LEAPS-MPS: Development of Novel Multistage Models for Wolbachia-Based Strategies to Control Mosquito-Borne diseases

蚊子是世界上最致命的生物之一，因为它们可以传播蚊子传播的疾病，如登革热，疟疾，基孔肯雅病和寨卡病毒。基于沃尔巴克氏体的干预是控制蚊媒疾病传播的一种新的替代缓解策略，因为一些感染沃尔巴克氏体的蚊子传播疾病的能力较低。该项目提出了新的和创新的数学模型，用于蚊子中Wolbachia感染的传播，作为疾病控制，帮助公共卫生工作者更好地了解疾病动态并优化缓解工作。除了复杂的传播动力学，模型还将考虑影响传播过程的空间和时间异质性。有了这些实际的考虑，所提出的模型可以提供对基于沃尔巴克氏体的干预措施的全面和坚实的理解，其结果可以更好地支持公共卫生工作者确定减少蚊媒疾病的有效和可持续的方法。该项目将设在一个为西班牙裔/少数民族服务的机构，其中67%的学生是少数民族。研究工作将与来自不同学术背景的学生参与传染病建模和鼓励来自代表性不足群体的学生参与完全整合。利用多样化的学生群体及其与少数民族组织的密切联系，研究成果将通过校园，专业，和媒体场所，以实现对这些群体和公众观众的进一步影响。拟议的模型将建立在坚实的流行病学和数学基础，并将占沃尔巴克氏体-诱导的生物学效应以及季节性和蚊子空间分散的异质性。该项目将推导出具有不同生物分辨率的模型，以平衡模型的可预测性和分析挑战，具体目标包括三个：（1）分析小规模模型，以获得对Wolbachia建立的基本定性理解，特别是Wolbachia传播和空间感染波传播的临界阈值条件的表征;这为以下方面提供了重要的见解：（2）设计捕捉生物效应细节的全尺寸模型。对全尺寸模型的数值研究将为有关实地释放的实际情况提供信息，并确定在实地建立沃尔巴克氏体的有效做法。(3)PI还将进行详细的模型参数化，并在项目的不同阶段量化模型的不确定性。当地和全球敏感性分析方法将被用来量化模型中的不确定性，并确定它们对模型预测的相对重要性，以便它们可以更有用和更容易被公共卫生界解释。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。

Mosquitoes are one of the deadliest creatures in the world because of the mosquito-borne diseases they can transmit, such as dengue fever, malaria, chikungunya, and Zika. Wolbachia-based intervention is a novel alternative mitigation strategy to control the spread of mosquito-borne diseases, as some Wolbachia-infected mosquitoes are less capable of transmitting diseases. This project proposes new and innovative mathematical models for the spread of Wolbachia infection in mosquitoes as a disease control which helps public health workers better understand the disease dynamics and optimize mitigation efforts. Besides the complex transmission dynamics, the models will also account for spatial and temporal heterogeneity that affects the transmission process. With these practical considerations, the proposed models can provide a comprehensive and solid understanding of Wolbachia-based interventions, and the results can better support public health workers to identify effective and sustainable approaches for reducing mosquito-borne diseases. The project will be based at a Hispanic-/minority-serving institution, where 67% of the students are minorities. The research efforts will be fully integrated with engaging students from various academic backgrounds in modeling infectious diseases and encouraging the participation of students from underrepresented groups. Leveraging the diverse student populations and their close connections to minority organizations, the research results will be disseminated through campus, professional, and media venues to achieve further impact on these groups and the general public audience.The proposed models will be built on solid epidemiological and mathematical foundations and will account for both the Wolbachia-induced biological effects and the heterogeneity from seasonality and mosquitoes’ spatial dispersions. The project will derive models with different levels of biological resolutions to balance the model’s predictability and analytical challenge, and it includes three specific aims: (1) analysis of small-scale models to gain a basic qualitative understanding of the Wolbachia establishment, in particular, the characterization of critical threshold condition for Wolbachia spreading and spatial infection wave propagation; this provides important insights into (2) the design of full-scale models that capture details of the biological effects. The numerical study of the full-scale models will inform practical scenarios that concern the field releases and identify efficient practices for establishing Wolbachia in the field. (3) The PI will also conduct detailed model parametrizations and quantify model uncertainty at different stages of the project. The local and global sensitivity analysis approaches will be employed to quantify the uncertainty in the models and determine their relative importance to the model predictions so that they can be more useful and interpretable by the public health community.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.