CyanoMap: Mapping inland lake quality and Amyotrophic lateral sclerosis risk fact

描述（由申请人提供）：肌萎缩性侧索硬化症（ALS）是一种进行性、致命性的神经退行性疾病，年轻成人的终生风险为400分之一（Armon 2007）。ALS患者的平均预期寿命为2 - 5年，每年有5600例新病例被诊断出来。工业化国家的发病率（每10万人每年发病率为0.2至2.4）与发展中国家的发病率（每10万人每年发病率为1.5至2.0）各不相同。有证据表明蓝藻与ALS集群之间存在潜在联系（Bradley et al. 2013）。蓝藻在所有生态系统中无处不在，当人为水体富营养化导致高浓度形成“水华”时，蓝藻尤其有害。众所周知，蓝藻会产生对人体健康有影响的急性和慢性毒素。推进我们对蓝藻华、毒性和ALS之间联系的理解的主要障碍是缺乏关于水体中有害藻华（HABs）和水质的存在、程度、幅度和强度的信息。目标：NIH SBIR第二阶段的创新是开发可操作的水质和蓝藻风险图，利用多尺度卫星遥感平台驱动生态流行病学模型来评估水质与ALS之间的联系。方法：将运算带比和形状滤波算法应用于多尺度卫星遥感数据。我们将利用Landsat、MERIS和MODIS进行规模化处理。采用空间回归、聚类和先进地统计学等方法构建生态流行病学模型，绘制ALS危险因素图，刻画水质与ALS发病的关系。预期结果操作湖蓝藻和水质暴露图和风险指标2。开发生态流行病学模型框架，以评估水质与ALS之间的联系。第二阶段将为加利福尼亚、新英格兰和佛罗里达的公共卫生机构开发三个独特而多样的案例研究模型。使用开源技术为最终用户建立和运营最先进的湖泊水质和健康风险网络地图服务和移动应用程序，覆盖第二阶段研究区域的所有湖泊，面积为808公顷。

DESCRIPTION (provided by applicant): Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease with a lifetime risk of 1 in 400 for a young adult (Armon 2007). The average life expectancy of a person with ALS is two to five years from time of diagnosis with 5,600 new cases diagnosed per year. Incidence rates vary in industrialized nations (an annual incidence rate of 0.2 to 2.4 per 100,000 population), to that in developing countries (1.5-2.0 per 100,000 per year). Evidence has shown potential linkages between cyanobacteria and ALS clusters (Bradley et al. 2013). Cyanobacteria are ubiquitous throughout all ecosystems and are particularly noxious when anthropogenic eutrophication of water-bodies causes large concentrations to form "blooms". Cyanobacteria are well-known to produce acute and chronic toxins that have human health implications. A primary obstacle in advancing our understanding of linkages between cyanobacteria blooms, toxicity, and ALS is a lack of information on the presence, extent, magnitude, and intensity of harmful algal blooms (HABs) and water quality in water bodies. Goal: The innovation of this NIH SBIR Phase II is the development of operational water quality and cyanobacteria risk maps that utilize multiscale satellite remote sensing platforms to drive an eco- epidemiological model for evaluating linkages between water quality and ALS. Approach: We will apply operational band ratio and shape filter algorithms to multiscale satellite remote sensing data. We will utilize Landsat, MERIS, and MODIS to have scaled approach. Spatial regression, clustering, and advanced geostatistics will be employed to build an eco-epidemiological model to map ALS risk factors and characterize the relationship between water quality and ALS cases. Expected Outcomes 1. Operational lake cyanobacteria and water quality exposure maps and risk metrics 2. Development of eco-epidemiological modeling framework for evaluating linkages between water quality and ALS. Phase II will develop model for three unique and diverse case studies for public health agencies in California, New England, and Florida. 3. Build and operate state-of-the-art lake water quality and health risk web mapping services and mobile app for all lakes >8 hectares in Phase II study areas for end users using open source technology.