BackgroundTo implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012.MethodologyTo detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols.Principal FindingsIn three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities.Conclusions/SignificanceThe WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other networks, and scaled up to national and international levels for early detection and control of outbreaks.
Shigella flexneri is a major health problem in developing countries. There are 19 serotypes recognized based on O-antigen structure and its typing is important for epidemiological purposes. However, the diversity of serotypes and the difficulties presented by phenotypic serotyping, for example, unavailable antisera for less common antigens, require the implementation of molecular techniques. In this study, we developed two multiplex PCR assays targeting the O-antigen synthesis genes and the O-antigen modification genes, for the rapid identification of S. flexneri serotypes 1/7, 2, 4, 5, and 6 (PCR A) and serotype 7 and group antigenic factors (3,4; 6; 7,8; E1037) (PCR B). A total of 73 S. flexneri strains representing 18 serotypes, except serotype 1d, were used in the study. Specific amplification patterns were obtained for each of the different serotypes. All strains tested had concordant results with phenotypic and genotypic serotyping; therefore, its implementation in the microbiology clinical laboratory will significantly improve S. flexneri serotyping.
Shigella flexneri is divided into 13 serotypes based on the combination of antigenic determinants present in the O-antigen. A new O-antigen modification with phosphoethanolamine has been identified. The presence of this antigenic determinant (called E1037) is recognized by monoclonal antibody MASF IV-1. Given the increasing incidence of these new variants and the difficulty in supplying the monoclonal antibody to our country, we produced a polyclonal antiserum (AA479) through immunization with a S. flexneri Xv strain. The antiserum specificity was assessed by slide agglutination against isolates from clinical cases and a culture collection representing all Shigella serotypes. The results obtained demonstrated a 100% correlation between AA479 absorbed antiserum and monoclonal antibody MASF IV-1. The availability of AA479 antiserum in every public hospital in Argentina will allow us to identify atypical S. flexneri isolates in order to strengthen Shigella surveillance in our country and to compare with global epidemiological data.
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