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Surveillance Open Access
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Abstract

Background

Multidrug-resistant (MDR) bacteria are among chief causes of healthcare-associated infections (HAIs). In Spain, studies addressing multidrug resistance based on epidemiological surveillance systems are lacking.

Aim

In this observational study, cases of HAIs by MDR bacteria notified to the epidemiological surveillance system of Andalusia, Spain, between 2014−2021, were investigated. Notified cases and their spatiotemporal distribution were described, with a focus on social determinants of health (SDoH).

Methods

New cases during the study period of HAIs caused by extended-spectrum β-lactamase (ESBL)-/carbapenemase-producing Enterobacterales, MDR , MDR or meticillin resistant were considered. Among others, notification variables included sex and age, while socio-economic variables comprised several SDoH. Cases’ spatial distribution across municipalities was assessed. The smooth standardised incidence ratio (sSIR) was obtained using a Bayesian spatial model. Association between municipalities’ sSIR level and SDoH was evaluated by bivariate analysis.

Results

In total, 6,389 cases with a median age of 68 years were notified; 61.4% were men (n = 3,921). The most frequent MDR bacteria were ESBL-producing Enterobacterales (2,812/6,389; 44.0%); the main agent was spp. (2,956/6,389; 46.3%). Between 2014 and 2021 case numbers appeared to increase. Overall, up to 15-fold differences in sSIR between municipalities were observed. In bivariate analysis, there appeared to be an association between municipalities’ sSIR level and deprivation (p = 0.003).

Conclusion

This study indicates that social factors should be considered when investigating HAIs by MDR bacteria. The case incidence heterogeneity between Andalusian municipalities might be explained by SDoH, but also possibly by under-notification. Automatising reporting may address the latter.

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/content/10.2807/1560-7917.ES.2023.28.39.2200805
2023-09-28
2024-06-15
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2023.28.39.2200805
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References

