基于大规模社交媒体数据的新型冠状病毒肺炎症状趋势及共现网络研究卡塔尔世界杯8强波胆分析信息监测研究%吴a，王嘉庚%，王璐敏%，华璐敏%，李义宁%，周明辉%，李%，贝茨%，David W %，杨洁%+浙江大学医学院公共卫生学院及第二附属医院，杭州余杭堂路866号，中国，310058,86 057187077982,jieynlp@gmail.com %K社交媒体%K网络分析%K公共卫生%K数据挖掘%K COVID-19 %D 2023 %7 14.3.2023 %9原创论文%J J Med Internet Res %G English %X对于COVID-19等突发大流行，由于无症状或轻症状感染的比例很高，因此基于医院数据的症状统计可能存在偏差或延迟。同时，大规模临床数据的难以获取也限制了很多研究者进行及时的研究。目的:考虑到社交媒体覆盖面广、及时性强的特点，本研究旨在通过大规模、长期的社交媒体数据，提供一种高效的工作流来跟踪和可视化新冠肺炎大流行的动态特征和症状共现情况。方法:本回顾性研究纳入了2020年2月1日至2022年4月30日期间与covid -19相关的471,553,966条推文。我们为社交媒体策划了一个分层症状词典，其中包含10个受影响的器官/系统，257个症状和1808个同义词。从每周新发病例、报告症状总体分布和时间流行等方面分析新冠肺炎症状随时间的动态特征。通过比较两种病毒株优势期的症状流行情况，探讨两种病毒株的症状演变。一个共现症状网络被开发和可视化，以调查症状和受影响的身体系统之间的内在关系。 Results: This study identified 201 COVID-19 symptoms and grouped them into 10 affected body systems. There was a significant correlation between the weekly quantity of self-reported symptoms and new COVID-19 infections (Pearson correlation coefficient=0.8528; P<.001). We also observed a 1-week leading trend (Pearson correlation coefficient=0.8802; P<.001) between them. The frequency of symptoms showed dynamic changes as the pandemic progressed, from typical respiratory symptoms in the early stage to more musculoskeletal and nervous symptoms in the later stages. We identified the difference in symptoms between the Delta and Omicron periods. There were fewer severe symptoms (coma and dyspnea), more flu-like symptoms (throat pain and nasal congestion), and fewer typical COVID symptoms (anosmia and taste altered) in the Omicron period than in the Delta period (all P<.001). Network analysis revealed co-occurrences among symptoms and systems corresponding to specific disease progressions, including palpitations (cardiovascular) and dyspnea (respiratory), and alopecia (musculoskeletal) and impotence (reproductive). Conclusions: This study identified more and milder COVID-19 symptoms than clinical research and characterized the dynamic symptom evolution based on 400 million tweets over 27 months. The symptom network revealed potential comorbidity risk and prognostic disease progression. These findings demonstrate that the cooperation of social media and a well-designed workflow can depict a holistic picture of pandemic symptoms to complement clinical studies. %M 36812402 %R 10.2196/45419 %U //www.mybigtv.com/2023/1/e45419 %U https://doi.org/10.2196/45419 %U http://www.ncbi.nlm.nih.gov/pubmed/36812402