探索冠状病毒疾病2019年风险因素:一个文本网络分析方法
1Department of Nursing, Keimyung College University, Daegu 42601, Republic of Korea.
Journal of clinical medicine
|March 27, 2025
概括
文字网络分析确定了严重COVID-19的关键风险因素,包括年龄和高血压. 随着时间的推移,研究重点从急性症状转向长期COVID和疫苗疗效.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 数据科学数据科学数据科学
背景情况:
- COVID-19 疫情深刻影响了全球健康和社会.
- 了解影响COVID-19传播和严重程度的因素至关重要.
研究的目的:
- 通过使用文本网络分析,分析严重COVID-19风险因素之间的相互联系.
- 为了跟踪疫情期间研究重点的演变.
主要方法:
- 已发表研究的文本网络分析 (2020年1月至2021年12月).
- 确定关键决定因素,如年龄,高血压和并发症.
- 研究主题的时间趋势分析.
主要成果:
- 确定了五个风险因素集群:生物医学,职业,人口,行为和并发症相关.
- 早期的研究重点是急性COVID-19的临床特征.
- 后来的研究强调了长期的COVID,生活质量,以及针对变种 (Alpha,Delta,Omicron) 的疫苗有效性.
结论:
- 调查结果为高风险群体提供了针对性公共卫生干预措施的见解.
- 文本网络分析是合成复杂的流行病数据的宝贵工具.
- 支持基于证据的决策,为流行病做好准备和应对.
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