  1. Baquero F. From pieces to patterns: evolutionary engineering in bacterial pathogens. Nat Rev Microbiol. 2004;2(6):510-8.  https://doi.org/10.1038/nrmicro909  PMID: 15152207 
  2. Cole J. Antimicrobial resistance--a ‘rising tide’ of national (and international) risk. J Hosp Infect. 2016;92(1):3-4.  https://doi.org/10.1016/j.jhin.2015.10.005  PMID: 26631624 
  3. European Centre for Disease Prevention and Control (ECDC). Antimicrobial resistance in the EU/EEA (EARS-Net) - Annual Epidemiological Report for 2020. Stockholm: ECDC; 2022. [Accessed 17 Aug 2021]. Available from: https://www.ecdc.europa.eu/en/publications-data/antimicrobial-resistance-eueea-ears-net-annual-epidemiological-report-2020
  4. Bonnet V, Dupont H, Glorion S, Aupée M, Kipnis E, Gérard JL, et al. Influence of bacterial resistance on mortality in intensive care units: a registry study from 2000 to 2013 (IICU Study). J Hosp Infect. 2019;102(3):317-24.  https://doi.org/10.1016/j.jhin.2019.01.011  PMID: 30659869 
  5. Murray CJ, Ikuta KS, Sharara F, Swetschinski L, Robles Aguilar G, Gray A, et al. , Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629-55.  https://doi.org/10.1016/S0140-6736(21)02724-0  PMID: 35065702 
  6. World Health Organization (WHO). Prioritization of pathogens to guide discovery, research and development of new antibiotics for drug-resistant bacterial infections, including tuberculosis. Geneva: WHO; 2017. Available from: https://www.who.int/publications/i/item/WHO-EMP-IAU-2017.12
  7. Lipsitch M, Samore MH. Antimicrobial use and antimicrobial resistance: a population perspective. Emerg Infect Dis. 2002;8(4):347-54.  https://doi.org/10.3201/eid0804.010312  PMID: 11971765 
  8. Malhotra-Kumar S, Lammens C, Coenen S, Van Herck K, Goossens H. Effect of azithromycin and clarithromycin therapy on pharyngeal carriage of macrolide-resistant streptococci in healthy volunteers: a randomised, double-blind, placebo-controlled study. Lancet. 2007;369(9560):482-90.  https://doi.org/10.1016/S0140-6736(07)60235-9  PMID: 17292768 
  9. Low M, Neuberger A, Hooton TM, Green MS, Raz R, Balicer RD, et al. Association between urinary community-acquired fluoroquinolone-resistant Escherichia coli and neighbourhood antibiotic consumption: a population-based case-control study. Lancet Infect Dis. 2019;19(4):419-28.  https://doi.org/10.1016/S1473-3099(18)30676-5  PMID: 30846277 
  10. Muraki Y, Kitamura M, Maeda Y, Kitahara T, Mori T, Ikeue H, et al. Nationwide surveillance of antimicrobial consumption and resistance to Pseudomonas aeruginosa isolates at 203 Japanese hospitals in 2010. Infection. 2013;41(2):415-23.  https://doi.org/10.1007/s15010-013-0440-0  PMID: 23471823 
  11. Alividza V, Mariano V, Ahmad R, Charani E, Rawson TM, Holmes AH, et al. Investigating the impact of poverty on colonization and infection with drug-resistant organisms in humans: a systematic review. Infect Dis Poverty. 2018;7(1):76.  https://doi.org/10.1186/s40249-018-0459-7  PMID: 30115132 
  12. Allel K, García P, Labarca J, Munita JM, Rendic M, Undurraga EA, Grupo Colaborativo de Resistencia Bacteriana. Socioeconomic factors associated with antimicrobial resistance of Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli in Chilean hospitals (2008-2017). Rev Panam Salud Publica. 2020;44:e30.  https://doi.org/10.26633/RPSP.2020.30  PMID: 32973892 
  13. Nomamiukor BO, Horner C, Kirby A, Hughes GJ. Living conditions are associated with increased antibiotic resistance in community isolates of Escherichia coli. J Antimicrob Chemother. 2015;70(11):3154-8.  https://doi.org/10.1093/jac/dkv229  PMID: 26260128 
  14. Collignon P, Beggs JJ, Walsh TR, Gandra S, Laxminarayan R. Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis. Lancet Planet Health. 2018;2(9):e398-405.  https://doi.org/10.1016/S2542-5196(18)30186-4  PMID: 30177008 
  15. World Health Organization (WHO). Tackling antimicrobial resistance (‎AMR)‎ together: working paper 5.0: enhancing the focus on gender and equity. WHO: Geneva; 2018 [Accessed 11 Jul 2022]. Available from: https://apps.who.int/iris/handle/10665/336977
  16. Junta de Andalucía. Consejería de Salud y Consumo. Programas de Vigilancia de Enfermedades Transmisibles. [Communicable Disease Surveillance Programmes]. [Accessed 24 Jan 2023]. Available from: https://www.juntadeandalucia.es/organismos/saludyconsumo/areas/salud-vida/vigilancia/paginas/vigilancia-transmisibles.html
