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An agent-based model to simulate the transmission of vancomycin-resistant enterococci according different prevention and control measures

Published online by Cambridge University Press:  18 December 2020

Stéphanie Deboscker*
Affiliation:
Service d’hygiène hospitalière, Hôpitaux universitaires de Strasbourg, Strasbourg, France ICube, UMR7357, Universitè de Strasbourg, Strasbourg, France
François Séverac
Affiliation:
ICube, UMR7357, Universitè de Strasbourg, Strasbourg, France Groupe Méthode en Recherche Clinique (GMRC), Service de Santé Publique, Hôpitaux universitaires de Strasbourg, Strasbourg, France
Jean Gaudart
Affiliation:
Hôpital La Timone, Service Biostatistique et Technologies de l’Information et de la Communication, APHM, Marseille, France IRD, INSERM, SESSTIM UMR912, Aix Marseille Univ, Marseille, France
Céline Ménard
Affiliation:
Service d’hygiène hospitalière, Hôpitaux universitaires de Strasbourg, Strasbourg, France Laboratoire de bactèriologie, Hôpitaux universitaires de Strasbourg, Strasbourg, France
Nicolas Meyer
Affiliation:
ICube, UMR7357, Universitè de Strasbourg, Strasbourg, France Groupe Méthode en Recherche Clinique (GMRC), Service de Santé Publique, Hôpitaux universitaires de Strasbourg, Strasbourg, France
Thierry Lavigne
Affiliation:
Service d’hygiène hospitalière, Hôpitaux universitaires de Strasbourg, Strasbourg, France
*
Author for correspondence: Dr Stéphanie Deboscker, E-mail: stephanie.deboscker@chru-strasbourg.fr

Abstract

Objective:

Despite the existence of various levels of infection prevention and control (IPC) measures aimed at limiting the transmission of vancomycin-resistant enterococci (VRE) in hospitals, these measures are sometimes difficult to implement. Using an agent-based model (ABM), we simulated the transmission of VRE within and between 3 care units according to different IPC measures.

Methods:

The ABM was modelled on short-stay medical wards, represented by 2 conventional care units and 1 intensive care unit. The scenarios consisted of the simulation of various compliance rates of caregivers with regard to hand hygiene (HH) in different contexts of IPC measures: (1) standard precautions for all patients, (2) additional contact precautions for VRE-carrier patients, (3) geographical cohorting of carrier patients, and (4) creation of an isolation unit with dedicated staff.

Results:

With <50% HH compliance, the dissemination of VRE was not adequately controlled. With 80% compliance for all patients (ie, standard precautions scenario), there were no secondary VRE cases in 50% of the simulations, which represented the best scenario. A more realistic rate, 60% HH compliance for all patients, revealed interesting results. Implementing an isolation unit was effective only if the level of HH compliance was low. Patient cohorting was less effective.

Conclusions:

The present ABM showed that while contact precautions, geographic cohorting, and an isolation unit may represent good complements to standard precautions, they may theoretically not be necessary if HH is followed at a high level of compliance.

Type
Original Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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References

