Modeling of Mosquitoes Carrying Transgenes or Genetically Modified Bacteria in Preventing the Transmission of Mosquito-Borne Diseases

研究人员在该项目中开发了蚊子种群和疾病传播动力学的各种数学模型。 这包括转基因蚊子的模型，这种蚊子对蚊子传播的疾病具有抵抗力，并且具有明显的适应性，其中一些比其他蚊子具有优势。 利用组合流行病模型研究蚊子之间的相互作用动力学，表征转基因蚊子相对于非转基因蚊子具有选择优势的事实，并研究转基因蚊子对疾病传播的影响。 具有各种基因或品系的转基因蚊子的建模以及包括雄性和雌性的两性蚊子种群的建模也是该项目的一部分。 所有模型都从简单的形式开始，逐渐包括更复杂的结构，以更好地描述潜在的生物学。 在每个模型类别中，研究人员确定出生和死亡函数以及接触率的不同公式，这有助于将建模与真实的数据联系起来。 随着蚊子种群模型的建立，将结合各种人类和蚊子种群的流行病模型来研究蚊媒疾病的传播动力学。 研究人员还专注于新开发的副转基因技术的建模，该技术试图通过共生体的转基因从蚊子种群中消除病原体，即，一种转基因细菌，可以防止蚊子传播病原体。 研究了蚊虫间细菌水平传播和垂直传播的动态及其对疾病传播的影响。 其目的是了解相互作用的野生蚊子和携带转基因或转基因细菌的蚊子的动力学的复杂性，并预测释放转基因蚊子的影响。 分析和数值模拟相结合，研究定性和定量的特点，包括平衡点的存在性和稳定性，存在的周期和非周期振荡通过分叉，混沌行为和瞬态动力学。 模型参数是从真实的生物数据中估计或导出的，并且模型的数学分析覆盖所有参数区域。生物学的新发展允许研究人员对蚊子进行遗传改变，使得它们能够抵抗疟疾感染或其他蚊媒疾病，如登革热和西尼罗河病毒。 最近开发的一种新的副转基因方法产生了携带转基因细菌的蚊子，这些细菌会削弱蚊子中病原体的传播。蚊子传播的疾病是通过吸血蚊子在人类之间传播的，它们的传播和控制一直是公共卫生的主要问题。 将转基因蚊子引入野生蚊子种群可能是控制蚊媒疾病的有效措施。 为了探索这种可能性，研究人员与生物学家合作，开发和分析了代表野生和转基因蚊子种群动态的数学模型。这些模型解释了转基因或转基因细菌在蚊子种群中的多代传播，并预测了对疾病传播的影响。它们有助于回答这样的问题，如携带转基因或改良细菌的蚊子如何有效地与野生蚊子竞争伴侣，新的抗性基因或细菌需要多长时间才能渗透到蚊子种群中，以及它在预防疾病传播方面的有效性。这样，该项目的结果可以为公共卫生措施和疾病预防战略提供有益的指导。

The investigator develops various mathematical models for mosquito populations and disease transmission dynamics in this project. This includes models for transgenic mosquitoes, which are resistant to infection by mosquito-borne diseases, and have distinct fitnesses, some of which have advantages over the others. Combined epidemic models are used to study the interactive dynamics of the mosquitoes, characterizing the fact that transgenic mosquitoes have a selective advantage over non-transgenic mosquitoes, and to investigate the effects of transgenic mosquitoes on the disease transmissions. Modeling of transgenic mosquitoes with various genes or strains, as well as modeling of two-sex mosquito populations including both males and females, is also part of this project. All models start with simpler forms, and gradually include more complex structures to better describe the underlying biology. Within each model category, the investigator determines different formulas for the birth and death functions and the contact rates, which facilitates the ability to connect the modelling with real data. With the population models for the mosquitoes well established, various epidemic models for both human and mosquito populations will be incorporated to study the transmission dynamics of the mosquito-borne diseases. The investigator also focuses on modeling of the newly developed paratransgenic technique, which attempts to eliminate a pathogen from mosquito populations through transgenesis of a symbiont, i.e., a genetically modified bacterium, that prevents the mosquitoes from transmitting the pathogen. The dynamics of horizontal bacteria transmission, as well as vertical transmission between mosquitoes, and their effects on the disease transmissions are investigated. The goal is to understand the complexity of the dynamics of the interacting wild mosquitoes and the mosquitoes carrying transgenes or genetically modified bacteria, and predict the impact of releasing the modified mosquitoes. Analysis and numerical simulation is combined to study qualitative and quantitative features of the models, including existence and stability of equilibria, existence of periodic and aperiodic oscillations through bifurcations, and chaotic behavior and transient dynamics. Model parameters are estimated or derived from real biological data and the mathematical analysis of the models covers all parameter regions.New developments in biology allow researchers to genetically alter mosquitoes so that they are resistant to malaria infection or other mosquito-borne diseases, such as dengue fever and West Nile virus. A more recently developed new paratransgenic approach generates mosquitoes carrying genetically modifies bacteria that impairs in the transmission of pathogens in mosquitoes. The mosquito-borne diseases are transmitted between humans by blood-feeding mosquitoes, and their spread and control have been major concerns for public health. The introduction of modified mosquitoes into wild mosquito populations could be an effective measure in controlling mosquito-borne diseases. To explore this possibility, the investigator, in collaboration with biologists, develops and analyzes mathematical models that represent the population dynamics of wild and transgenic mosquitoes. The models account for the spread of transgenes or genetically modified bacteria through the mosquito population over multiple generations, and predict the impact on the disease transmissions. They help answer such questions as how effectively mosquitoes carrying transgenes or modified bacteria would be able to compete for partners with their wild counterparts, how long it would take for a new resistance gene or bacterium to penetrate the mosquito population, and how effective it would be in preventing the spread of the diseases. In this way, the results of the project can provide useful guidance for public health measures and for disease prevention strategies.