Spatial distribution of antimicrobial resistance of extra-intestinal clinical Escherichia coli isolated from poultry farms in western provinces of Cuba

Main Article Content

Oshin Ley-García
Yandy Abreu Jorge
Virginia Masdeus-Fonseca
Patricio Pinto-Morales
Damarys de las N. Montano-Valle
María I. Percedo Abreu
Ivette Espinosa
Pastor Alfonso

Abstract

Antimicrobial resistance (AMR) is a worldwide concern and a threat to global public health. On the other hand, Escherichia coli has played a significant role in the evolution of AMR. The current study aimed to characterise the spatial pattern of AMR of extra-intestinal clinical E. coli isolated from commercial poultry in western provinces of Cuba. Data for the study covered January-2014 to December-2017. Trend analysis and exploratory description were carried out using R environment 4.0.4. ArcMap 10.4 was used for the spatial analysis by the Kernel Density Estimation method and visualisation map. Incremental trends in the frequency of resistance were observed during the study period. Kernel Density indicated that AMR was spatially distributed across the whole geographical region under study, although the highest density (high values) of AMR was located mainly in municipalities of Artemisa province. Areas of significantly higher and lower risk of AMR were identified in the Southeast and North of the region, respectively. Finally, the identification of the spatial distribution and relative risk surface of E. coli antimicrobial resistance from poultry farms in Cuba is a major step that contributes to optimise antimicrobial stewardship practices across the western region. This allows for improved preventive health measures and control strategies to prevent diseases and increase epidemiological surveillance.

Article Details

How to Cite
1.
Ley-García O, Abreu Jorge Y, Masdeus-Fonseca V, Pinto-Morales P, Montano-Valle D de las N, Percedo Abreu MI, Espinosa I, Alfonso P. Spatial distribution of antimicrobial resistance of extra-intestinal clinical Escherichia coli isolated from poultry farms in western provinces of Cuba. Rev. Salud Anim. [Internet]. 2023 Jul. 21 [cited 2024 Nov. 22];45:https://cu-id.com/2248/v45e08. Available from: https://revistas.censa.edu.cu/index.php/RSA/article/view/1215
Section
ARTÍCULOS ORIGINALES

References

Velazquez-Meza ME, Galarde-López M, Carrillo-Quiróz B, Alpuche-Aranda CM. Antimicrobial resistance: One Health approach. Vet World. 2022;15:743-9. Available from: http://dx.doi.org/10.14202/vetworld.2022.743-749

Assoumy MA, Bedekelabou AP, Teko-Agbo A, Ossebi W, Akoda K, Nimbona F, et al. Antibiotic resistance of Escherichia coli and Salmonella spp. strains isolated from healthy poultry farms in the districts of Abidjan and Agnibilékrou (Côte d’Ivoire). Vet World. 2021;14(4):1020-7. Available from: http://dx.doi.org/10.14202/vetworld.2021.1020-1027

FAO. The FAO Action Plan on Antimicrobial Supporting innovation and resilience in food and agriculture sectors [Internet]. Rome, Italia; 2021 [cited 2023 Jun 19]. Available from: https://doi.org/10.4060/cb5545en

WHO, FAO, OIE, UNEP. Strategic Framework for collaboration on antimicrobial resistance - together for One Health. Geneva: World Health Organization, Food and Agriculture Organization of the United Nations and World Organization for Animal Health; 2022. Licence: CC BY-NC-SA 3.0 IGO. [cited 2023 Jun 19] Available from: https://www.who.int/publications/i/item/9789240045408

WHO. WHO integrated global surveillance on ESBL-producing E. coli using a “One Health” approach: implementation and opportunities [Internet]. Geneva, Switzerland: World Health Organization; 2021. Available from: https://www.who.int/publications/i/item/9789240021402

Ramos S, Silva V, de Lurdes Enes Dapkevicius M, Caniça M, Tejedor-Junco MT, Igrejas G, et al. Escherichia coli as Commensal and Pathogenic Bacteria among Food-Producing Animals: Health Implications of Extended Spectrum β-Lactamase (ESBL) Production. Anim an Open Access J from MDPI [Internet]. 2020 Dec 1 [cited 2022 May 9];10(12):1-15. Available from: https://doi.org/10.3390/ANI10122239

Iskandar K, Molinier L, Hallit S, Sartelli M, Hardcastle TC, Haque M, et al. Surveillance of antimicrobial resistance in low- and middle-income countries: a scattered picture. Antimicrob Resist Infect Control. 2021;10(1):1-19. Available from: https://doi.org/10.1186/s13756-021-00931-w

Schnall J, Rajkhowa A, Ikuta K, Rao P, Moore CE. Surveillance and monitoring of antimicrobial resistance: limitations and lessons from the GRAM project. BMC Med 2019 171 [Internet]. 2019 Sep 20 [cited 2021 Jul 22];17(1):1-3. Available from: https://doi.org/10.1186/S12916-019-1412-8

Safdari R, Ghazi Saeedi M, Masoumi-Asl H, Rezaei-Hachesu P, Mirnia K, Mohammadzadeh N, et al. National Minimum Data Set for Antimicrobial Resistance Management: Toward Global Surveillance System. Iran J Med Sci [Internet]. 2018 Sep 1 [cited 2023 Jun 19];43(5):494. Available from: PMID: 30214102; PMCID: PMC6123552.

