@article{6dbeca36df1543b3947eaab83dd35f01,
title = "Improving antimicrobial resistance surveillance in livestock production",
author = "Michelle Baker and Tania Dottorini",
note = "Funding Information: The research question came about during a meeting with Professor Junshi Chen at a workshop jointly organized by the UK Research and Innovation Medical Research Council (UKRI MRC) and the National Natural Science Foundation of China (NSFC) in Shanghai. Our appetite for collaboration and synergistic approaches prompted further meetings between the United Kingdom and China to co-design a new way to target AMR. Despite challenges caused by the COVID-19 pandemic, which impacted data collection on farms, the project — funded by the UKRI–Ministry of Science and Technology of the People{\textquoteright}s Republic of China (MoST) — proved highly successful. We collected and analysed a large set of microbiological, sensing and sequencing data, as well as data on human practices, from ten poultry farms. The step-change in the research came when our approaches for mining big data captured the intricate nature of AMR across ecological contexts, animals, environments, practices and environmental conditions. These findings not only open possibilities for enhancing surveillance and ultimately mitigating the effect of AMR, but also reinforce the relevance of a multi-country, multi-scale and multi-modal approach against AMR. T.D. ",
year = "2023",
month = aug,
doi = "10.1038/s43016-023-00835-5",
language = "English",
volume = "4",
pages = "646--647",
journal = "Nature Food",
issn = "2662-1355",
publisher = "Springer Nature",
number = "8",
}