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

描述（由申请人提供）：肌萎缩侧索硬化症（ALS）是一种进行性、致死性神经退行性疾病，年轻人的终生风险为1/400（Armon 2007）。ALS患者的平均预期寿命为2至5年，每年诊断出5，600例新病例。发病率在工业化国家（年发病率为每100 000人0.2 - 2.4）和发展中国家（每年每100 000人1.5-2.0）各不相同。有证据表明，蓝细菌和ALS集群之间存在潜在联系（布拉德利等人，2013年）。蓝细菌普遍存在于所有生态系统中，当水体人为富营养化导致大量浓度形成“水华”时，蓝细菌特别有害。众所周知，蓝细菌会产生对人类健康有影响的急性和慢性毒素。在推进我们的理解蓝藻水华，毒性和ALS之间的联系的主要障碍是缺乏信息的存在，范围，规模和强度的有害藻华（HABs）和水质在水体中。目标：该NIH SBIR第二阶段的创新是开发可操作的水质和蓝藻风险地图，该地图利用多尺度卫星遥感平台来驱动生态流行病学模型，以评估水质和ALS之间的联系。方法：我们将应用业务波段比和形状滤波算法的多尺度卫星遥感数据。我们将利用陆地卫星，MERIS和中分辨率成像光谱仪进行缩放的方法。空间回归，聚类和先进的地质统计学将建立一个生态流行病学模型来映射ALS的危险因素和水质和ALS病例之间的关系。预期成果1。业务湖泊蓝藻和水质暴露地图和风险度量2。生态流行病学模型框架的发展，以评估水质和ALS之间的联系。第二阶段将为加州、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。3.使用开源技术为第二阶段研究区域内所有大于8公顷的湖泊构建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的应用程序。

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.