Geographically Targeted Surveillance of Livestock Could Help Prioritize Intervention Against Antimicrobial Resistance in China

Overview

Journal Nat Food

Specialties Environmental Health
Nutritional Sciences

Date 2023 Apr 28

PMID 37118162

Authors

Cheng Zhao

Yu Wang

Katie Tiseo

Joao Pires

Nicola G Criscuolo

Thomas P Van Boeckel

Affiliations

Soon will be listed here.

Abstract

The rise of antimicrobial resistance (AMR) in animals is being fuelled by the widespread use of veterinary antimicrobials. China is the largest global consumer of veterinary antimicrobials, and improving AMR surveillance strategies in this region could help prioritize intervention and preserve antimicrobial efficacy. Here we mapped AMR rates in pigs, chickens and cattle in China using 446 surveys of event-based surveillance between 2000 and 2019 for foodborne bacteria, in combination with geospatial models to identify locations where conducting new surveys could have the highest benefits. Using maps of uncertainty, we show that eastern China currently has the highest AMR rates, and southwestern and northeastern China would benefit the most from additional surveillance efforts. Instead of distributing new surveys evenly across administrative divisions, using geographically targeted surveillance could reduce AMR prediction uncertainty by two-fold. In a context of competing disease control priorities, our findings present a feasible option for optimizing surveillance efforts-and slowing the spread of AMR.

Citing Articles

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

Zhao C, Wang Y, Mulchandani R, Van Boeckel T Nat Commun. 2024; 15(1):763.

PMID: 38278814 PMC: 10817973. DOI: 10.1038/s41467-024-45111-7.

Predictive Mapping of Antimicrobial Resistance for Escherichia coli, Salmonella, and Campylobacter in Food-Producing Animals, Europe, 2000-2021.

Mulchandani R, Zhao C, Tiseo K, Pires J, Van Boeckel T Emerg Infect Dis. 2023; 30(1):96-104.

PMID: 38146995 PMC: 10756390. DOI: 10.3201/eid3001.221450.

Antimicrobial Resistance in Commensal of the Porcine Gastrointestinal Tract.

ONeill L, Manzanilla E, Ekhlas D, Leonard F Antibiotics (Basel). 2023; 12(11).

PMID: 37998818 PMC: 10669415. DOI: 10.3390/antibiotics12111616.

Genomic analysis of almost 8,000 genomes reveals drivers and landscape of antimicrobial resistance in China.

Wang Y, Xu X, Zhu B, Lyu N, Liu Y, Ma S Microbiol Spectr. 2023; 11(6):e0208023.

PMID: 37787535 PMC: 10714754. DOI: 10.1128/spectrum.02080-23.

The temporal dynamics of antimicrobial-resistant and predominant serovars in China.

Wang Y, Liu Y, Lyu N, Li Z, Ma S, Cao D Natl Sci Rev. 2023; 10(3):nwac269.

PMID: 37035020 PMC: 10076184. DOI: 10.1093/nsr/nwac269.

References

Silbergeld E, Graham J, Price L . Industrial food animal production, antimicrobial resistance, and human health. Annu Rev Public Health. 2008; 29:151-69. DOI: 10.1146/annurev.publhealth.29.020907.090904. View

Mohsin M, Van Boeckel T, Saleemi M, Umair M, Naseem M, He C . Excessive use of medically important antimicrobials in food animals in Pakistan: a five-year surveillance survey. Glob Health Action. 2019; 12(sup1):1697541. PMC: 6896466. DOI: 10.1080/16549716.2019.1697541. View

Nordstrom L, Liu C, Price L . Foodborne urinary tract infections: a new paradigm for antimicrobial-resistant foodborne illness. Front Microbiol. 2013; 4:29. PMC: 3589730. DOI: 10.3389/fmicb.2013.00029. View

Van Boeckel T, Glennon E, Chen D, Gilbert M, Robinson T, Grenfell B . Reducing antimicrobial use in food animals. Science. 2017; 357(6358):1350-1352. PMC: 6510296. DOI: 10.1126/science.aao1495. View