  17. Duque I, Domínguez-Berjón MF, Cebrecos A, Prieto-Salceda MD, Esnaola S, Calvo Sánchez M, et al. , en nombre del Grupo de Determinantes Sociales de la Salud, iniciativa contexto de la Sociedad Española de Epidemiología. Índice de privación en España por sección censal en 2011. [Deprivation index by enumeration district in Spain, 2011]. Gac Sanit. 2021;35(2):113-22.  https://doi.org/10.1016/j.gaceta.2019.10.008  PMID: 32014314 
  18. Junta de Andalucía. Consejería de Salud y Familias. Programa integral de prevención y control de las infecciones relacionadas con la asistencia sanitaria y uso apropiado de los antimicrobianos. [Institutional Programme for the Prevention and Control of Healthcare-Associated Infections and Appropriate Use of Antimicrobials]. Informes PIRASOA. 2022. Available from: http://pirasoa.iavante.es/course/view.php?id=3&section=2
  19. Dijkstra L, Poelman H. A harmonised definition of cities and rural areas: the new degree of urbanisation. Brussels, Belgium; 2014. [Accessed 22 Aug 2022]. Report No.: 01/2014. Available from: https://ec.europa.eu/regional_policy/es/information/publications/working-papers/2014/a-harmonised-definition-of-cities-and-rural-areas-the-new-degree-of-urbanisation
  20. Gini C. On the Measure of Concentration with Special Reference to Income and Statistics. Colorado College Publication, General Series. 1936; No. 208:73-9.
  21. Le Grand J, Rabin M. (1986) Trends in British health inequality, 1931-83. In: Culyer, A. J. and Jonsson, Bengt, (eds.) Public and Private Health Services: Complementarities and Conflicts. Basil Blackwell Publisher, Oxford, UK, pp. 112-127. ISBN 0631150889.
  22. INEbase. Madrid: Instituto Nacional de Estadística; 2022. Encuesta de condiciones de vida. Resultados nacionales. Riesgo de pobreza 2015. [Survey of living conditions. National results. Risk of poverty 2015]. Available from: https://www.ine.es/jaxiT3/Tabla.htm?t=9966&L=0
  23. National Healthcare Safety Network (NHSN). Procedure-associated Module. Surgical Site Infection Event (SSI). 2022 Jan [Accessed 27 Sep 2022]. Available from: https://www.cdc.gov/nhsn/pdfs/ps-analysis-resources/ImportingProcedureData.pdf
  24. Sistema de Vigilancia Epidemiológica de Andalucía (SVEA). Protocolo de vigilancia y control de infecciones relacionadas con la asistencia sanitaria (IRAS) producidas por microorganismos multirresistentes (MMR). [Protocol for surveillance and control of healthcare-associated infections (HAI) caused by multidrug-resistant microorganisms]. Seville, Spain; 2018. [Accessed 19 Aug 2022]. Available from: https://www.juntadeandalucia.es/export/drupaljda/SVSL_IRAS Protocolo Vigilancia CASOS MMR 20181127.pdf
  25. Besag J, York J, Mollié A. Bayesian image restoration, with two applications in spatial statistics. Ann Inst Stat Math. 1991;43(1):1-20.  https://doi.org/10.1007/BF00116466 
  26. Moraga P. Areal data. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny. Chapman & Hall/CRC Biostatistics Series; 2019. Available from: https://www.paulamoraga.com/book-geospatial/index.htm
  27. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2022. Available from: https://www.r-project.org/
  28. Centers for Disease Control and Prevention (CDC);National Center for Emerging and Zoonotic Infectious Diseases. Division of Healthcare Quality Promotion; COVID-19: U.S. Impact on Antimicrobial Resistance, Special Report 2022. Atlanta: CDC; 2022 [Accessed 2 Aug 2022]. Available from: https://stacks.cdc.gov/view/cdc/117915
  29. Weiner LM, Webb AK, Limbago B, Dudeck MA, Patel J, Kallen AJ, et al. Antimicrobial-Resistant Pathogens Associated With Healthcare-Associated Infections: Summary of Data Reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2011-2014. Infect Control Hosp Epidemiol. 2016;37(11):1288-301.  https://doi.org/10.1017/ice.2016.174  PMID: 27573805 
  30. Weiner-Lastinger LM, Abner S, Edwards JR, Kallen AJ, Karlsson M, Magill SS, et al. Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015-2017. Infect Control Hosp Epidemiol. 2020;41(1):1-18.  https://doi.org/10.1017/ice.2019.296  PMID: 31767041 
  31. Canadian Nosocomial Infection Surveillance Program. Healthcare-associated infections and antimicrobial resistance in Canadian acute care hospitals, 2014-2018. Can Commun Dis Rep. 2020;46(5):99-112.  https://doi.org/10.14745/ccdr.v46i05a01  PMID: 32558807 
