PREDICTING VIRAL DYNAMICS, IMMUNE RESPONSE AND EPIDEMIC SPREAD OF MULTI-HOST PAT

预测多宿主病毒的病毒动力学、免疫反应和流行病传播

• 批准号: 8168270
• 负责人: MELANIE MOSES
• 金额: $ 38.44万
• 依托单位: UNIVERSITY OF NEW MEXICO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8168270
• 关键词: Biological; Birds; Blood; Characteristics; Communities; Computer Retrieval of Information on Scientific Projects Database; Computer Simulation; Data; Ecology; Epidemic; Funding; Grant; Health; Human; Immune response; Infection; Institution; Laboratories; Metabolic; Modeling; Physiology; Population; Publishing; Research; Research Personnel; Resources; Source; Testing; Time; United States National Institutes of Health; Viral; Viremia; Virus; West Nile virus; base; field study; innovation; life history; pathogen; theories; vector mosquito

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Many existing and emerging pathogens are multi-host pathogens that cross into human populations. It is difficult to predict how those pathogens will spread, because each species can have very different infectivity, immune response and ecological characteristics. The proposed research uses an innovative and powerful modeling approach that combines biological theory, published data and computer simulations to predict immune response, viral dynamics and epidemic spread from host mass. The research focuses on West Nile Virus (WNV), a pathogen that has spread rapidly across the US with severe consequences to human health. Because WNV is well-studied in the laboratory and in ecological field studies, there is sufficient information to build accurate computer models and to test their predictions. The models predict how WNV spreads within and between bird host species using Metabolic Scaling Theory (MST). MST identifies profound and predictable differences in the physiology, life history and ecology of different species based on their mass. The aims of this project are to predict 1) the time course of viremia in each infective bird species 2) characteristics of bird species that harbor sufficient WNV to infect mosquito vectors, 3) how long those bird species are infective, and 4) which bird communities have a combination of species that enable WNV to persist. MST guides these predictions by relating rates of viral replication, immune response and ecological interaction to mass. Aim 1 predicts the time course of viremia, including the concentration of virus in blood each day post infection and the duration of viremia that is sufficient to infect mosquito vectors. The duration of infective viremia is an important determinant of epidemic spread which is modeled in Aim 2.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 许多现有和新出现的病原体是跨入人类群体的多宿主病原体。很难预测这些病原体将如何传播，因为每个物种都有非常不同的传染性、免疫反应和生态特征。拟议的研究采用了一种创新且强大的建模方法，该方法结合了生物学理论、已发表的数据和计算机模拟来预测免疫反应、病毒动态和宿主群体的流行病传播。 该研究重点关注西尼罗河病毒（WNV），这种病原体已在美国迅速传播，对人类健康造成严重后果。由于西尼罗河病毒在实验室和生态实地研究中得到了充分研究，因此有足够的信息来建立准确的计算机模型并测试其预测。该模型利用代谢尺度理论 (MST) 预测西尼罗河病毒如何在鸟类宿主物种内部和之间传播。 MST 根据不同物种的质量识别其生理学、生活史和生态学方面的深刻且可预测的差异。 该项目的目的是预测 1) 每种传染性鸟类病毒血症的时间进程；2) 携带足够 WNV 来感染蚊媒的鸟类的特征；3) 这些鸟类的传染性持续多长时间；以及 4) 哪种鸟类群落中的物种组合使得西尼罗河病毒能够持续存在。 MST 通过将病毒复制率、免疫反应和生态相互作用与质量联系起来来指导这些预测。目标 1 预测病毒血症的时间进程，包括感染后每天血液中病毒的浓度以及足以感染蚊媒的病毒血症的持续时间。感染性病毒血症的持续时间是目标 2 中模拟的流行病传播的重要决定因素。