Understanding zoonotic disease risk using dynamic ecological models

在气候变化、栖息地破坏、人口增长和全球化加剧的推动下，自然界预计将在下个世纪发生重大转变。许多疾病，如埃博拉、鼠疫和炭疽，都是在人们与野生动物接触时感染的，这些疾病被称为“人畜共患病”。自然界和人类世界的过程决定了携带人畜共患病的物种目前在哪里被发现，这些潜在过程的任何变化都会导致携带疾病的物种在哪里生存的差异，因此，人们可以从它们那里感染疾病的地点。我将创建第一个全面但通用的模型，关于一系列高度优先的非洲人畜共患病的生态学和流行病学，重点关注那些对贫穷和脆弱的人类社区的生计有重大影响的疾病。我的建模方法将捕捉宿主物种所经历的环境条件的季节和年度差异，然后确定物种可以在全球范围内移动以应对环境变化的不同物理路线。在对真实疾病病例数据进行测试后，我的建模框架将首次允许研究人员和政策制定者同时致力于减少可能感染各种非常不同的人畜共患病的人数，然后预测气候和土地利用变化将如何影响未来的这些政策决定。我的工作有可能在未来减轻整个非洲的疾病负担，从而减轻人类的痛苦。

The natural world is expected to undergo a significant transformation over the next century, driven by climate change, habitat destruction, human population increase and greater globalisation. Many diseases, such as Ebola, Plague and Anthrax, are caught when people come into contact with wild animals and these diseases are called 'zoonoses'. Processes within the natural and human world dictate where the species that carry zoonoses are currently found, and any changes to these underlying processes will lead to differences in where disease-carrying species can live, and therefore, the locations where people can catch diseases from them. I will create the first, comprehensive but general model of the ecology and epidemiology of a set of high priority African zoonoses, focusing on those diseases that have a major impact on the livelihoods of poor and vulnerable human communities. My modelling approach will capture the seasonal and annual differences to the environmental conditions that host species experience and then determine the different physical routes by which species can then move around the globe to respond to environmental change. After testing against real disease case data, my modelling framework will, for the first time, allow researchers and policy makers to simultaneously aim to minimise the number of people who can contract a wide set of very different zoonoses, and then predict how climate and land-use change will impact these policy decisions in the future. My work has the potential to reduce disease burden and consequently levels of human suffering across Africa in the future.