Cattoir, V, Leclercq, R. Twenty-five years of shared life with vancomycin-resistant enterococci: is it time to divorce? J Antimicrob Chemother 2013;68:731742.CrossRefGoogle ScholarPubMed
Wolfensberger, A, Clack, L, Kuster, SP, et al. Transfer of pathogens to and from patients, healthcare providers, and medical devices during care activity—a systematic review and meta-analysis. Infect Control Hosp Epidemiol 2018;39:10931107.CrossRefGoogle ScholarPubMed
Siegel, JD, Rhinehart, E, Jackson, M, Chiarello, L. Healthcare Infection Control Practices Advisory Committee. Management of multidrug-resistant organisms in healthcare settings, 2006. Am J Infect Control 2007;35(10 suppl 2):S165S193.CrossRefGoogle Scholar
HCSP. Actualisation des recommandations relatives aux BHRe. Paris: Haut Conseil de la Santé Publique 2019 Dec. https://www.hcsp.fr/explore.cgi/avisrapportsdomaine?clefr=758 (accessed 20 Feb 2020).Google Scholar
Stelfox, HT, Bates, DW, Redelmeier, DA. Safety of patients isolated for infection control. JAMA 2003;290:18991905.CrossRefGoogle ScholarPubMed
Kim, T, Oh, PI, Simor, AE. The economic impact of methicillin-resistant Staphylococcus aureus in Canadian hospitals. Infect Control Hosp Epidemiol 2001;22:99104.CrossRefGoogle ScholarPubMed
Reeme, AE, Bowler, SL, Buchan, BW, et al. Use of a cohorting-unit and systematic surveillance cultures to control a Klebsiella pneumoniae carbapenemase (KPC)–producing Enterobacteriaceae outbreak. Infect Control Hosp Epidemiol 2019;40:767773.CrossRefGoogle ScholarPubMed
Keeling, MJ, Rohani, P. Modeling Infectious Diseases in Humans and Animals, 1st ed. Princeton, NJ: Princeton University Press; 2007: 408 pp.Google Scholar
Railsback, SF, Grimm, V. Agent-Based and Individual-Based Modeling: A Practical Introduction, 2nd ed. Princeton, NJ: Princeton University Press; 2019: 360 pp.Google Scholar
D’Agata, EMC, Magal, P, Olivier, D, Ruan, S, Webb, GF. Modeling antibiotic resistance in hospitals: the impact of minimizing treatment duration. J Theor Biol 2007;249:487499.CrossRefGoogle ScholarPubMed
Hotchkiss, JR, Strike, DG, Simonson, DA, Broccard, AF, Crooke, P. An agent-based and spatially explicit model of pathogen dissemination in the intensive care unit. Crit Care Med 2005;33:168.CrossRefGoogle ScholarPubMed
Temime, L, Opatowski, L, Pannet, Y, Brun-Buisson, C, Boëlle, PY, Guillemot, D. Peripatetic healthcare workers as potential superspreaders. Proc Natl Acad Sci U S A 2009;106:1842018425.CrossRefGoogle ScholarPubMed
Barnes, SL, Morgan, DJ, Harris, AD, Carling, PC, Thom, KA. Preventing the transmission of multidrug-resistant organisms: modeling the relative importance of hand hygiene and environmental cleaning interventions. Infect Control Hosp Epidemiol 2014;35:11561162.CrossRefGoogle ScholarPubMed
Lee, BY, Yilmaz, SL, Wong, KF, et al. Modeling the regional spread and control of vancomycin-resistant enterococci. Am J Infect Control 2013;41:668673.CrossRefGoogle ScholarPubMed
Triola, MM, Holzman, RS. Agent-based simulation of nosocomial transmission in the medical intensive care unit. In: 16th IEEE Symposium Computer-Based Medical Systems, 2003 Proceedings. New York, NY, USA: IEEE 2003 doi: 10.1109/CBMS.2003.1212803.CrossRefGoogle Scholar
Milazzo, L, Bown, JL, Eberst, A, Phillips, G, Crawford, JW. Modelling of healthcare-associated infections: a study on the dynamics of pathogen transmission by using an individual-based approach. Comput Methods Programs Biomed 2011;104:260265.CrossRefGoogle Scholar
Rubin, MA, Jones, M, Leecaster, M, Khader, K, Ray, W, Huttner, A, et al. A simulation-based assessment of strategies to control Clostridium difficile transmission and infection. PLoS One 2013;8(11):e80671.CrossRefGoogle ScholarPubMed
Codella, J, Safdar, N, Heffernan, R, Alagoz, O. An agent-based simulation model for Clostridium difficile infection control. Med Decis Making 2015;35:211229.CrossRefGoogle ScholarPubMed
Barker, AK, Alagoz, O, Safdar, N. Interventions to reduce the incidence of hospital-onset Clostridium difficile infection: an agent-based modeling approach to evaluate clinical effectiveness in adult acute-care hospitals. Clin Infect Dis 2018;66:11921203.CrossRefGoogle ScholarPubMed
Grimm, V, Berger, U, Bastiansen, F, et al. A standard protocol for describing individual-based and agent-based models. Ecol Model 2006;198:115126.CrossRefGoogle Scholar
