lunes, 20 de julio de 2015

Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France - Volume 21, Number 8—August 2015 - Emerging Infectious Disease journal - CDC

full-text ►

Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France - Volume 21, Number 8—August 2015 - Emerging Infectious Disease journal - CDC

Volume 21, Number 8—August 2015


Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France

Cédric Abat, Hervé Chaudet, Philippe Colson, Jean-Marc Rolain, and Didier RaoultComments to Author 
Author affiliations: Aix-Marseille Université, Marseille, France (C. Abat, P. Colson, J.-M. Rolain, D. Raoult);Sciences Economiques et Sociales de la Santé et Traimtement de l’Information Médicale (SESSTIM), Marseille (H. Chaudet)


Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data–based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved.
Although infectious diseases were declared under control and considered to be a past public health problem during the second half of the 20th century (1), these diseases, including those that are well-known, emerging, and reemerging, remain a major threat to humanity. Indeed, infectious pathogens possess an amazing common capacity to emerge and spread in unpredictable ways before they are detected by public health institutions (2). Infectious diseases have a substantial effect on both global human demographics (they are the second leading cause of death in humans worldwide, accounting for ≈15 million deaths) (3) and the economy (4), which has led the public health community to reconsider them as a real threat. This alarming observation has led public health authorities to try to improve infectious disease surveillance.
One of these strategies, known as traditional public health surveillance of infectious diseases, has been to use clinical case reports from sentinel laboratories or laboratory networks and direct reports of positive results from clinical laboratories to survey the presence of microbial agents known to be dangers to health in a precise population (5). Some examples of surveillance systems implemented by using this strategy are the National Tuberculosis Surveillance System in the United States (6), the surveillance system of the Netherlands Reference Laboratory for Bacterial Meningitis (7) and the European Gonococcal Antimicrobial Surveillance Programme (8).
Another strategy, known as syndromic surveillance, consists of developing real-time surveillance systems capable of detecting abnormal epidemiologic events, not on the basis of infectious disease diagnosis data, but rather on the basis of nonspecific health indicators, such as absenteeism, chief complaints, and prescription drug sales (5,9). Such surveillance systems can be implemented nationally, such as the Emergency Department Syndromic Surveillance System in England (10) or the National Retail Data Monitor in the United States (11), and regionally, such as the Emergency Department Syndromic Surveillance in Canada (12) or the European Antimicrobial Resistance Surveillance Network in Europe (13), or the systems can be administered by laboratories with large quantities of data and the financial and human resources to apply the information.
On the basis of our experience at the Assistance Publique–Hôpitaux de Marseille (AP-HM), we describe all the steps necessary for implementing a laboratory data–based syndromic surveillance system in a laboratory. Because of its simplicity, we believe that it can be rapidly applied and used as a first surveillance tool in well-established laboratories. We also show the advantages and limits of this surveillance system.
Mr. Abat is a PhD student at the Institut Hospitalo-Universitaire Méditerranée Infection, Aix-Marseille Université. His research interest is the implementation of computer tools for real-time epidemiologic surveillance of abnormal events based on clinical microbiology laboratory data.


We thank American Journal Experts for English corrections.
This work was partly funded by the Centre National de la Recherche Scientifique and the Institut Hospitalo–Universitaire Méditerranée Infection.


