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PulseNet Lebanon: An Overview of Its Activities, Outbreak Investigations, and Challenges
Sukayna M Fadlallah1, Marwa Shehab1, Katia Cheaito1
11 Department of Experimental Pathology, Immunology and Microbiology and Center for Infectious Diseases Research, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Abstract:
Foodborne diseases are still a major health issue in Lebanon, although some steps have been taken forward in food safety. To this purpose, PulseNet Lebanon, a foodborne diseases tracking network, was established in 2009, through the collaboration between the Ministry of Public Health (MoPH) and the American University of Beirut (AUB). Three papers published regarding the PulseNet project were summarized. Initially, clinical and food samples, collected within the surveillance network scope, were identified by using the respective API for Salmonella and Listeria spp. Salmonella spp. were further serotyped by using the Kauffman and White method. Campylobacter spp. were determined by the 16 S rRNA sequencing method. Antimicrobial susceptibility to a number of antibiotics was determined by using the disk diffusion method for Samonella and Campylobacter spp. Genomic diversity was determined by using pulsed field gel electrophoresis (PFGE) and random amplified polymorphic DNA (RAPD). Results indicated that 290 clinical and 49 food isolates were identified as Salmonella. Serotyping revealed the prevalence of ten and seven serotypes in the clinical and food samples, respectively. Fifty-one isolates from chicken ceca and carcass were identified to be Campylobacter spp. Fifty-nine samples were identified to be Listeria monocytogenes. Antimicrobial susceptibility testing revealed a wide range of resistance among the different samples. PFGE showed a variation in pulsotypes among the Salmonella serotypes. PFGE also linked certain outbreaks to their food sources. This method also demonstrated 13 subtypes with 100% similarity among the L. monocytogenes isolates. Finally, the Camplyobcater spp. were grouped into nine clusters with a minimum similarity of 43.5% using RAPD. This summary of results shows the importance of implementing a "farm-to-fork" approach in the surveillance of foodborne disease outbreaks in Lebanon, allowing the detection of pathogens causing foodborne disease outbreaks in a timely fashion.
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