文章基本信息

标题：Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis — New York City, May–June 2019
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作者：Julia Latash ; Sharon K. Greene ; Faina Stavinsky 等
期刊名称：Morbidity and Mortality Weekly Report
出版年度：2020
卷号：69
期号：26
页码：815-819
DOI：10.15585/mmwr.mm6926a2
出版社：Centers for Disease Control and Prevention
摘要：What is already known about this topic? Whole genome sequencing (WGS) improves detection of foodborne outbreaks caused by contaminated products. However, detecting geographically focal outbreaks can be delayed pending WGS results, and public health laboratory capacity limitations might preclude sequencing of all Salmonella isolates. What is added by this report? Through daily automated spatiotemporal analysis of notifiable diseases, a salmonellosis outbreak in New York City was detected 9 days before availability of serotyping results. Early detection primed investigators to look for common exposures and facilitated rapid environmental assessments, leftover food collection, and prioritization of isolates for subtyping. What are the implications for public health practice? Along with laboratory subtyping results, public health officials can use spatiotemporal cluster detection analyses to prioritize investigations.
关键词：Salmonellosis Outbreak New York City;Cluster Detection Foodborne Illness;Salmonella Outbreak Automated Spatiotemporal Analysis;Food Poisoning New York City;Salmonella Outbreak Cluster Detection;Salmonella;Outbreaks;Food Safety;MMWR;Morbidity & Mortality Weekly Report