Groeneveld Geert H, Dalhuijsen Anton, Kara-Zaïtri Chakib, Hamilton Bob, de Waal Margot W, van Dissel Jaap T, van Steenbergen Jim E
Department of Internal Medicine and Infectious Diseases, Leiden University Medical Center, P.O. box 9600, 2300 RC, Leiden, The Netherlands.
Unit for Infectious Disease Control, Public Health Service Hollands Midden, Leiden, The Netherlands.
BMC Infect Dis. 2017 Mar 9;17(1):201. doi: 10.1186/s12879-017-2300-5.
Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika virus outbreak.
In the Netherlands, ICARES (Integrated Crisis Alert and Response System) has been developed and tested on three syndromes as an automated, real-time tool for early detection of clusters of infectious diseases. From local general practices, General Practice Out-of-Hours services and a hospital, the numbers of routinely used syndrome codes for three piloted tracts i.e., respiratory tract infection, hepatitis and encephalitis/meningitis, are sent on a daily basis to a central unit of infectious disease control. Historic data combined with information about patients' syndromes, age cohort, gender and postal code area have been used to detect clusters of cases.
During the first 2 years, two out of eight alerts appeared to be a real cluster. The first was part of the seasonal increase in Enterovirus encephalitis and the second was a remarkably long lasting influenza season with high peak incidence.
This tool is believed to be the first flexible automated, real-time cluster detection system for infectious diseases, based on physician information from both general practitioners and hospitals. ICARES is able to detect and follow small regional clusters in real time and can handle any diseases entity that is regularly registered by first line physicians. Its value will be improved when more health care institutions agree to link up with ICARES thus improving further the signal-to-noise ratio.
传染病聚集性病例往往发现得较晚。对于地方政策制定者、计划前往该地区的旅行者以及当地居民而言，获取有关正在演变的聚集性病例及可能相关情况的实时详细信息至关重要。寨卡病毒疫情便是当前的一个例证。
在荷兰，已开发出ICARES（综合危机警报与应对系统）并针对三种综合征进行了测试，作为一种用于早期发现传染病聚集性病例的自动化实时工具。来自当地全科诊所、全科诊所非工作时间服务机构以及一家医院的三种试点疾病（即呼吸道感染、肝炎和脑炎/脑膜炎）的常规使用综合征代码数量每天被发送至传染病控制中心。利用历史数据以及有关患者综合征、年龄组、性别和邮政编码区域的信息来检测病例聚集情况。
在最初的两年中，八个警报中有两个似乎是真正的聚集性病例。第一个是肠道病毒脑炎季节性增加的一部分，第二个是流感季节持续时间极长且发病率峰值很高。
该工具被认为是首个基于来自全科医生和医院的医生信息的灵活的传染病自动化实时聚集性病例检测系统。ICARES能够实时检测并跟踪小范围的区域聚集性病例，并且能够处理一线医生常规登记的任何疾病实体。当更多的医疗机构同意与ICARES建立联系从而进一步提高信噪比时，其价值将得到提升。
