COVID-19 期间美国疾病控制和预防中心社交媒体内容与流行病措施之间的动态关联:信息监控研究。

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2024-01-23 DOI:10.2196/49756
Shuhua Yin, Shi Chen, Yaorong Ge
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引用次数: 0

摘要

背景:卫生机构已广泛采用社交媒体来传播重要信息、就新出现的健康问题教育公众并了解公众意见。在 COVID-19 大流行期间,美国疾病控制和预防中心(CDC)广泛使用社交媒体平台与公众沟通并缓解疫情。了解疾病预防控制中心的社交媒体传播与实际疫情指标之间的关系对于改善公共卫生机构在卫生突发事件中的传播策略至关重要:本研究旨在确定疾病预防控制中心在疫情期间发布的推文中的关键话题,调查这些关键话题与 COVID-19 实际疫情指标之间的时间动态关系,并为疾病预防控制中心未来的突发卫生事件数字健康传播策略提出建议:收集了两类数据:(1)2019 年 12 月 7 日至 2022 年 1 月 15 日期间中国疾病预防控制中心发布的与 COVID-19 相关的英文推文共计 17524 条;(2)2020 年 1 月至 2022 年 7 月期间约翰霍普金斯大学公共 GitHub 存储库中的美国 COVID-19 流行措施。采用潜在德里希勒分配主题模型从美国疾病预防控制中心发布的所有 COVID-19 相关推文中识别关键主题,最终主题由领域专家确定。在每个确定的关键主题和实际的 COVID-19 流行指标之间应用了各种多元时间序列分析技术,以量化这两类时间序列数据之间的动态关联:从疾病预防控制中心的 COVID-19 推文中确定了四个主要议题:(1) 有关预防 COVID-19 健康后果的信息;(2) 儿科干预和家庭安全;(3) COVID-19 流行情况的更新;(4) 遏制 COVID-19 的研究和社区参与。多变量分析表明,疾病预防控制中心的主题与 COVID-19 实际流行情况之间存在显著的进展差异。在整个大流行期间的不同时间跨度内,疾病预防控制中心的一些主题与 COVID-19 的测量结果显示出实质性的关联,这表明这两类时间序列数据之间存在相似的时间动态:我们的研究首次全面调查了美国疾病预防控制中心在 Twitter 上讨论的话题与 COVID-19 流行病指标之间的动态关联。我们通过话题建模确定了 4 个主要话题主题,并通过各种多变量时间序列分析探讨了每个话题与每个主要流行病指标之间的关联。我们建议,对于疾病预防控制中心等公共卫生机构来说,及时向公众更新和传播准确的信息,并随着时间的推移使主要话题与关键流行病措施保持一致至关重要。我们建议,社交媒体可以帮助公共卫生机构向公众通报突发卫生事件并有效缓解这些事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Associations Between Centers for Disease Control and Prevention Social Media Contents and Epidemic Measures During COVID-19: Infoveillance Study.

Background: Health agencies have been widely adopting social media to disseminate important information, educate the public on emerging health issues, and understand public opinions. The Centers for Disease Control and Prevention (CDC) widely used social media platforms during the COVID-19 pandemic to communicate with the public and mitigate the disease in the United States. It is crucial to understand the relationships between the CDC's social media communications and the actual epidemic metrics to improve public health agencies' communication strategies during health emergencies.

Objective: This study aimed to identify key topics in tweets posted by the CDC during the pandemic, investigate the temporal dynamics between these key topics and the actual COVID-19 epidemic measures, and make recommendations for the CDC's digital health communication strategies for future health emergencies.

Methods: Two types of data were collected: (1) a total of 17,524 COVID-19-related English tweets posted by the CDC between December 7, 2019, and January 15, 2022, and (2) COVID-19 epidemic measures in the United States from the public GitHub repository of Johns Hopkins University from January 2020 to July 2022. Latent Dirichlet allocation topic modeling was applied to identify key topics from all COVID-19-related tweets posted by the CDC, and the final topics were determined by domain experts. Various multivariate time series analysis techniques were applied between each of the identified key topics and actual COVID-19 epidemic measures to quantify the dynamic associations between these 2 types of time series data.

Results: Four major topics from the CDC's COVID-19 tweets were identified: (1) information on the prevention of health outcomes of COVID-19; (2) pediatric intervention and family safety; (3) updates of the epidemic situation of COVID-19; and (4) research and community engagement to curb COVID-19. Multivariate analyses showed that there were significant variabilities of progression between the CDC's topics and the actual COVID-19 epidemic measures. Some CDC topics showed substantial associations with the COVID-19 measures over different time spans throughout the pandemic, expressing similar temporal dynamics between these 2 types of time series data.

Conclusions: Our study is the first to comprehensively investigate the dynamic associations between topics discussed by the CDC on Twitter and the COVID-19 epidemic measures in the United States. We identified 4 major topic themes via topic modeling and explored how each of these topics was associated with each major epidemic measure by performing various multivariate time series analyses. We recommend that it is critical for public health agencies, such as the CDC, to update and disseminate timely and accurate information to the public and align major topics with key epidemic measures over time. We suggest that social media can help public health agencies to inform the public on health emergencies and to mitigate them effectively.

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