网络流行病模型的模式形成及其在口腔医学中的应用
1School of Mathematical Sciences, Jiangsu University, Zhenjiang, PR China.
Computer methods and programs in biomedicine
|March 8, 2025
概括
这项研究引入了易受感染-康复 (SIR) 模型,在网络上出现疾病复发. 复发率的增加加剧了传染病的传播,影响了公共卫生战略.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 网络科学 网络科学
背景情况:
- 预防和控制传染病是关键的公共安全问题.
- 复杂的网络环境和疾病复发显著影响流行病的动态.
研究的目的:
- 建立和分析一种可感-感染-恢复 (SIR) 流行病模型,将疾病在连续空间和网络环境中的复发纳入其中.
- 调查各种网络结构中传染病模型的图灵模式,最佳控制和参数识别.
主要方法:
- 在同质和异质网络上分析疾病平衡和图灵不稳定的条件.
- 用目标模式的最佳控制理论推导全球最佳参数解决方案.
- 数字模拟和公共COVID-19数据的拟合以验证模型.
主要成果:
- 疾病复发率的增加导致感染人口的增加和恢复人口的减少.
- 复杂的网络模型准确地模拟了传染病传播动态.
- 模型预测与公共COVID-19数据中观察到的趋势保持一致.
结论:
- 复杂的网络模型在模拟传染病传播方面提供了卓越的准确性.
- 最佳控制和参数识别为公共卫生干预提供了至关重要的理论支持.
- 参数识别显示了在口腔图像识别和辅助疗法等领域的潜在应用.
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