Redefining thermal suitability for urban malaria transmission in the context of humidity

项目总结/摘要 城市环境是地球上增长最快的景观， 在过去的几十年里，适应城市的蚊子的数量显著增加。城市病媒包括 斯氏按蚊，南亚城市疟疾的罪魁祸首。消灭疟疾 南亚，以及防止其进一步扩展到非洲的准备工作，取决于采取有效行动， 城市里的疾病我们知道温度对疟疾传播有很强的非线性影响。虽然 相对湿度对疟疾流行病学也有重要影响， 对它们的研究还远远不够，通常被认为与温度无关。与蚊子有关的小气候 进一步受到人口密度和景观特征的明显空间变化的影响， 城市环境导致疾病传播的强烈时空模式。因为这些 关系目前还没有得到很好的理解，我们有有限的能力来预测的出现，传播， 控制城市环境中的疟疾。我们的首要假设是湿度影响城市疟疾 通过改变温度-透射关系来提高透射率。此外，结合以下效果： 湿度将改善对疟疾传播和疟疾风险热点的预测， 传播的空间模式。我们建议的研究将通过以下方式解决这一知识差距 具体目标。目的1探讨湿度对温度-疟疾传播的影响 关系将进行全面的实验，以表征相对湿度 和温度对传播相关的蚊子和疟疾生活史性状的影响。这些机械 然后，将把这些关系纳入目标2和3中的疟疾流行病学时空模型。 目标2将制定和参数化一个时间耦合的人-蚊传播模型，用于预测 疟疾发病率和病媒丰度的季节性和年际变化。目标3将实施 利用气象资料预测城市环境中传播风险和发病率的空间模型 利用城市土地覆盖数据进行观测，绘制疟疾传播的环境适宜性地图。适用性 然后，地图将覆盖人口密度和社会经济因素，以预测 传输印度的两个城市，苏拉特和阿赫梅达巴德， 在过去的二十年里，我们一直保持着广泛的疟疾监测计划。 这两个城市将提供对比的机会来测试气候特征关系的能力， 目标1改善城市疟疾传播模式。主要成果包括： 基于蚊子生物学的城市疟疾环境流行病学框架和新模型 将这些知识应用于预测疾病传播的方法。预测未来 异常季节与确定热点相结合，将加强有针对性的公共卫生干预。

PROJECT SUMMARY / ABSTRACT With urban environments the fastest growing landscapes on the planet, transmission of vector-borne diseases by urban adapted mosquitoes has increased markedly over the past several decades. Urban vectors include Anopheles stephensi, the mosquito responsible for urban malaria across South Asia. Elimination of malaria in South Asia, and preparedness against its further expansion into Africa, hinges on effective action against the disease in cities. We know temperature has strong, non-linear effects on malaria transmission. Although relative humidity also has important effects on malaria epidemiology, its quantitative effects on transmission are vastly understudied and often treated as independent from temperature. Mosquito-relevant microclimates are further affected by pronounced spatial variation in human population densities and landscape features of urban environments resulting in strong temporal and spatial patterns of disease transmission. Because these relationships are currently not well understood, we have limited capacity to predict the emergence, spread, and control of malaria in urban environments. Our overarching hypothesis is that humidity affects urban malaria transmission by modifying the temperature-transmission relationship. Further, incorporating the effect of humidity will improve predictions of malaria transmission and hot spots of malaria risk in both temporal and spatial models of transmission. Our proposed research will address this knowledge gap through the following specific aims. Aim 1 will investigate the effects of humidity on the temperature-malaria transmission relationship. Comprehensive experiments will be conducted to characterize the effects of both relative humidity and temperature on mosquito and malaria life history traits relevant for transmission. These mechanistic relationships will then be integrated into temporal and spatial models of malaria epidemiology in Aims 2 and 3. Aim 2 will formulate and parameterize a temporal coupled human-mosquito transmission model used to predict the seasonal and interannual variation in malaria incidence and vector abundance. Aim 3 will implement a spatial model to predict transmission risk and incidence across urban environments by using meteorological observations with urban land cover data to map environmental suitability for malaria transmission. Suitability maps will then be overlaid with population density and socio-economic factors to predict hotspots for transmission. Two cities in India, Surat and Ahmedabad, experience notable differences in mean annual relative humidity and have maintained extensive surveillance malaria programs over the last two decades. These two cities will provide contrasting opportunities to test the ability of the climate-trait relationships from Aim 1 to improve transmission models of urban malaria. Major outcomes include an improved conceptual framework for the environmental epidemiology of urban malaria based on mosquito biology, and new modeling approaches that apply this knowledge to make predictions of disease transmission. Prediction of upcoming anomalous seasons combined with identification of hotspots will enhance targeted public health intervention.