Expósito B, Bermellón S, Lescaille G, Delgado R, Aliaga C. Resistencia antimicrobiana de la Escherichia coli en pacientes con infección del tracto urinario. Rev Inf Científica [Internet]. 2019;98(6):755-64. Available from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1028-99332019000600755&lng=es.

Espinosa I, Baez M, Marrero K, Perreten V, Lobo E, Martínez S, et al. Primeros Hallazgos De Resistencia Antimicrobiana En Especies De Bacterias Patógenas, Zoonóticas Y Comensales En La Producción Porcina En Cuba. Rev An la Acad Ciencias Cuba [Internet]. 2017;8(1):1-8. Available from: http://www.revistaccuba.cu/index.php/revacc/article/view/368

Baez M, Espinosa I, Collaud A, Miranda I, Montano D de las N, Feria AL, et al. Genetic Features of Extended-Spectrum β-Lactamase-Producing Escherichia coli from Poultry in Mayabeque Province, Cuba. Antibiotics [Internet]. 2021 Jan 22 [cited 2021 Feb 22];10(2):107. Available from: https://doi.org/10.3390/antibiotics10020107

Ruckthongsook W, Tiwari C, Oppong JR, Natesan P. Evaluation of threshold selection methods for adaptive kernel density estimation in disease mapping. Int J Health Geogr. 2018 May 8;17(1):1-13. Available from: https://doi.org/10.1186/s12942-018-0129-9

Elson R, Davies TM, Jenkins C, Vivancos R, O’Brien SJ, Lake IR. Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England. Spat Spatiotemporal Epidemiol. 2020 Feb 1;32(2). Available from: https://doi.org/10.1016/j.sste.2019.100305

Microsoft Corporation. Microsoft Excel TM. Redmond, Washington: Microsoft Corporation; 2016.

CLSI. Performance Standards for Antimicrobial Susceptibility Testing 27 th ed. CLSI supplement M100. Wayne, PA: Clinical and Laboratory Standards Institute [Internet]. 2017. Available from: https://file.qums.ac.ir/repository/mmrc/clsi2017.pdf

Thrusfield M, Christley R, Brown H, Diggle PJ, French N, Howe K, et al. Veterinary Epidemiology [Internet]. Fourth Edi. Hoboken N, editor. Wiley; 2018. Available from: https://www.wiley.com/en-us/Veterinary+Epidemiology%2C+4th+Edition-p-9781118280287

Davies TM, Marshall JC, Hazelton ML. Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk. Stat Med. 2017;37(7):1-31. Available from: https://doi.org/10.1002/sim.7577

Davies TM, Jones K, Hazelton ML. Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function. Comput Stat Data Anal. 2016 Sep 1;101:12-28. Available from: https://doi.org/10.1016/j.csda.2016.02.008

Wickham H. ggplot2 - Elegant Graphics for Data Analysis (2nd Edition). J Stat Softw. 2017;77(April):3-5.

Millard SP. Getting Started. In: EnvStats [Internet]. New York, NY: Springer New York; 2013 [cited 2021 May 12]. p. 1-24. Available from: http://link.springer.com/10.1007/978-1-4614-8456-1_1

R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria; 2017. Available from: https://www.r-project.org/

ESRI. ArcGIS E. Release 10.4. Redlands, CA: ESRI [Internet]. 2015. Available from: https://www.esri.com/en-us/arcgis/about-arcgis/overview

Poirel L, Madec J-Y, Lupo A, Schink A-K, Kieffer N, Nordmann P, et al. Antimicrobial Resistance in Escherichia coli. In: Antimicrobial Resistance in Bacteria from Livestock and Companion Animals [Internet]. American Society of Microbiology; 2018 [cited 2021 Feb 22]. p. 289-316. Available from: https://doi.org/10.1128/microbiolspec.arba-0026-2017

Hedman HD, Zhang L, Trueba G, Vinueza Rivera DL, Zurita Herrera RA, Barrazueta JJV, et al. Spatial Exposure of Agricultural Antimicrobial Resistance in Relation to Free-Ranging Domestic Chicken Movement Patterns among Agricultural Communities in Ecuador. Am J Trop Med Hyg [Internet]. 2020 Nov 4 [cited 2022 Mar 17];103(5):1803-9. Available from: https://doi.org/10.4269/AJTMH.20-0076

