Current Trends in Social-Media based Disease Outbreak Prediction & Surveillance Systems

Soofi Shafiya, S. Jabin
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Abstract

The purpose of disease surveillance is to monitor and predict public health emergencies or to predict outbreak of any disease. It can be achieved by analyzing disease related data being collected by various government agencies/hospitals. Public health officials keep track of information, predict possible outbreaks, and keep an eye on emergency situations using this data. In the recent past, social media has grown enough to have deep impact on people’s life specially during time of pandemic. Analysis of social media data offers meaningful insights towards disease surveillance. It helps in figuring out how much people know about diseases and how they feel about official/government health related communications and responses. In this study, we present review of most recent works which used social media as a data source for the prevention & prediction of outbreaks. Additionally, we discuss methods that are being implemented on social media data towards designing robust disease outbreak prediction models. This study emphasizes how social media has helped during various outbreaks in the past. A bibliometric analysis has also been done over the most recent & relevant literature collected from source SCOPUS.
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基于社交媒体的疾病爆发预测和监测系统的当前趋势
疾病监测的目的是监测和预测突发公共卫生事件或预测任何疾病的爆发。它可以通过分析各种政府机构/医院收集的疾病相关数据来实现。公共卫生官员利用这些数据跟踪信息,预测可能的疫情爆发,并密切关注紧急情况。最近,社交媒体已经发展到足以对人们的生活产生深刻影响,特别是在大流行期间。对社交媒体数据的分析为疾病监测提供了有意义的见解。它有助于弄清楚人们对疾病的了解程度,以及他们对官方/政府卫生相关沟通和反应的感受。在本研究中,我们回顾了最近使用社交媒体作为预防和预测疫情的数据源的工作。此外,我们还讨论了在社交媒体数据上实施的方法,以设计稳健的疾病爆发预测模型。这项研究强调了社交媒体在过去各种疫情爆发期间的作用。文献计量学分析也完成了从源SCOPUS收集的最新和相关文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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