Unit for Animals, Health, Territories, Risks and Ecosystems (UMR ASTRE), French Agricultural Research for Development (CIRAD), French National Institute for Agricultural Research (INRA), Montpellier, France.
Institute of Infection and Global Health (IGH), School of Veterinary Science, University of Liverpool, Liverpool, United Kingdom.
PLoS One. 2018 Aug 3;13(8):e0199960. doi: 10.1371/journal.pone.0199960. eCollection 2018.
Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.
自 2013 年以来,法国动物健康疫情情报系统(Veille Sanitaire Internationale,VSI)一直在监测全球新出现和外来动物传染病的信号。一旦发现信号,VSI 团队会进行核实,并在发现对法国存在潜在威胁时向法国动物卫生当局发布早期预警报告。为了提高对在线新闻来源信号的检测能力,我们设计了用于从网络自动提取疾病信息的平台(PADI-web)。PADI-web 自动从谷歌新闻中收集、处理和提取英文流行病学信息。PADI-web 的核心组件是一种基于规则系统和数据挖掘技术的综合信息提取(IE)方法。IE 方法允许提取新闻中疾病、地点、日期、宿主和病例数等关键信息。我们在一个包含 352 篇与疾病相关的新闻报道的数据集上评估了针对 IE 的综合方法,这些报道涉及疾病、地点、日期、宿主和病例数。IE 的综合方法准确地识别了 95%的疾病和宿主、85%的病例数、83%的日期和 80%的地点。我们评估了 PADI-web 检测世界动物卫生组织(OIE)通报的四种新发动物传染病原发性暴发的敏感性。2016 年 1 月至 6 月,PADI-web 检测到非洲猪瘟、禽流感、蓝舌病和口蹄疫原发性暴发的信号分别占所有原发性暴发的 64%、53%、25%和 19%。PADI-web 及时检测到亚洲的禽流感和口蹄疫原发性暴发,即分别比向 OIE 立即通报提前 8 天和 3 天。