Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource
Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource
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推特上的 COVID-19 症状自述：分析与研究资源
DOI：
10.1093/jamia/ocaa116
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发表时间：
2020-08-01
影响因子：
6.4
通讯作者：
Yang, Yuan-Chi
中科院分区：
文献类型：
--
作者：
Sarker, Abeed;Lakamana, Sahithi;Yang, Yuan-Chi
目的：挖掘Twitter并定量分析用户自述的COVID-19症状，比较各研究的症状分布，为未来的研究创建症状词典。材料与方法：我们使用新冠肺炎相关关键词检索推文，并进行半自动过滤，整理阳性用户的自我报告。我们提取了用户提到的covid -19相关症状，将其映射到统一医学语言系统中的标准概念id，并将其分布与临床环境中早期研究报告的分布进行了比较。结果：我们确定了203名阳性检测用户，他们使用668种独特表达报告了1002种症状。在报告至少一种症状的使用者中，最常报告的症状是发烧/发热（66.1%）、咳嗽（57.9%）、身体疼痛（42.7%）、疲劳（42.1%）、头痛（37.4%）和呼吸困难（36.3%）。轻微的症状，如嗅觉缺失（28.7%）和老年痴呆（28.1%），经常在Twitter上报道，但没有在临床研究中报道。结论：从推特上识别的COVID-19症状谱可能与临床环境中识别的症状谱相补充。
Objective: To mine Twitter and quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon for future research.Materials and Methods: We retrieved tweets using COVID-19-related keywords, and performed semiautomatic filtering to curate self-reports of positive-tested users. We extracted COVID-19-related symptoms mentioned by the users, mapped them to standard concept IDs in the Unified Medical Language System, and compared the distributions to those reported in early studies from clinical settings.Results: We identified 203 positive-tested users who reported 1002 symptoms using 668 unique expressions. The most frequently-reported symptoms were fever/pyrexia (66.1%), cough (57.9%), body ache/pain (42.7%), fatigue (42.1%), headache (37.4%), and dyspnea (36.3%) amongst users who reported at least 1 symptom. Mild symptoms, such as anosmia (28.7%) and ageusia (28.1%), were frequently reported on Twitter, but not in clinical studies.Conclusion: The spectrum of COVID-19 symptoms identified from Twitter may complement those identified in clinical settings.