Impact of El Niño on malaria vector dynamics in Tanzania: observation, improvement and unleashing forecasting potential

厄尔尼诺现象已被证明对许多媒介传播疾病产生重大影响，包括疟疾、登革热、裂谷热和其他疾病。虽然厄尔尼诺现象与疾病之间的联系已经确立，但其背后的机制尚未完全解决，但可能涉及降雨模式的变化(通常是干旱和暴雨，反之亦然)或厄尔尼诺现象带来的温度变化对病媒生物本身的影响。在这里，我们的目标是利用过去9年收集的关于一个VBD的详细昆虫学数据来检测当前厄尔尼诺事件对媒介动力学造成的扰动。当前厄尔尼诺现象的强度，高质量昆虫学数据的存在，负责团队的加入，以及对当地气象数据的获取，为了解厄尔尼诺事件如何引发VBD的出现提供了一个独特的机会。我们将重点放在疟疾上，它仍然是VBD对人类死亡率和发病率影响最大的疾病，并建议在坦桑尼亚中部的基隆贝罗山谷地区进行新的田野工作，那里的人口感染率为30%。疟疾是由疟原虫属的寄生原虫引起的，由雌性按蚊传播。疟疾分布的空间范围、季节活动和蚊媒动态对气候因素以及当地控制疾病的能力非常敏感。这项提议的目的是描述当前厄尔尼诺事件、其对区域和当地气候的影响以及随后对坦桑尼亚疟疾病媒和疟疾负担的后果之间的连锁联系。开展这项工作是为了更好地了解厄尔尼诺现象如何影响疟疾，并为坦桑尼亚的疟疾风险建立一个早期预警系统原型。我们将通过使用新的标准技术来测量Kilombero山谷内的蚊子媒介特性来实现这一目标。我们将在该地区一些以前研究过的村庄进行为期12个月的详细昆虫学研究，以期发现厄尔尼诺现象对媒介动态或行为造成的变化或扰动。这些新数据将结合2006-2015年间已经收集的9年历史数据(这一实地行动于2015年5月结束)以及疟疾临床数据和不同的气候数据集进行分析，从区域尺度的卫星估计到研究区域现有的地方尺度气象站数据。这些地区的详细天气数据可从当地气象站获得，并将由研究村庄的温度/湿度数据收集提供支持。基于这些发现，我们将更好地了解厄尔尼诺现象对疟疾及其媒介的影响(适用于更广泛的VBD)，并在坦桑尼亚建立疟疾风险预警系统原型。这将是当地决策者和公共卫生专家今后针对和允许病媒控制资源的有用资源。

El Nino events have been shown to impact significantly on many vector-borne diseases (VBDs), including malaria, dengue, Rift Valley fever and others. While the link between El Nino and disease is well established, the mechanism underlying it is not fully resolved, but probably involves impact of the change in rainfall patterns (often drought and then heavy rain, or vice versa) or altered temperatures brought by El Nino on the vectors themselves. Here we aim to take advantage of the collection over the past 9 years of detailed entomological data on one VBD to detect a perturbation to vector dynamics caused by the current El Nino event. The strength of the current El Nino, the existence of high quality entomological data, the inclusion of the team responsible in this proposal, and access to local meteorological data provide a unique opportunity to understand how El Niño events trigger the emergence of VBDs.We focus on malaria, which remains the VBD with the greatest impact on human mortality and morbidity, and propose new fieldwork in the Kilombero valley area of central Tanzania, where there is a 30% prevalence of infection in people. Malaria is caused by parasitic protozoa of the genus Plasmodium and it is transmitted by female Anopheles mosquitoes. The spatial limits of malaria distribution, its seasonal activity and the mosquito vector dynamics are very sensitive to climate factors, as well as the local capacity to control the disease.The aim of this proposal is to characterize the chain of connections between the current El Niño event, its impact on regional and local climate, and the subsequent consequences on malaria vectors and malaria burden in Tanzania. This is carried out to better understand how El Nino affects malaria, and in order to build an early warning system prototype for malaria risk in Tanzania. We will achieve this though the use of new and standard technologies to measure mosquito vector properties within the Kilombero Valley. We will undertake 12 months of detailed entomological study in a number of previously-studied villages in the region, in the expectation of detecting a change or perturbation to vector dynamics or behaviour caused by El Nino. These new data will be analysed in the context of the 9 years of historic data already collected between 2006-2015 (this field campaign ended in May 2015), as well as malaria clinical data and different climate datasets, ranging from regional scale satellite estimates to local scale meteorological station data available for the studied region. Detailed weather data for the areas are available from a local weather station, and will be supported by temperature/humidity data collection in the study villages. Based on the findings, we will develop a better understanding of how El Nino impacts on malaria and its vectors (with applicability to a wider range of VBDs) and build a prototype early warning system for malaria risk in Tanzania. This will be a useful resource for local decision makers and public health specialists to target and allow vector control resources in future.