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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

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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

Synopsis

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)

Abstract

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.

Acknowledgments

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.

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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]. http://dx.doi.org/10.3201/eid2108.141419
DOI: 10.3201/eid2108.141419

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