Laboratory-based prospective surveillance for community outbreaks of Shigella spp. in Argentina

Abstract

Background: To 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.

Methodology: To 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 findings: In 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/significance: The 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.

Figure 1. Geographic distribution of laboratories including in this study.

The 23 participating laboratories of six provinces of Argentina are indicated with a green circle : 11 hospitals in the three contiguous provinces HAC, BAR, HAZ and HGR from Río Negro province (RN); HLM, HGC from La Pampa province (LP); HHH, NEU, HJA, HNB, SMA from Neuquén province (NEU); and with a red circle: 12 additional hospitals from the three additional contiguous provinces: PJC, RFB, IMC, HST, VIL, HDF and VSW from Córdoba province; PVM and HSL of San Luis province and H09, NOT and HTS from Mendoza province.

Figure 2. Dendrogram showing the genetic relatedness of isolates of S. flexneri 2 included in Event 1 and 6.

Isolates recovered in Santa Rosa, La Pampa (Event 1 and 6), and selected isolates for comparison, including one from an outbreak in San Luis and three from sporadic cases in 2009. The rectangle highlights isolates of S. flexneri 2 recovered in March–April 2009 (Event 1) and October–November 2009 (Event 6).

Figure 3. Dendrogram showing the genetic relatedness of S. sonnei SXT resistant isolates included in the Event 7.

Isolates recovered in Santa Rosa, La Pampa in January – February 2010. The rectangle highlights the 7 S. sonnei isolates with an indistinguishable PFGE pattern which had not previously been recorded in the National Data Base (NDB). The remaining 7 isolates identified statistically and epidemiologically as part of Event 7, exhibited high genetic relatedness (from 91.4 to 97.4% similarity, 1 to 3 bands of difference) to the most frequent pattern within the event, confirming the relation of the cases.

Figure 4. Time series of cases of Shigella sonnei isolates detected by SaTScan programme from December 2009 to March 2010.

The rectangle highlights the time series of cases corresponding to the detection and evolution of Event 7.