  32. Suzuki S. A View on 20 Years of Antimicrobial Resistance in Japan by Two National Surveillance Systems: The National Epidemiological Surveillance of Infectious Diseases and Japan Nosocomial Infections Surveillance. Antibiotics (Basel). 2021;10(10):1189.  https://doi.org/10.3390/antibiotics10101189  PMID: 34680770 
  33. Kohler P, Fulchini R, Albrich WC, Egli A, Balmelli C, Harbarth S, et al. Antibiotic resistance in Swiss nursing homes: analysis of National Surveillance Data over an 11-year period between 2007 and 2017. Antimicrob Resist Infect Control. 2018;7(1):88.  https://doi.org/10.1186/s13756-018-0378-1  PMID: 30038781 
  34. Eure TR, Stone ND, Mungai EA, Bell JM, Thompson ND. Antibiotic-resistant pathogens associated with urinary tract infections in nursing homes: Summary of data reported to the National Healthcare Safety Network Long-Term Care Facility Component, 2013-2017. Infect Control Hosp Epidemiol. 2021;42(1):31-6.  https://doi.org/10.1017/ice.2020.348  PMID: 32782037 
  35. Tydeman F, Craine N, Kavanagh K, Adams H, Reynolds R, McClure V, et al. Incidence of Clostridioides difficile infection (CDI) related to antibiotic prescribing by GP surgeries in Wales. J Antimicrob Chemother. 2021;76(9):2437-45.  https://doi.org/10.1093/jac/dkab204  PMID: 34151964 
  36. Fortin E, Thirion DJG, Ouakki M, Garenc C, Lalancette C, Bergeron L, et al. , Québec Clostridiodes difficile Infection Surveillance Program (SPIN-CD). Role of high-risk antibiotic use in incidence of health-care-associated Clostridioides difficile infection in Quebec, Canada: a population-level ecological study. Lancet Microbe. 2021;2(5):e182-90.  https://doi.org/10.1016/S2666-5247(21)00005-7  PMID: 35544207 
  37. Tosas Auguet O, Betley JR, Stabler RA, Patel A, Ioannou A, Marbach H, et al. Evidence for Community Transmission of Community-Associated but Not Health-Care-Associated Methicillin-Resistant Staphylococcus Aureus Strains Linked to Social and Material Deprivation: Spatial Analysis of Cross-sectional Data. PLoS Med. 2016;13(1):e1001944.  https://doi.org/10.1371/journal.pmed.1001944  PMID: 26812054 
  38. Collignon P, Beggs JJ, Walsh TR, Gandra S, Laxminarayan R. Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis. Lancet Planet Health. 2018;2(9):e398-405.  https://doi.org/10.1016/S2542-5196(18)30186-4  PMID: 30177008 
  39. Forrester JD, Cao S, Schaps D, Liou R, Patil A, Stave C, et al. Influence of Socioeconomic and Environmental Determinants of Health on Human Infection and Colonization with Antibiotic-Resistant and Antibiotic-Associated Pathogens: A Scoping Review. Surg Infect (Larchmt). 2022;23(3):209-25.  https://doi.org/10.1089/sur.2021.348  PMID: 35100052 
  40. European Centre for Disease Prevention and Control (ECDC). Data quality monitoring and surveillance system evaluation - A handbook of methods and applications. Stockholm: ECDC; 2014. [Accessed 24 Jan 2023]. Available from: https://www.ecdc.europa.eu/en/publications-data/data-quality-monitoring-and-surveillance-system-evaluation-handbook-methods-and
  41. Kavanagh KT, Abusalem S, Calderon LE. The incidence of MRSA infections in the United States: is a more comprehensive tracking system needed? Antimicrob Resist Infect Control. 2017;6(1):34.  https://doi.org/10.1186/s13756-017-0193-0  PMID: 28396730 
  42. O’Driscoll T, Crank CW. Vancomycin-resistant enterococcal infections: epidemiology, clinical manifestations, and optimal management. Infect Drug Resist. 2015;8:217-30.  PMID: 26244026 
  43. García Martínez de Artola D, Castro B, Ramos MJ, Díaz Cuevas Z, Lakhwani S, Lecuona M. Outbreak of vancomycin-resistant enterococcus on a haematology ward: management and control. J Infect Prev. 2017;18(3):149-53.  https://doi.org/10.1177/1757177416687832 
  44. Thomas BE, Shanmugam P, Malaisamy M, Ovung S, Suresh C, Subbaraman R, et al. Psycho-Socio-Economic Issues Challenging Multidrug Resistant Tuberculosis Patients: A Systematic Review. PLoS One. 2016;11(1):e0147397.  https://doi.org/10.1371/journal.pone.0147397  PMID: 26807933 
  45. Jeong HE, Bea S, Kim JH, Jang SH, Son H, Shin JY. Socioeconomic disparities and multidrug-resistant tuberculosis in South Korea: Focus on immigrants and income levels. J Microbiol Immunol Infect. 2023;56(2):424-8.  https://doi.org/10.1016/j.jmii.2022.08.014  PMID: 36115791 
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