High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery
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DOI：
10.1371/journal.pntd.0007105
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发表时间：
2019-01-01
影响因子：
3.8
通讯作者：
Gamboa, Dionicia
中科院分区：
文献类型：
--
作者：
Carrasco-Escobar, Gabriel;Manrique, Edgar;Gamboa, Dionicia
近年来，人们对幼虫源管理（LSM）作为控制和消除疟疾传播的辅助干预措施的兴趣日益增加，主要是因为长效杀虫蚊帐（LLINs）和室内残留喷雾（IRS）对嗜外性和嗜外性蚊子无效。在亚马逊流域的秘鲁，确定最具生产力的积极水体将增加对水生生物阶段有针对性的蚊虫控制的影响。本研究探讨了利用无人机在秘鲁亚马逊地区利用高分辨率图像（0.02m/像素）及其多光谱剖面识别达林按蚊（Nyssorhynchus darlingi，原达林按蚊）的繁殖地点。我们的研究结果表明，高分辨率的多光谱图像可以区分出Ny的水体剖面。达林吉星的繁殖精度为86.73% ~ 96.98%，光谱波段分化适中。这项工作提供了使用高分辨率图像检测亚马逊秘鲁疟疾媒介滋生地点的概念证明，这种创新方法可能对LSM疟疾综合干预至关重要。拉丁美洲地区最有效的疟疾媒介是达林按蚊（Nyssorhynchus darlingi）。在亚马逊流域的秘鲁，疟疾是一种地方性疾病。达林吉在室内和室外进食（内食，外食），取决于当地的环境，在室外休息（外食）。LLINs和IRS是病媒控制最常用的工具，针对的是自噬性和嗜内性蚊子。因此，它们对Ny仅部分有效。darlingi。病媒蚊子水生阶段的控制，即幼虫源管理（LSM），以最接近人类居住地的最高产繁殖地点为目标。在四个河流社区，我们使用具有高分辨率图像的无人机作为关键的初始步骤，以分析纽约估计飞行范围内的水体。达林吉，1公里。我们发现了不同的水体光谱剖面，它们对Ny呈阳性，对Ny呈阴性。darlingi。本文报告的方法和分析为检验LSM能否与LLINs和IRS成功结合，从而有助于消除亚马逊地区疟疾热点地区的传播提供了基础。
Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Peru, the identification of the most productive, positive water bodies would increase the impact of targeted mosquito control on aquatic life stages. The present study explores the use of unmanned aerial vehicles (drones) for identifying Nyssorhynchus darlingi (formerly Anopheles darlingi) breeding sites with high-resolution imagery ( 0.02m/pixel) and their multispectral profile in Amazonian Peru. Our results show that high-resolution multispectral imagery can discriminate a profile of water bodies where Ny. darlingi is most likely to breed (overall accuracy 86.73%- 96.98%) with a moderate differentiation of spectral bands. This work provides proof-of-concept of the use of high-resolution images to detect malaria vector breeding sites in Amazonian Peru and such innovative methodology could be crucial for LSM malaria integrated interventions.Author summary The most efficient malaria vector in the Latin American region is Nyssorhynchus darlingi (formerly Anopheles darlingi). In Amazonian Peru, where malaria is endemic, Ny. darlingi feeds both indoors and outdoors (endophagy, exophagy), depending on the local environment, and rests outdoors (exophily). LLINs and IRS, the most common tools employed for vector control, target endophagic and endophilic mosquitoes. Thus, they are only partially effective against Ny. darlingi. Control of the aquatic stages of vector mosquitoes, larval source management (LSM), targets the most productive breeding sites nearest to human habitation. In four riverine communities, we used drones with high-resolution imagery as a key initial step to analyze water bodies within the estimated flight range of Ny. darlingi, 1 km. We found distinctive spectral profiles for water bodies that were positive versus negative for Ny. darlingi. The methodology and analysis reported here provide the basis for testing whether LSM can be combined successfully with LLINs and IRS to contribute to the elimination of transmission in malaria hotspots in the Amazon.