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Updated: Feb 13, 2026

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疾病在不断演变的敏感网络中传播的动态
Khagendra Adhikari1, Naveen K Vaidya2, Feng-Bin Wang3
1Amrit Campus, Tribhuvan University, Kathmandu, Nepal; Department of Natural Science, Center for General Education, Chang Gung University, Taiwan; Mathematical Biology Research Center, Kathmandu, Nepal.
Journal of theoretical biology
|February 11, 2026
概括
这项研究引入了疾病传播的动态分隔模型,揭示了控制不断扩大的易感人口是缓解COVID-19等流行病的关键. 该模型准确地预测了流行病浪潮,并强调了病例报告不足.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生 公共卫生
背景情况:
- 传统的隔间模型通常假定静态种群.
- 疾病传播动态受到不断变化的接触网络和易感人群的影响.
研究的目的:
- 开发和验证一个包含动态联系和不断变化的目标易感人群的区块模型.
- 将该模型应用于尼泊尔的COVID-19数据,并评估其预测准确性.
- 确定影响流行病严重程度和疾病灭绝的关键参数.
主要方法:
- 开发一种具有动态接触和不断变化的易受感染群体的新型分隔模型.
- 模型的应用和验证使用尼泊尔的COVID-19流行病学数据.
- 对模型属性的灵敏度,值和分析分析.
主要成果:
- 该模型准确地重现了尼泊尔三次主要的COVID-19流行浪潮的时间,规模和形状.
- 模型输出与报告的血清流行率数据密切一致,表明病例报告不足.
- 目标人口扩张率被确定为流行病严重程度和R0.0的关键驱动因素.
结论:
- 针对传播率,易受感染的人口扩张和接触网络动态的战略干预可以有效地缓解流行病.
- 拟议的不断发展的网络模型为实时流行病评估和适应性政策制定提供了强大的框架.
- 确定了灭绝值指数,这对于预测疾病的持续性或根除至关重要.
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