New spatially explicit approaches for estimating malaria parasite migration

估计疟疾寄生虫迁移的新的空间明确方法

• 批准号: 2049805
• 负责人: Kathleen Stewart
• 金额: $ 40.55万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2049805&HistoricalAwards=false
• 关键词: New; spatially; explicit; approaches; estimating

This research improves the ability to estimate and map malaria parasite migration pathways. It will do so by accounting for the spatial patterns present in parasite genomic data as well as the spatial properties of features of the landscape and built environment that are relevant for gene flow, for example, features that serve to either impede or enable parasite migration. The investigators consider how the spatial distribution of parasite genomic sampling locations impacts estimated migration patterns and determine whether the mapped migration paths are still meaningful even when there is an irregular distribution of sampling locations. The research provides insights on how to include locally known migration barriers as well as other relevant natural or built environmental features into mapped migration estimates. As public health officials work toward reducing and eventually eliminating malaria, local information about factors driving malaria risk is important for prioritizing resources and optimizing control and elimination strategies. The research will be undertaken using computational methods that generate estimated effective migration surfaces. These methods use Markov chain Monte Carlo simulations to estimate migration and create migration contours that can be mapped to show relative high or low areas of gene flow. This research will integrate local spatial features to improve gene flow estimates and account for possible barriers thereby reducing spatial uncertainty that is commonplace in current maps of parasite migration. A set of analyses will be undertaken to determine the robustness of parasite migration surface estimates to varying spatial distributions of genomic data sample locations. This research is expected to not only have a profound impact for local public health officials tasked with eliminating P. falciparum and P. vivax malaria but will transform the ability of a broader group of researchers to produce parasite migration estimates for other kinds of species at local scales and provide new computational tools for studying parasite migration.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.

这项研究提高了估计和绘制疟原虫迁移路径的能力。它将通过考虑寄生虫基因组数据中存在的空间模式以及与基因流动相关的景观和建筑环境特征的空间特性来做到这一点，例如，有助于阻碍或使寄生虫迁移的特征。研究人员考虑了寄生虫基因组采样位置的空间分布如何影响估计的迁移模式，并确定即使采样位置分布不规则，绘制的迁移路径是否仍然有意义。该研究提供了如何将当地已知的迁移障碍以及其他相关的自然或建筑环境特征纳入映射迁移估计的见解。随着公共卫生官员努力减少并最终消除疟疾，有关导致疟疾风险的因素的当地信息对于确定资源的优先次序和优化控制和消除战略非常重要。这项研究将使用计算方法来产生估计的有效迁移面。这些方法使用马尔科夫链蒙特卡罗模拟来估计迁移，并创建迁移轮廓，可以映射以显示相对高或低的基因流动区域。这项研究将整合当地的空间特征，以改善基因流估计，并解释可能的障碍，从而减少目前寄生虫迁移地图中常见的空间不确定性。将进行一系列分析，以确定寄生虫迁移表面估计对基因组数据样本位置不同空间分布的稳健性。这项研究预计不仅会对当地负责消除恶性疟原虫和间日疟原虫疟疾的公共卫生官员产生深远的影响，而且会改变更广泛的研究小组的能力，以便在当地范围内对其他种类的物种进行寄生虫迁移估计，并为研究寄生虫迁移提供新的计算工具。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

项目成果

Estimation of malaria parasite migration using gene flow simulations: Addressing the impact of sparse sample locations

使用基因流模拟估计疟原虫迁移：解决样本位置稀疏的影响

• 发表时间: 2023
• 期刊: American Society of Tropical Medicine and Hygiene
• 作者: Li, Y.

Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model

• DOI: 10.1093/cid/ciac568
• 发表时间: 2022-07-19
• 期刊: CLINICAL INFECTIOUS DISEASES
• 影响因子: 11.8
• 作者: Li, Yao;Stewart, Kathleen;Plowe, Christopher, V
• 通讯作者: Plowe, Christopher, V