Laboratory-Based Prospective Surveillance for Community Outbreaks of Shigella spp. in Argentina
Laboratory-Based Prospective Surveillance for Community Outbreaks of Shigella spp. in Argentina
复制标题
DOI：
10.1371/journal.pntd.0002521
复制
发表时间：
2013-12-01
影响因子：
3.8
通讯作者：
Galas, Marcelo
中科院分区：
文献类型：
--
作者：
Vinas, Maria R.;Tuduri, Ezequiel;Galas, Marcelo
为了实施有效的控制措施，及时发现疫情至关重要。志贺氏菌是阿根廷细菌性腹泻最常见的病因。已经出现了具有高度耐药性的志贺氏菌克隆，并在封闭环境和整个社区中发现了疫情。我们在此报告2009年4月至2012年3月期间在阿根廷六个相邻省份运行的不断发展的、综合的、基于实验室的近实时监测系统的经验。方法采用WHONET软件中嵌入的SaTScan前瞻性时空排列扫描统计算法，及时发现局部志贺氏菌病暴发。23个实验室每周向国家参考实验室发送最新的志贺氏菌数据。在几个分类水平上进行了聚类检测分析：对所有志贺氏菌属、种内血清型和种内抗菌素耐药表型进行了聚类检测分析。采用脉冲场凝胶电泳（PFGE）技术，采用脉冲场凝胶电泳技术（PulseNet）对具有统计学意义信号（复发间隔365天的时间/空间簇）相关的志贺氏菌分离株进行分型。在三年的主动监测中，我们的系统发现了32起具有统计学意义的事件，其中26起是在医院工作人员意识到志贺氏菌分离株数量意外增加之前发现的。PFGE检测了26个信号，其中22个事件（84.6%）的分离株之间存在密切关系。从流行病学角度调查了七个事件，揭示了患者之间的联系。在抗性水平上发现了17个事件。该系统发现了具有公共卫生重要性的事件：罕见的耐药性概况、长期和/或重新出现的群集以及就其持续时间或规模而言具有重要意义的事件，并向地方公共卫生当局报告。whoonet - satscan系统可作为一种监测模式，可应用于其他病原体，由其他网络实施，并扩大到国家和国际层面，以便及早发现和控制疫情。志贺氏菌病引起痢疾，全世界每年约有110万人因志贺氏菌病死亡，其中60%为5岁以下儿童。传染媒介是志贺氏菌，通过粪口途径或通过摄入受污染的食物或水在人与人之间传播。拥有一个及早发现疫情的系统对于实施控制措施将非常有用，这些措施有助于减少受影响患者的数量、减少经济损失并防止抗菌素耐药性的传播。我们介绍了在免费的SaTScan软件中实施的时空排列扫描统计在阿根廷六个省的志贺氏菌病例实验室监测中的应用。在2009年4月至2012年3月期间，对6个省载入世界卫生组织网络数据库（世界范围内使用的电子实验室数据系统）的数据应用了SaTScan。该项目查明了32起事件，包括因其持续时间或受影响患者人数而具有特别公共卫生重要性的几起事件。它还加强了实验室和流行病学工作人员之间的关系。总之，将世卫网络实验室数据与SaTScan分析相结合，可以及时发现重要的耐药志贺菌病社区暴发，从而对公共卫生产生影响。
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.Author Summary Shigellosis causes dysentery and kills an estimated 1.1 million people per year worldwide, 60% of them children under the age of 5. The infectious agent is Shigella spp, transmitted from person to person by fecal-oral route or via ingestion of contaminated food or water. Having a system for early detection of outbreaks would be very useful for implementing control measures that help reduce the number of affected patients, economic losses and prevent the dissemination of antimicrobial resistance. We present the application of a space-time permutation scan statistic implemented within the free SaTScan software for laboratory based surveillance of Shigella cases in six provinces from Argentina. SaTScan was applied on the data loaded into WHONET databases (an electronic laboratory data system used world-wide) in the six provinces from April 2009 to March 2012. The project allowed the identification of 32 events, including several of particular public health importance for their duration or number of affected patients. It also strengthened the relationship between the laboratory and epidemiology staff. In conclusion, the combination of WHONET laboratory data and SaTScan analysis can detect important community outbreaks of antimicrobial-resistant shigellosis in a timely manner, to make a difference to public health.