Van Boeckel T, Brower C, Gilbert M, Grenfell B, Levin S, Robinson T . Global trends in antimicrobial use in food animals. Proc Natl Acad Sci U S A. 2015; 112(18):5649-54. PMC: 4426470. DOI: 10.1073/pnas.1503141112. View

Carrique-Mas J, Trung N, Hoa N, Mai H, Thanh T, Campbell J . Antimicrobial usage in chicken production in the Mekong Delta of Vietnam. Zoonoses Public Health. 2014; 62 Suppl 1:70-8. DOI: 10.1111/zph.12165. View

Strom G, Halje M, Karlsson D, Jiwakanon J, Pringle M, Fernstrom L . Antimicrobial use and antimicrobial susceptibility in on small- and medium-scale pig farms in north-eastern Thailand. Antimicrob Resist Infect Control. 2017; 6:75. PMC: 5512823. DOI: 10.1186/s13756-017-0233-9. View

Dyar O, Zhang T, Peng Y, Sun M, Sun C, Yin J . Knowledge, attitudes and practices relating to antibiotic use and antibiotic resistance among backyard pig farmers in rural Shandong province, China. Prev Vet Med. 2019; 175:104858. DOI: 10.1016/j.prevetmed.2019.104858. View

Xiao Y, Li L . China's national plan to combat antimicrobial resistance. Lancet Infect Dis. 2016; 16(11):1216-1218. DOI: 10.1016/S1473-3099(16)30388-7. View

10.

Liu Y, Wang Y, Walsh T, Yi L, Zhang R, Spencer J . Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect Dis. 2015; 16(2):161-8. DOI: 10.1016/S1473-3099(15)00424-7. View

11.

Bhatt S, Gething P, Brady O, Messina J, Farlow A, Moyes C . The global distribution and burden of dengue. Nature. 2013; 496(7446):504-7. PMC: 3651993. DOI: 10.1038/nature12060. View

12.

Gething P, Patil A, Smith D, Guerra C, Elyazar I, Johnston G . A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J. 2011; 10:378. PMC: 3274487. DOI: 10.1186/1475-2875-10-378. View

13.

Gilbert M, Xiao X, Pfeiffer D, Epprecht M, Boles S, Czarnecki C . Mapping H5N1 highly pathogenic avian influenza risk in Southeast Asia. Proc Natl Acad Sci U S A. 2008; 105(12):4769-74. PMC: 2290786. DOI: 10.1073/pnas.0710581105. View

14.

Kraemer M, Sinka M, Duda K, Mylne A, Shearer F, Barker C . The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. Elife. 2015; 4:e08347. PMC: 4493616. DOI: 10.7554/eLife.08347. View

15.

Kabaghe A, Chipeta M, McCann R, Phiri K, van Vugt M, Takken W . Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi. PLoS One. 2017; 12(2):e0172266. PMC: 5308819. DOI: 10.1371/journal.pone.0172266. View

16.

Andrade-Pacheco R, Rerolle F, Lemoine J, Hernandez L, Meite A, Juziwelo L . Finding hotspots: development of an adaptive spatial sampling approach. Sci Rep. 2020; 10(1):10939. PMC: 7331748. DOI: 10.1038/s41598-020-67666-3. View

17.

Weiss D, Nelson A, Gibson H, Temperley W, Peedell S, Lieber A . A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature. 2018; 553(7688):333-336. DOI: 10.1038/nature25181. View

18.

Gilbert M, Nicolas G, Cinardi G, Van Boeckel T, Vanwambeke S, Wint G . Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci Data. 2018; 5:180227. PMC: 6207061. DOI: 10.1038/sdata.2018.227. View

19.

Bai Z, Ma L, Qin W, Chen Q, Oenema O, Zhang F . Changes in pig production in China and their effects on nitrogen and phosphorus use and losses. Environ Sci Technol. 2014; 48(21):12742-9. DOI: 10.1021/es502160v. View

20.

Saksena S, Fox J, Epprecht M, Tran C, Nong D, Spencer J . Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam. PLoS One. 2015; 10(9):e0138138. PMC: 4580613. DOI: 10.1371/journal.pone.0138138. View