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Phylogenetic modeling of viral transmission dynamics at the human-wildlife interface in Uganda

Phylogenetic modeling of viral transmission dynamics at the human-wildlife interface in Uganda
乌干达人类与野生动物界面病毒传播动力学的系统发育模型
批准号:
10814050
负责人:
Krista Milich
金额:
$54.06万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-20 至 2028-05-31

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中文摘要
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英文摘要
Many infectious diseases that threaten humans originated among wildlife, yet we know relatively little about the real-world ecological conditions that enable spillover events. Despite its importance, identifying novel viral pathogens and characterizing their transmission dynamics remains difficult because it requires advanced genetic sequencing technologies, sampling wildlife likely to harbor pathogens of concern to humans, and sophisticated modeling techniques. We will study red colobus monkeys in Kibale National Park, Uganda, other nonhuman primates, and people who neighbor these wildlife populations to quantify transmission dynamics within and between species. Our team will collect behavioral ecology data on red colobus monkeys living in areas of the forest with different degrees of anthropogenic disturbance and conduct interviews with people living along the boundary of the park with varying exposure risks for zoonotic diseases. We will conduct repeat sampling of people and individually identifiable red colobus monkeys to analyze the gut virome, assess infection with gastrointestinal parasites known to infect both red colobus and people, discover previously undocumented viral diversity, detect the presence of novel pathogens of concern to humans, red colobus monkeys, and other primates (e.g. SARS-CoV-2), and track the evolutionary spread of detected pathogens. To model how red colobus-associated viruses spread, we will develop new phylodynamic models that allow longitudinal ecological and biogeographical data to structure time-heterogenous epidemiological event rates. We will also create, test, and distribute new software for simulation, Bayesian inference, and deep learning-based inference to model how infectious diseases spread in a wide variety of ecosystem-level transmission scenarios. Our proposed project will benefit public health and wildlife conservation and expand STEM training in the USA and Uganda. Working with Ugandan communities, we will co-create solutions to address risks for zoonotic disease transmission and test mitigation strategies to reduce transmission pathways.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s11538-024-01337-6
发表时间: 2024-08-01
期刊: BULLETIN OF MATHEMATICAL BIOLOGY
影响因子: 3.5
作者: [Soewongsono,Albert C., Landis,Michael J.]
通讯作者: Landis,Michael J.
PhyloJunction: a computational framework for simulating, developing, and teaching evolutionary models.
PhyloJunction:用于模拟、开发和教授进化模型的计算框架。
DOI: 10.1101/2023.12.15.571907
发表时间: 2023
期刊: bioRxiv : the preprint server for biology
影响因子: --
作者: [Mendes,FábioK, Landis,MichaelJ]
通讯作者: Landis,MichaelJ
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