Grimm, V, Berger, U, DeAngelis, DL, Polhill, JG, Giske, J, Railsback, SF. The ODD protocol: a review and first update. Ecol Model 2010;221:27602768.CrossRefGoogle Scholar
Wilensky, U. 1999. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University website. http://ccl.northwestern.edu/netlogo/. Accessed November 3, 2020.Google Scholar
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing,Vienna, Austria 2019. https://www.R-project.org/.Google Scholar
Austin, DJ, Bonten, MJ, Weinstein, RA, Slaughter, S, Anderson, RM. Vancomycin-resistant enterococci in intensive-care hospital settings: transmission dynamics, persistence, and the impact of infection control programs. Proc Natl Acad Sci U S A 1999;96:69086913.CrossRefGoogle ScholarPubMed
D’Agata, EMC, Horn, MA, Webb, GF. The impact of persistent gastrointestinal colonization on the transmission dynamics of vancomycin-resistant enterococci. J Infect Dis 2002;185:766773.CrossRefGoogle ScholarPubMed
Wolkewitz, M, Dettenkofer, M, Bertz, H, Schumacher, M, Huebner, J. Environmental contamination as an important route for the transmission of the hospital pathogen VRE: modeling and prediction of classical interventions. Infect Dis Res Treat 2008;1:311.Google Scholar
Cooper, BS, Medley, GF, Scott, GM. Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. J Hosp Infect 1999;43:131147.CrossRefGoogle ScholarPubMed
D’Agata, EMC, Webb, G, Horn, M. A mathematical model quantifying the impact of antibiotic exposure and other interventions on the endemic prevalence of vancomycin-resistant enterococci. J Infect Dis 2005;192:20042011.CrossRefGoogle ScholarPubMed
DalBen M de F, Teixeira Mendes, E, Moura, ML, et al. A model-based strategy to control the spread of carbapenem-resistant Enterobacteriaceae: simulate and implement. Infect Control Hosp Epidemiol 2016;37:13151322.Google Scholar
Pittet, D, Mourouga, P, Perneger, TV. Compliance with handwashing in a teaching hospital. Infection Control Program. Ann Intern Med 1999;130:126130.CrossRefGoogle Scholar
Boyce, JM, Laughman, JA, Ader, MH, Wagner, PT, Parker, AE, Arbogast, JW. Impact of an automated hand hygiene monitoring system and additional promotional activities on hand hygiene performance rates and healthcare-associated infections. Infect Control Hosp Epidemiol 2019;40:741747.CrossRefGoogle ScholarPubMed
Erasmus, V, Daha, TJ, Brug, H, et al. Systematic review of studies on compliance with hand hygiene guidelines in hospital care. Infect Control Hosp Epidemiol 2010;31:283294.CrossRefGoogle ScholarPubMed
Dufour, JC, Reynier, P, Boudjema, S, Soto Aladro, A, Giorgi, R, Brouqui, P. Evaluation of hand hygiene compliance and associated factors with a radio-frequency-identification–based real-time continuous automated monitoring system. J Hosp Infect 2017;95:344351.CrossRefGoogle ScholarPubMed
Eveillard, M, Hitoto, H, Raymond, F, et al. Measurement and interpretation of hand hygiene compliance rates: importance of monitoring entire care episodes. J Hosp Infect 2009;72:211217.CrossRefGoogle ScholarPubMed
Yahdi, M, Abdelmageed, S, Lowden, J, Tannenbaum, L. Vancomycin-resistant enterococci colonization-infection model: parameter impacts and outbreak risks. J Biol Dyn 2012;6:645662.CrossRefGoogle ScholarPubMed
Arias, CA, Murray, BE. The rise of the Enterococcus: beyond vancomycin resistance. Nat Rev Microbiol 2012;10:266278.CrossRefGoogle ScholarPubMed
Rutala, WA, Weber, DJ. Best practices for disinfection of noncritical environmental surfaces and equipment in health care facilities: a bundle approach. Am J Infect Control 2019;47:A96A105.CrossRefGoogle Scholar
McBryde, ES, McElwain, DLS. A mathematical model investigating the impact of an environmental reservoir on the prevalence and control of vancomycin-resistant enterococci. J Infect Dis 2006;193:14731474.CrossRefGoogle ScholarPubMed
Perencevich, EN, Fisman, DN, Lipsitch, M, Harris, AD, Morris, JG, Smith, DL. Projected benefits of active surveillance for vancomycin-resistant enterococci in intensive care units. Clin Infect Dis 2004;38:11081115.CrossRefGoogle ScholarPubMed
Niewiadomska, AM, Jayabalasingham, B, Seidman, JC, et al. Population-level mathematical modeling of antimicrobial resistance: a systematic review. BMC Med 2019;17:81.CrossRefGoogle ScholarPubMed
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