for real-time logging, automated analysis, standardization, and modelling of microbial data to strengthen knowledge of global water quality. These opportunities should be leveraged for achieving SDG 6 around the world.
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