HYDROMAL: Hydro-dynamic drivers of malaria transmission hazard in Africa

HYDROMAL：非洲人类疟疾传播危险的流体动力驱动因素。托马斯，麦克林，史密斯和加马拉总结疟疾是一种病媒传播的疾病-我们成为感染的叮咬受感染的蚊子。目前人们非常关切的是，气候变化可能会改善蚊子等许多病媒的生存条件，疟疾等疾病也会增加。这种疾病的主要负担福尔斯落在非洲，预计下一个世纪那里的降雨量和温度将发生变化。虽然我们从实验室研究中对温度变化如何影响蚊子数量有了相当好的了解，但我们对降雨量变化的影响知之甚少，降雨量变化控制了蚊子繁殖地的可用性。这些繁殖地与人类宿主的分布是当地流行病学的主要驱动因素，在非洲许多地方，降水量的变化而不是温度的变化可能会推动传播的变化。这是我们的项目旨在填补的关键空白，不是通过开发新的科学，而是通过耦合不同学科来增加现有知识的价值。现代挑战需要跨学科的思维，我们的项目就是一个例子。我们的目标是将成熟的水文学工具与疟疾传播的数学模型联系起来，这些模型已经存在了50多年。为了量化这种关系，我们将在坦桑尼亚实地考察一年，同时开展水文学和昆虫学项目，在世界上疟疾传播水平最高的一个大山谷工作。然后，我们将再花一年时间分析数据并将数学联系起来。我们的想法是，如果我们能根据降雨量和地形，在任何给定时间预测病媒蚊子的繁殖地点，我们就能估计疟疾的传播。如果我们能证明这个简单的想法是可行的，它将为未来的研究铺平道路，将气候变化预测与非洲这种疾病的影响联系起来。它也可能被证明对卫生规划者有用：它可能被证明更有效地针对关键地点的资源，而且不同的干预措施可能在不同的景观中更有效。

HYDROMAL: Hydro-dynamic drivers of human malaria transmission hazard in Africa. Thomas, Macklin, Smith and Gamarra Summary Malaria is a vector borne disease - we become infected by the bite of an infected mosquito. There is currently great concern that climate change may improve conditions for many disease vectors, such as mosquitoes, and that diseases like malaria will increase. The main burden of this disease falls in Africa, where changes in rainfall and temperature are projected to occur over the next century. While we have a reasonably good understanding, from laboratory studies, of how changed temperature may effect mosquito populations, we have very little on the effect of changed rainfall, which controls the availability of mosquito breeding sites. The distribution of these breeding sites in relation to human hosts is the main driver of local epidemiology, and in many locations across Africa it is likely that changes in precipitation, not temperature, will drive changes in transmission. This is the critical gap our project aims to fill, not by developing new science, but by adding value to existing knowledge by coupling different disciplines. Modern challenges require interdisciplinary thinking, and our project is an example of this. We aim to link well-established tools from geophyscial hydrology with mathematical models of malaria transmission, models that have been around for over 50 years. To quantify this relationship we will spend a year in the field in Tanzania, with a parallel program of hydrology and entomology, working in a large valley with the highest levels of malaria transmission in the world. We will then spend a further year analyzing the data and linking the mathematics. Our idea is that if we can predict where the breeding sites for vector mosquitoes will be at any given time, based on rainfall and terrain, we can estimate the malaria transmission. If we can prove this simple idea works, it will pave the way for future studies linking climate change projections to impact on this disease in Africa. It may also prove useful for health planners: it may prove more effective to target resources in key locations, and it may be that different interventions are more effective in different landscapes.