Harnessing Tweets for Early Detection of an Acute Disease Event
Harnessing Tweets for Early Detection of an Acute Disease Event
复制标题
利用推文及早发现急性疾病事件
DOI：
10.1097/ede.0000000000001133
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发表时间：
2020-01-01
期刊：
影响因子：
5.4
通讯作者：
MacIntyre, C. Raina
中科院分区：
文献类型：
--
作者：
Joshi, Aditya;Sparks, Ross;MacIntyre, C. Raina
背景资料：澳大利亚墨尔本于2016年11月21日爆发雷暴哮喘，截至下午6点，导致8，000多人入院。这是一次典型的急性疾病事件。由于对急性疾病事件的反应时间很短，因此基于事件间隔时间的算法显示出了希望。疾病连续发生的时间越短，爆发的可能性就越大。社交媒体帖子（诸如推文）可以用作监测算法的输入。然而，由于大量的推文，可能会产生大量的警报。我们将此问题称为警报淹没。方法：我们提出了一个四步架构的急性疾病事件的早期检测，使用社交媒体帖子（推文）在Twitter上。为了抑制警报淹没，算法的前三步确保了推文的相关性。第四步是基于事件之间的时间的监视算法。我们对2014年至2016年在墨尔本发布的推文数据集进行了实验，重点关注2016年11月墨尔本爆发的雷暴哮喘。结果如下：在我们的18个实验组合中，有3个在官方报道中提到的时间之前9小时检测到雷暴哮喘爆发，5个能够在第一次新闻报道之前检测到。结论：通过对警报淹没进行适当的检查，并使用基于事件间隔时间的监控算法，推文可以为雷暴哮喘等急性疾病事件提供早期警报。
Background: Melbourne, Australia, witnessed a thunderstorm asthma outbreak on 21 November 2016, resulting in over 8,000 hospital admissions by 6 p.m. This is a typical acute disease event. Because the time to respond is short for acute disease events, an algorithm based on time between events has shown promise. Shorter the time between consecutive incidents of the disease, more likely the outbreak. Social media posts such as tweets can be used as input to the monitoring algorithm. However, due to the large volume of tweets, a large number of alerts may be produced. We refer to this problem as alert swamping. Methods: We present a four-step architecture for the early detection of the acute disease event, using social media posts (tweets) on Twitter. To curb alert swamping, the first three steps of the algorithm ensure the relevance of the tweets. The fourth step is a monitoring algorithm based on time between events. We experiment with a dataset of tweets posted in Melbourne from 2014 to 2016, focusing on the thunderstorm asthma outbreak in Melbourne in November 2016. Results: Out of our 18 experiment combinations, three detected the thunderstorm asthma outbreak up to 9 hours before the time mentioned in the official report, and five were able to detect it before the first news report. Conclusions: With appropriate checks against alert swamping in place and the use of a monitoring algorithm based on time between events, tweets can provide early alerts for an acute disease event such as thunderstorm asthma.