An Integrated System for the Epidemiological Application of Earth Observation Tec

对地观测技术流行病学应用综合系统

• 批准号: 8629907
• 负责人: MICHAEL C WIMBERLY
• 金额: $ 14.47万
• 依托单位: SOUTH DAKOTA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-15 至 2018-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8629907
• 关键词: Address; Africa South of the Sahara; Algorithms; Archives; Atlases; Bioinformatics; Biomedical Technology; Climate; Collection; Communicable Diseases; Communities; Computer Systems; Computer software; Culicidae; Data; Databases; Decision Making; Decision Support Model; Development; Disease; Disease Outbreaks; Early Diagnosis; Elements; Environment; Environmental Monitoring; Environmental Risk Factor; Epidemic; Epidemiology; Ethiopia; Future; Goals; Habitats; Health; Human; Information Systems; Internet; Knowledge; Link; Location; Malaria; Malaria prevention; Maps; Modeling; Mosquito-borne infectious disease; Online Systems; Pattern; Population; Population Surveillance; Process; Public Health; Public Health Informatics; Research; Resolution; Resources; Risk; Seasons; Sentinel; Site; System; Techniques; Testing; Time; United States; Virus Diseases; West Nile virus; Work; base; burden of illness; data acquisition; disorder risk; improved; indexing; new technology; novel; outcome forecast; public health relevance; remote sensing; response; surveillance data; tool; transmission process; trend

Project Summary In this renewal application, we will expand upon our ongoing research in which we successfully used satellite remote sensing to develop environmental models for mapping and forecasting mosquito-borne disease risk. As in the current project, our overarching goal is to reduce the gap between earth observation technologies and the biomedical fields by developing novel bioinformatics techniques and tools. The specific objective of our new project is to extend our work on the environmental modeling and forecasting of malaria risk by directly linking our existing environmental monitoring system with public health surveillance. Our overarching hypothesis is that an integrated approach to disease forecasting that combines elements of early warning (based on environmental risk factors) and early detection (based on patterns of disease cases) will be more effective than either approach alone, resulting in more accurate predictions that are useful to public health decision makers.. For this renewal we have chosen to focus on the Ethiopian Highlands because we believe that this approach to disease forecasting has the potential to make a particularly significant impact on public health decision-making in this region. We will address the following specific aims: SA1: Develop a web-based computer system for malaria epidemic forecasting that integrates epidemiological surveillance of malaria cases with environmental monitoring data from earth observing satellites; SA2: Test novel modeling and decision support approaches that combine multiple risk indicators based on seasonal climatic anomalies, lagged responses to environmental variability, and early detection of malaria epidemics; SA3: Develop and test interfaces for uploading surveillance data and visualizing malaria risk indicators in low-bandwidth environments. We will achieve these aims by developing the Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) computer system. This system will link our existing EASTWeb software for environmental monitoring with new subsystems for automated submission, processing, and summarization of malaria surveillance data. Novel algorithms will be developed and tested to generate forecasts using a combination of environmental risk factors and trends in malaria indicators, and a public health interface will be created to facilitate data acquisition from and dissemination of results to end users in low bandwidth environments. The EPIDEMIA system will be implemented and tested at a network of sentinel sites in the Amhara region of Ethiopia through our existing partnerships with the regional health bureau and a local NGO. We expect that the new tools and scientific knowledge gained through this research will ultimately be extendible to other regions to improve forecasting of future malaria epidemics support efforts toward malaria prevention, control, and ultimately elimination.

项目概要 在此更新应用程序中，我们将扩展我们正在进行的研究，其中我们成功地使用了 卫星遥感开发用于绘制和预测蚊媒传播的环境模型 疾病风险。与当前项目一样，我们的首要目标是缩小地球观测之间的差距 通过开发新颖的生物信息学技术和工具来推动技术和生物医学领域的发展。这 我们新项目的具体目标是扩展我们在环境建模和预测方面的工作 将我们现有的环境监测系统与公共卫生监测直接联系起来，从而降低疟疾风险。 我们的首要假设是，一种综合的疾病预测方法结合了以下要素： 早期预警（基于环境风险因素）和早期发现（基于疾病模式） 情况）将比单独使用任何一种方法更有效，从而产生更准确的预测 对公共卫生决策者有用。对于本次更新，我们选择重点关注埃塞俄比亚 高地，因为我们相信这种疾病预测方法有潜力使 对该地区的公共卫生决策产生特别重大的影响。我们将解决以下问题 具体目标： SA1：开发一个基于网络的疟疾流行病预测计算机系统，该系统集成了 利用地球观测环境监测数据对疟疾病例进行流行病学监测 卫星； SA2：测试结合多个风险指标的新颖建模和决策支持方法 基于季节性气候异常、对环境变化的滞后反应以及早期发现 疟疾流行； SA3：开发和测试用于上传监测数据和可视化疟疾的接口 低带宽环境中的风险指标。我们将通过发展流行病来实现这些目标 结合疾病和环境监测进行综合评估的预后 (EPIDEMIA) 计算机系统。该系统将把我们现有的环境监测 EASTWeb 软件与 用于自动提交、处理和总结疟疾监测数据的新子系统。 将开发和测试新的算法，以结合环境因素生成预测 将创建疟疾指标的风险因素和趋势以及公共卫生界面以促进数据的获取 在低带宽环境中从最终用户获取结果并将其传播给最终用户。流行病 系统将在埃塞俄比亚阿姆哈拉地区的哨点网络上实施和测试 通过我们与地区卫生局和当地非政府组织的现有合作伙伴关系。我们期望新的 通过这项研究获得的工具和科学知识最终将扩展到其他地区 改进对未来疟疾流行病的预测，支持疟疾预防、控制和预防工作 最终消除。