To assess interventions for malaria in India and Pakistan

疟疾仍然是一个主要的全球卫生问题，也是许多热带和亚热带国家的主要死亡和疾病原因之一。在非洲以外，印度的疟疾负担最大，据估计，印度有4亿人面临感染风险，仅2014年就有110万病例。近年来，控制努力大大减轻了疾病负担，尽管实现消除可能会更加困难。印度的疟疾生态非常复杂，其特点是病媒和寄生虫的多样性，其相对贡献因环境而异。虽然该国中部的特点是嗜内性媒介和间日疟原虫高负担，但在其他地区，恶性疟原虫占主导地位，并通过各种嗜外性和嗜外性媒介传播。这种多样性对旨在控制疾病的干预措施产生了实质性影响，其影响可能会受到当地疟疾背景的重大影响。数学模型为了解传染病的传播动态提供了有用的工具，并在非洲被广泛用于指导和制定旨在控制疟疾的干预措施的部署。尽管如此，印度疟疾数学模型的发展仍然很出色--在这种缺失的推动下，本论文试图构建一个涵盖印度各地不同生态环境的疟疾传播模型。然后，这个模型将被用来帮助驾驭生态环境和控制努力的影响之间的复杂相互作用，并协助绘制特定控制努力部署在哪里最好的地图。这种工作将使干预部署能够以对当地和区域疟疾情况敏感的方式进行，并最终为根除工作提供信息。

Malaria remains a major global health problem, and one of the leading causes of death and disease across many tropical and subtropical countries. India possesses the largest burden of malaria outside of Africa, with an estimated 400 million at risk of infection and 1.1 million cases in 2014 alone. Recent years have seen control efforts achieve large reductions in the burden of disease, although achieving elimination is likely to prove more difficult. The ecology of malaria in India is highly complex, and characterised by a diversity of vectors and parasites whose relative contributions vary significantly depending on the setting. Whilst the centre of the country is characterised by endophilic vectors and a high Plasmodium vivax burden, in other areas, Plasmodium falciparum dominates and is transmitted by a variety of exophagic and exophilic vectors. This diversity has material consequences for interventions aimed at controlling the disease, with impact likely to be significantly influenced by the local malaria context. Mathematical models provide useful tools to understand the transmission dynamics of infectious diseases, and have been used extensively in African contexts to guide and shape the deployment of interventions aimed at controlling malaria. Despite this, development of a mathematical model of malaria in India remains outstanding- motivated by this absence, this thesis seeks to construct a model of malaria transmission that encompasses the diverse ecological settings seen across India. This model will then be used to help navigate the complex interplay between the ecological setting and the impact of control efforts, and assist mapping of where particular control efforts would best be deployed. Such work will enable intervention deployment to be carried out in a manner sensitive to local and regional malaria contexts, and ultimately inform eradication efforts.