动态网络用于精确确定传染病爆发前的阶段
Qibin Song1, Haoming Zhang1, Yanping Jiang1
1Foshan University, Foshan, Guangdong, People's Republic of China.
Journal of the Royal Society, Interface
|August 19, 2025
概括
一种新的计算方法,动态网络 (DNE),有效地识别了传染病爆发的早期预警信号. 这种方法可以提前几周预测流感和HFMD等疫情,改善公共卫生监测.
科学领域:
- 计算流行病学计算流行病学
- 公共卫生监督是对公共卫生的监督.
- 网络科学 网络科学
背景情况:
- 传染病爆发对人类健康和经济构成重大威胁.
- 早期检测和干预对于疫情控制至关重要.
- 由于复杂的生物和社会动态,对传染病传播的实时预测仍然具有挑战性.
研究的目的:
- 开发一种新的计算方法,用于传染病爆发的早期预警信号.
- 准确识别流感和手足口病 (HFMD) 等疾病的爆发前阶段.
- 提高公共卫生监测系统的及时性和准确性.
主要方法:
- 开发一个动态网络 (DNE) 计算方法.
- 基于医院访问记录的城市网络的建设.
- 利用高维,动态数据进行信号检测.
主要成果:
- 该DNE方法准确地识别了流感和HFMD的爆发前信号.
- 早期预警信号至少在6周 (流感) 和5周 (HFMD) 之前爆发.
- 与现有方法相比,该方法在确定关键警告信号方面表现优越.
结论:
- DNE方法提供了一种创新的策略,用于识别传染病的爆发前阶段.
- 这种方法在改善实时公共卫生监测方面具有重大潜力.
- 利用动态网络信息可以在灾难性流行病过渡之前进行预测.
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