Global surveillance of antimicrobial resistance in food animals using priority drugs maps

被引:16
|
作者
Zhao, Cheng [1 ]
Wang, Yu [1 ]
Mulchandani, Ranya [1 ]
Van Boeckel, Thomas P. [1 ,2 ,3 ]
机构
[1] Swiss Fed Inst Technol, Hlth Geog & Policy Grp, Zurich, Switzerland
[2] One Hlth Trust, Washington, DC 20036 USA
[3] Univ Libre Bruxelles, Spatial Epidemiol Lab, Brussels, Belgium
基金
瑞士国家科学基金会;
关键词
CHLORAMPHENICOL; ANTIBIOTICS; THERAPY;
D O I
10.1038/s41467-024-45111-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Antimicrobial resistance (AMR) in food animals is a growing threat to animal health and potentially to human health. In resource-limited settings, allocating resources to address AMR can be guided with maps. Here, we mapped AMR prevalence in 7 antimicrobials in Escherichia coli and nontyphoidal Salmonella species across low- and middle-income countries (LIMCs), using 1088 point-prevalence surveys in combination with a geospatial model. Hotspots of AMR were predicted in China, India, Brazil, Chile, and part of central Asia and southeastern Africa. The highest resistance prevalence was for tetracycline (59% for E. coli and 54% for nontyphoidal Salmonella, average across LMICs) and lowest for cefotaxime (33% and 19%). We also identified the antimicrobial with the highest probability of resistance exceeding critical levels (50%) in the future (1.7-12.4 years) for each 10 x 10 km pixel on the map. In Africa and South America, 78% locations were associated with penicillins or tetracyclines crossing 50% resistance in the future. In contrast, in Asia, 77% locations were associated with penicillins or sulphonamides. Our maps highlight diverging geographic trends of AMR prevalence across antimicrobial classes, and can be used to target AMR surveillance in AMR hotspots for priority antimicrobial classes. Monitoring antimicrobial resistance in food animals is challenging due to limited surveillance systems. Here, the authors combine data from point prevalence surveys in lower- and middle-income settings to map resistance to seven antimicrobials and predict which are likely to exceed key resistance thresholds.
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页数:10
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