Cross-scale dynamics of LASV spillover within human-driven ecosystems
LASV 溢出在人类驱动的生态系统中的跨尺度动态
基本信息
- 批准号:2208034
- 负责人:
- 金额:$ 299.88万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-15 至 2027-07-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The transmission of animal diseases to humans has significant consequences for public health and economies globally, as evidenced by the COVID-19 pandemic. When evaluating disease risks, policy decisions often rely on data visualization techniques, such as risk maps. However, there is a limited understanding of how broad-scale risk maps relate to local-scale processes that affect disease transmission from animals to humans. For example, risk maps are often missing vital information on how broad associations between disease risk and factors such as climate, land-use, and poverty are driven by interactions between humans, animals, and the environment that affect probability of human infection. On the other hand, localized studies revealing fine-scale disease processes are often poorly situated to inform projections of risk at broader spatial scales. This project bridges this gap through a study of Lassa fever, a rodent-borne hemorrhagic fever of public health significance in West Africa and a global health priority. Field studies are conducted to examine human-environment interactions that support reservoir populations and behaviors that result in Lassa virus exposures. These data can improve our understanding of risk factors and inform public health policies. This study uses participatory methods that engage local communities at the forefront of global health challenges in the construction of knowledge and management strategies. It also contributes to public health via the production of robust data products for scientists and decision makers and improved epidemic preparedness. This project uses a fine-scale quantitative and participatory modelling approach that explicitly integrates results from local-scale field studies into broad-scale risk models to identify the patterns and processes that drive spillover of Lassa virus within human-driven ecosystems. Field studies sample across known broad-scale drivers of Lassa fever risk to understand how local-scale processes vary across scale (e.g., how reservoir population dynamics are impacted by human land-use, or how poverty translates to high-risk human behavior etc.). Data on rodent population dynamics, movement, and infection are combined with data from participatory activity mapping and ethno-epidemiological research to capture the anthropogenic factors that construct pathways for zoonotic spillover; for example, through practices that modify environments, pathogen dynamics within reservoir hosts, and the human-reservoir interface. These local-scale analyses inform a set of interface models that can help to unpack the processes that determine the spatial and temporal distribution of Lassa virus and risky human exposures in relation to landscape dynamics. Model outcomes provide scenarios for participatory examination of disease control interventions in the context of competing risks, e.g., poverty and food insecurity. Finally, data from empirical studies and emergent patterns from the interface models are integrated back into existing broad-scale regression-based risk models. Local-scale studies and model predictions can therefore fill key gaps in our understanding of how risk is propagated across scales and be used to inform ongoing disease management efforts for Lassa fever, and zoonotic spillover more generally.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
动物疾病传播给人类对全球公共卫生和经济产生重大影响,COVID-19大流行就是明证。在评估疾病风险时,政策决策通常依赖于数据可视化技术,如风险地图。然而,人们对大规模风险地图如何与影响疾病从动物传播到人类的地方规模过程相关联的理解有限。例如,风险地图往往缺少关于疾病风险与气候、土地使用和贫困等因素之间的广泛关联是如何由影响人类感染概率的人类、动物和环境之间的相互作用驱动的重要信息。另一方面,揭示精细尺度疾病过程的局部研究往往不适合在更广泛的空间尺度上为风险预测提供信息。该项目通过对拉沙热的研究填补了这一空白,拉沙热是一种啮齿动物传播的出血热,在西非具有公共卫生意义,是全球卫生优先事项。进行实地研究,以检查人与环境的相互作用,支持水库人口和行为,导致拉沙病毒暴露。这些数据可以提高我们对风险因素的理解,并为公共卫生政策提供信息。本研究采用参与式方法,让处于全球健康挑战前沿的当地社区参与知识和管理策略的构建。它还通过为科学家和决策者提供可靠的数据产品和改进流行病防备工作,为公共卫生作出贡献。 该项目采用精细规模的定量和参与性建模方法,将地方规模实地研究的结果明确纳入大规模风险模型,以确定在人为驱动的生态系统内驱动拉沙病毒溢出的模式和过程。实地研究对拉沙热风险的已知大规模驱动因素进行抽样,以了解局部规模过程如何在不同规模上变化(例如,水库人口动态如何受到人类土地使用的影响,或贫困如何转化为高风险的人类行为等)。啮齿动物种群动态,运动和感染的数据相结合的参与性活动绘图和民族流行病学研究的数据,以捕捉人为因素,构建人畜共患病的溢出途径,例如,通过修改环境,病原体动态水库主机,和人类水库接口的做法。这些局部尺度的分析为一组界面模型提供了信息,这些模型可以帮助解开决定拉沙病毒时空分布的过程,以及与景观动态有关的人类风险暴露。模型结果提供了在相互竞争的风险背景下对疾病控制干预措施进行参与性检查的情景,例如,贫困和粮食不安全。最后,将来自经验研究的数据和来自界面模型的紧急模式整合回现有的大规模基于回归的风险模型。因此,地方规模的研究和模型预测可以填补我们对风险如何跨规模传播的理解的关键空白,并用于为拉沙热的持续疾病管理工作提供信息,以及更普遍的人畜共患病溢出。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。
项目成果
期刊论文数量(0)
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Sagan Friant其他文献
Threats from trading and hunting of pottos and angwantibos in Africa resemble those faced by slow lorises in Asia
非洲麻雀和安格万蒂博斯的贸易和狩猎带来的威胁与亚洲懒猴所面临的威胁类似
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
M. S. Svensson;Sagan Friant - 通讯作者:
Sagan Friant
Typical intracranial myiasis in Nigerian red river hogs (Potamochoerus porcus) caused by an unknown bot fly (Diptera: Oestridae).
尼日利亚红河猪(Potamochoerus porcus)的典型颅内蝇蛆病,由未知的蝇科(双翅目:Oestridae)引起。
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Sagan Friant;D. K. Young;T. Goldberg - 通讯作者:
T. Goldberg
Sagan Friant的其他文献
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