模型结构和数据可用性对乌苏图病毒动态在三种生物尺度上的影响
Nora Heitzman-Breen1, Yuganthi R Liyanage2, Nisha Duggal3
1Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Royal Society open science
|February 8, 2024
概括
数学建模有助于理解乌苏图病毒 (USUV) 流行病学. 跨传输尺度的不确定性会影响预测,但最佳的实验设计可以提高稳定性.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 病毒学 病毒学
背景情况:
- 像乌苏图病毒 (USUV) 这样的新兴病原体需要进行多层次的调查以了解流行病学.
- 新型病毒的现场数据往往有限,需要补充实验和建模方法.
研究的目的:
- 通过数学建模,研究乌苏图病毒 (USUV) 在宿主内部,鸟向载体传播和流行病学尺度上的动态.
- 评估模型结构,数据不确定性和实验设计对USUV预测准确性的影响.
主要方法:
- 开发了用于USUV的宿主内部,传播和流行病学尺度的数学模型.
- 利用宿主感染病毒数据和蚊子感染百分比来预测USUV发病率.
- 进行了in silico实验,以评估模型识别能力和采样策略的影响.
主要成果:
- 一个尺度的预测不确定性显著影响了其他尺度的结果.
- 12小时的采样间隔足以在宿主模型内进行识别.
- 提高传输规模的识别性需要不切实际的高采样率.
结论:
- 多尺度建模对于理解USUV流行病学至关重要,但跨尺度的不确定性带来了挑战.
- 建议进行最佳的实验设计,以提高传播规模的识别能力和提高流行病学预测的稳定性.
- 有针对性的实验对于强有力的预测USUV等新兴病毒的发病率至关重要.
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