Aharona Glatman-Freedman1, Zalman Kaufman2, Eran Kopel3, Ravit Bassal2, Diana Taran4, Lea Valinsky5, Vered Agmon5, Manor Shpriz3, Daniel Cohen6, Emilia Anis3, Tamy Shohat7. 1. Infectious Diseases Unit, Israel Center for Disease Control, Tel-Hashomer, Israel; Department of Pediatrics, New York Medical College, Valhalla, NY, USA; Department of Family and Community Medicine, New York Medical College, Valhalla, NY, USA. Electronic address: Aharona.Freedman@MOH.HEALTH.GOV.IL. 2. Infectious Diseases Unit, Israel Center for Disease Control, Tel-Hashomer, Israel. 3. Division of Epidemiology, Ministry of Health, Jerusalem, Israel. 4. Maccabi Healthcare Services, Tel-Aviv, Israel. 5. Government Central Laboratories, Ministry of Health, Jerusalem, Israel. 6. School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel. 7. Infectious Diseases Unit, Israel Center for Disease Control, Tel-Hashomer, Israel; School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.
Abstract
OBJECTIVES: To enhance timely surveillance of bacterial enteric pathogens, space-time cluster analysis was introduced in Israel in May 2013. METHODS: Stool isolation data of Salmonella, Shigella, and Campylobacter from patients of a large Health Maintenance Organization were analyzed weekly by ArcGIS and SaTScan, and cluster results were sent promptly to local departments of health (LDOHs). RESULTS: During eighteen months, we identified 52 Shigella sonnei clusters, two Salmonella clusters, and no Campylobacter clusters. S. sonnei clusters lasted from one to 33 days and included three to 30 individuals. Thirty-one (60%) of the S. sonnei clusters were known to LDOHs prior to cluster analysis. Clusters not previously known by the LDOHs prompted epidemiologic investigations. In 31 of the 37 (84%) confirmed clusters, educational institutes (nursery schools, kindergartens, and a primary school) were involved. CONCLUSIONS: Cluster analysis demonstrated capability to complement enteric disease surveillance. Scaling up the system can further enhance timely detection and control of outbreaks.
OBJECTIVES: To enhance timely surveillance of bacterial enteric pathogens, space-time cluster analysis was introduced in Israel in May 2013. METHODS: Stool isolation data of Salmonella, Shigella, and Campylobacter from patients of a large Health Maintenance Organization were analyzed weekly by ArcGIS and SaTScan, and cluster results were sent promptly to local departments of health (LDOHs). RESULTS: During eighteen months, we identified 52 Shigella sonnei clusters, two Salmonella clusters, and no Campylobacter clusters. S. sonnei clusters lasted from one to 33 days and included three to 30 individuals. Thirty-one (60%) of the S. sonnei clusters were known to LDOHs prior to cluster analysis. Clusters not previously known by the LDOHs prompted epidemiologic investigations. In 31 of the 37 (84%) confirmed clusters, educational institutes (nursery schools, kindergartens, and a primary school) were involved. CONCLUSIONS: Cluster analysis demonstrated capability to complement enteric disease surveillance. Scaling up the system can further enhance timely detection and control of outbreaks.
Authors: Chris Edens; Nisha B Alden; Richard N Danila; Mary-Margaret A Fill; Paul Gacek; Alison Muse; Erin Parker; Tasha Poissant; Patricia A Ryan; Chad Smelser; Melissa Tobin-D'Angelo; Stephanie J Schrag Journal: PLoS One Date: 2019-05-30 Impact factor: 3.240
Authors: Ashenafi Zebene Woldaregay; Ilkka Kalervo Launonen; Eirik Årsand; David Albers; Anna Holubová; Gunnar Hartvigsen Journal: J Med Internet Res Date: 2020-08-12 Impact factor: 5.428