New approaches to modelling malaria transmission and insecticide resistance: using realistic mosquito biology and behaviour, and network methods.

拟议的项目旨在通过纳入有关杀虫剂存在下蚊子生物学和行为的更多细节来调整标准的蚊媒建模框架。将重点关注时间序列动态和空间动态，这两者都可能对现实世界的疾病控制方案产生影响。外部合作伙伴提供了关于蚊子行为的实验数据，为模型开发提供信息;这些数据是在对疟疾病媒冈比亚按蚊进行实地实验期间收集的。目的是根据蚊子监测数据校准调整后的模型，并理想地与人类疟疾数据相匹配，目的是根据数据的可用性和外部合作伙伴的利益，侧重于特定地点，例如科特迪瓦和其他非洲国家。关于疟疾的文献通常不关注蚊子的网络模型-包括详细的病媒生物学的传播，因此开发关于其中具有蚊子和人类生物学和行为的网络的理论方法将是有趣的。这些方法，特别是包括使用蚊帐和杀虫剂的方法，将有助于了解疟疾的传播动态，也可以推广到其他蚊子或病媒传播的疾病，如登革热或裂谷热。(b)杀虫剂抗药性对传播有什么影响？蚊子喂养过程中的蚊子和宿主运动可能会对这些问题有潜在的洞察力，沿着探索杀虫剂暴露对蚊子的影响及其传播疟疾的能力。研究的背景-这项研究涉及数学流行病学，即传染病的数学建模。具体而言，疟疾是一种严重的蚊媒疾病，每年造成数千人死亡，特别是在非洲国家。蚊子对杀虫剂的抗药性是一个值得关注的问题，值得进一步探讨。缺乏关于病媒传播疾病和详细的病媒生物学网络的研究，这为产生新的方法提供了机会。研究的目的和目标-该项目将通过考虑蚊子生物学和行为的细节，调整标准的蚊子传播模型框架，并进一步了解杀虫剂抗药性对疟疾传播的影响。其目的是根据在科特迪瓦收集的真实蚊子数据校准经过调整的模型，并探索有关杀虫剂的不同情景。另一个目标是发展网络模型的理论方法，以便更好地了解疟疾传播动态。研究方法的新奇-本项目将根据从非洲特定区域收集的数据采用经过调整的模型，以比较不同的模型框架。此外，构建网络模型，旨在发展关于病媒传播疾病和杀虫剂的网络模型中有限的现有研究。潜在的影响，应用和好处-疟疾每年影响数百万人。由于目前缺乏疫苗，驱虫剂（蚊帐或喷雾）是控制这种疾病的主要方法之一。该项目可以通过使用一种新的网络方法来研究疟疾，从而帮助了解非洲国家的适当疾病控制战略。研究如何与职权范围相关-该项目福尔斯属于数学生物学和复杂性科学的范畴。研究领域;数学科学外部合作伙伴-利物浦热带医学院（LSTM）

The proposed project aims to adapt standard mosquito-borne modelling frameworks by including additional details about mosquito biology and behaviour in the presence of insecticides. There will be a strong focus on time-series dynamics and spatial dynamics, both of which could have implications for real-world disease control programmes. Experimental data on mosquito behavior has been provided by the external partner to inform model development; it was collected during field experiments on the malaria vector, Anopheles gambiae s.l. The aim is to calibrate the adapted model to mosquito surveillance data, and ideally match to human malaria data as well, with the intention to focus on specific locations, depending on data availability, and the external partner's interests, for example Côte d'Ivoire and other African countries.The literature on malaria does not routinely focus on network models of mosquito-borne transmission with detailed vector biology included and so it would be interesting to develop theoretical approaches on networks having mosquito and human biology and behaviour in them. Such approaches, particularly those including the use of bednets and insecticide, would help understand malaria transmission dynamics, and could also be generalised for other mosquito- or vector-borne diseases such as dengue, or Rift Valley fever.The basic research questions are:(a) How does malaria spread and persist over time?(b) What is the impact of insecticide resistance on the spread?Mosquito and host movement during mosquito feeding could potentially give an insight to these questions, along with exploring the impact of insecticide exposure on mosquitoes and their ability to transmit malaria.The context of the research - This research relates to Mathematical Epidemiology, i.e. mathematical modelling of infectious diseases. Specifically, modelling of malaria, a serious mosquito-borne disease, which is the cause of death of thousands of people every year, especially in African countries. Emerging insecticide resistance among mosquitoes is a key concern and worthy of further exploration. The lack of research on networks regarding vector-borne diseases and detailed vector biology gives an opportunity to produce novel methodologies.The aims and objectives of the research - This project will adapt standard mosquito-borne modelling frameworks by taking into consideration details about mosquito biology and behaviour, and further understand the impact of insecticide resistance on malaria transmission. The aim is to calibrate the adapted model to real-life mosquito data collected in Côte d'Ivoire, and explore different scenarios regarding insecticides. An additional aim is to develop theoretical approaches on network models in order to better understand malaria transmission dynamics.The novelty of the research methodology - This project will apply adapted models on data collected from specific regions in Africa to compare the different model frameworks. Additionally, construct network models aiming to develop the limited existing research in network models regarding vector-borne disease and insecticide.The potential impact, applications, and benefits - Malaria affects millions of people each year. Insecticides (bednets or spraying) are one main way to control this disease due to the current lack of vaccine. This project could support understanding of appropriate disease control strategies in African countries by looking at malaria from using a novel network approach.How the research relates to the remit - This project falls into the category of Mathematical Biology and also Complexity Science. It aims to develop and apply mathematical techniques in order to investigate biological systems at a population level.Research area; Mathematical Sciences External Partner - Liverpool School of Tropical Medicine (LSTM)