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High-throughput Detection Method for Influenza Virus
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数字健康应用程序是否可以作为流感监测系统的补充?
Jia Chen1, Feifei Bao1, Huiyao Sun1
1Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China.
Studies in health technology and informatics
|January 25, 2024
概括
通过将实时搜索查询与历史流感类疾病 (ILI) 数据相结合,可以预测中国的季节性流感趋势. 这种数字健康方法为传统的监测系统提供了及时的补充.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 数字健康数字健康
背景情况:
- 季节性流感在中国构成了重大公共卫生挑战.
- 传统的流感监测系统在实时数据采集方面存在局限性.
研究的目的:
- 评估将数字健康数据与传统监测相结合的有效性,以预测流感趋势.
- 评估预测流感类疾病 (ILI) 趋势的及时性和准确性.
主要方法:
- 从疾病预防控制中心收集历史流感样疾病 (ILI%) 数据.
- 利用来自数字健康应用程序的健康查询数据.
- 结合实时LI相关搜索查询与滞后的ILI%数据 (一周前).
主要成果:
- 综合方法准确地预测了ILI趋势.
- 预测是及时实现的.
- 数字健康数据在补充传统监测方面被证明是有效的.
结论:
- 将实时搜索查询与历史ILI数据相结合,可以更好地预测流感趋势.
- 数字健康应用程序为中国现有的流感监测提供了有价值的补充.
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