  1. Raoult D. Les causes de l'émergence des agents infectieux. Responsabilité et Environnement. 2008;51:21–5.
  2. Raoult D. Molecular, epidemiological, and clinical complexities of predicting patterns of infectious diseases. Front Microbiol. 2011;2:25. PubMed
  3. Morens DMFolkers GKFauci ASThe challenge of emerging and re-emerging infectious diseases. Nature2004;430:2429 and. DOIPubMed
  4. Jones KEPatel NGLevy MAStoreygard ABalk DGittleman JLGlobal trends in emerging infectious diseases. Nature2008;451:9903.DOIPubMed
  5. Zeng DChen HCastillo-Chavez CThurmond M. Clinical laboratory data for biosurveillance. In: Zeng D., Chen H., Castillo-Chavez C., Lober W.B., Thurmond M., editors. Infectious disease informatics and biosurveillance. New York: Springer; 2011. p. 67–87.
  6. Vinnard CWinston CAWileyto EPMacgregor RRBisson GPIsoniazid resistance and death in patients with tuberculous meningitis: retrospective cohort study. BMJ2010;341:c4451DOIPubMed
  7. van Wessel KRodenburg GDVeenhoven RHSpanjaard Lvan der Ende ASanders EANontypeable Haemophilus influenzae invasive disease in The Netherlands: a retrospective surveillance study 2001–2008. Clin Infect Dis2011;53:e17 . DOIPubMed
  8. Cole MJUnemo MHoffmann SChisholm SAIson CAvan de Laar MJThe European gonococcal antimicrobial surveillance programme, 2009. Euro Surveill2011;16:19995 .PubMed
  9. Sala Soler MFouillet AViso ACJosseran LSmith GEElliot AJAssessment of syndromic surveillance in Europe. Lancet2011;378:18334.DOIPubMed
  10. Severi EHeinsbroek EWatson CCatchpole MInfectious disease surveillance for the London 2012 Olympic and Paralympic Games. Euro Surveill.2012;17:20232 .PubMed
  11. Castillo-Salgado CTrends and directions of global public health surveillance. Epidemiol Rev2010;32:93109DOIPubMed
  12. van Dijk AAramini JEdge GMoore KMReal-time surveillance for respiratory disease outbreaks, Ontario, Canada. Emerg Infect Dis.2009;15:799801DOIPubMed
  13. Magiorakos APSuetens CMonnet DLGagliotti CHeuer OE. The rise of carbapenem resistance in Europe: just the tip of the iceberg? Antimicrob Resist Infect Control. 2013;2:6.
  14. Colson PGouriet FBadiaga STamalet CStein ARaoult DReal-time laboratory surveillance of sexually-transmissible infections in Marseille University hospitals reveals rise of gonorrhoea, syphilis and human immunodeficiency virus seroconversions in 2012. Euro Surveill2013;18:4.PubMed
  15. Parola PColson PDubourg GMillion MCharrel RMinodier PGroup A streptococcal infections during the seasonal influenza outbreak 2010/11 in South East England. Euro Surveill2011;16:19815 .PubMed
  16. Kempf MRolain JMAzza SDiene SJoly-Guillou MLDubourg GInvestigation of Acinetobacter baumannii resistance to carbapenems in Marseille hospitals, south of France: a transition from an epidemic to an endemic situation. APMIS2013;121:6471DOIPubMed
  17. Seng PAbat CRolain JMColson PLagier JCGouriet FIdentification of rare pathogenic bacteria in a clinical microbiology laboratory: impact of matrix-assisted laser desorption ionization–time of flight mass spectrometry. J Clin Microbiol2013;51:218294DOIPubMed
  18. Calain PFrom the field side of the binoculars: a different view on global public health surveillance. Health Policy Plan2007;22:1320.DOIPubMed
  19. Lagier JCDubourg GCassir NFournier PEColson PRichet HClostridium difficile 027 emerging outbreak in Marseille, France. Infect Control Hosp Epidemiol2013;34:133941DOIPubMed
  20. Kronenberg AHilty MEndimiani AMuhlemann KTemporal trends of extended-spectrum cephalosporin-resistant Escherichia coli and Klebsiella pneumoniae isolates in in- and outpatients in Switzerland, 2004 to 2011. Euro Surveill2013;18:20284 .PubMed
  21. Silva JCShah SCRumoro DPBayram JDHallock MMGibbs GSComparing the accuracy of syndrome surveillance systems in detecting influenza-like illness: GUARDIAN vs. RODS vs. electronic medical record reports. Artif Intell Med2013;59:16974DOIPubMed
  22. Chaudet HAnceaux FBeuscart MCPelayo SPellegrin L. Facteurs humains et ergonomie en informatique médicale. In: Venot A, Burgun A, Quantin C, editors. Informatique médicale, e-santé—fondements et applications. New York: Springer; 2013. p. 495–520.
  23. Meyer EJonas DSchwab FRueden HGastmeier PDaschner FDDesign of a surveillance system of antibiotic use and bacterial resistance in German intensive care units (SARI). Infection2003;31:20815 .PubMed
  24. Meyer ESchwab FSchroeren-Boersch BGastmeier PDramatic increase of third-generation cephalosporin-resistant E. coli in German intensive care units: secular trends in antibiotic drug use and bacterial resistance, 2001 to 2008. Crit Care2010;14:R113DOIPubMed
  25. Das DWeiss DMostashari FTreadwell TMcQuiston JHutwagner LEnhanced drop-in syndromic surveillance in New York City following September 11, 2001. J Urban Health2003;80(Suppl 1):i7688 .PubMed
  26. Enki DGNoufaily AGarthwaite PHAndrews NJCharlett ALane CAutomated biosurveillance data from England and Wales, 1991–2011. Emerg Infect Dis2013;19:3542DOIPubMed



Suggested citation for this article: Abat C, Chaudet H, Colson P, Rolain JM, Raoult D. Real-time microbiology laboratory surveillance system to detect abnormal events and emerging infections, Marseille, France. Emerg Infect Dis. 2015 Aug [date cited].
DOI: 10.3201/eid2108.141419

No hay comentarios:

Publicar un comentario