Ahmad I, Malak HA, Abulreesh HH. Environmental antimicrobial resistance and its drivers : a potential threat to public health. J Glob Antimicrob Resist [Internet]. 2021;27:101-11. Available from: https://doi.org/10.1016/j.jgar.2021.08.001

Guo K, Zhao Y, Cui L, Cao Z, Zhang F. The Influencing Factors of Bacterial Resistance Related to Livestock Farm : Sources and Mechanisms. Front Anim Sci. 2021;2. Available from: https://doi.org/10.3389/fanim.2021.650347

Hernández R, Báez F, Zamora P, Espinosa I. Susceptibilidad antimicrobiana y formación de biopelícula en aislados de Escherichia coli procedentes de gallinas ponedoras. Revi Salud Anim. 2017;39(3):1-14. Available from: http://www.revistaccuba.cu/index.php/revacc/article/view/368

Varga C, Guerin MT, Brash ML, Slavic D, Boerlin P, Susta L. Antimicrobial resistance in fecal Escherichia coli and Salmonella enterica isolates: a two-year prospective study of small poultry flocks in Ontario, Canada. BMC Vet Res [Internet]. 2019 Dec 21;15(1):1-10. Available from: https://doi.org/10.1186/s12917-019-2187-z

Bennani H, Mateus A, Mays N, Eastmure E, Stärk KDC, Häsler B. Overview of evidence of antimicrobial use and antimicrobial resistance in the food chain. Antibiotics [Internet]. 2020 Feb 1 [cited 2021 Feb 22];9(2):49. Available from: https://doi.org/10.3390/antibiotics9020049

OIE. Anual report on antimicrobial agents intended for use in animals. Better undertsanding of the global situattion [Internet]. 2018. Available from: https://www.oie.int/fileadmin/Home/eng/Our_scientific_expertise/docs/pdf/AMR/A_Third_Annual_Report_AMR.pdf

Tonoyan L, Fleming GTA, Friel R, O’Flaherty V. Continuous culture of Escherichia coli, under selective pressure by a novel antimicrobial complex, does not result in development of resistance. Sci Rep [Internet]. 2019 Dec 1 [cited 2023 Jun 19];9(1). Available from: https://doi.org/10.1038/S41598-019-38925-9

Akram F, Imtiaz M, Haq I ul. Emergent crisis of antibiotic resistance: A silent pandemic threat to 21st century. Microb Pathog. 2023 Jan 1;174:105923. https://doi.org/10.1038/S41598-019-38925-9

Liu X, Li R, Chan EWC, Xia X, Chen S. Plasmid-mediated ciprofloxacin, carbapenem and colistin resistance of a foodborne Escherichia coli isolate. Food Control. 2022 Jul 1;137:108937. Available from: https://doi.org/10.1016/J.FOODCONT.2022.108937

MINJUS. Gaceta Oficial No. 11 Ordinaria de 29 de enero de 2021. Decreto 20/2020 Contravenciones de la medicina veterinaria (GOC-2021-134-O11) [Internet]. Ministerio de Justicia. La Habanam Cuba: Ministerio de Justicia; 2021. Available from: https://www.gacetaoficial.gob.cu/es/gaceta-oficial-no-11-ordinaria-de-2021

Argudín MA, Deplano A, Meghraoui A, Dodémont M, Heinrichs A, Denis O, et al. Bacteria from Animals as a Pool of Antimicrobial Resistance Genes. Antibiotics [Internet]. 2017 Jun 6 [cited 2021 Dec 29];6(2):12. Available from: https://doi.org/10.3390/ANTIBIOTICS6020012

ONEI. Anuario Estadístico de Cuba. Agricultura, Ganadería, Silvicultura y Pesca. Edición 2021 [Internet]. 2021 [cited 2021 Feb 22]. Available from: http://www.onei.gob.cu/sites/default/files/agropecuario_-2020_0.pdf

Bindari YR, Gerber PF. Centennial Review: Factors affecting the chicken gastrointestinal microbial composition and their association with gut health and productive performance. Poult Sci. 2022 Jan 1;101(1):101612. Available from: https://doi.org/10.1016/J.PSJ.2021.101612

Ibrahim RA, Cryer TL, Lafi SQ, Basha EA, Good L, Tarazi YH. Identification of Escherichia coli from broiler chickens in Jordan, their antimicrobial resistance, gene characterization and the associated risk factors. BMC Vet Res [Internet]. 2019 May 22 [cited 2022 Mar 22];15(1):1-16. Available from: https://doi.org/10.1186/S12917-019-1901-1/TABLES/8

Muloi DM, Wee BA, McClean DMH, Ward MJ, Pankhurst L, Phan H, et al. Population genomics of Escherichia coli in livestock-keeping households across a rapidly developing urban landscape. Nat Microbiol 2022 74 [Internet]. 2022 Mar 14 [cited 2023 Jun 19];7(4):581-9. Available from: https://doi.org/10.1038/s41564-022-01079-y

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