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: 8708353
• 负责人: MICHAEL C WIMBERLY
• 金额: $ 29.41万
• 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: 2008-08-12 至 2013-12-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8708353
• 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; Feedback; Future; Goals; 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; remote sensing; response; surveillance data; tool; transmission process; trend

DESCRIPTION (provided by applicant): 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 t 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.

描述（由申请人提供）：在本次更新申请中，我们将扩展我们正在进行的研究，在该研究中，我们成功地利用卫星遥感开发了用于绘制和预测蚊媒疾病风险的环境模型。与当前项目一样，我们的首要目标是通过开发新型生物信息学技术和工具来缩小地球观测技术与生物医学领域之间的差距。我们新项目的具体目标是通过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，扩展我们在环境建模和疟疾风险预测方面的工作。我们的总体假设是，结合早期预警（基于环境风险因素）和早期检测（基于疾病病例模式）要素的疾病预测综合方法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。对于这次更新，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可能对该地区的公共卫生决策产生特别重大的影响。我们将实现以下具体目标： SA1：开发基于网络的疟疾流行病预测计算机系统，将疟疾病例的流行病学监测与地球观测卫星的环境监测数据相结合； SA2：测试新颖的建模和决策支持方法，结合基于季节性气候异常的多种风险指标、对环境变化的滞后反应以及疟疾流行的早期发现； SA3：开发和测试用于在低带宽环境中上传监测数据和可视化疟疾风险指标的接口。我们将通过开发结合疾病和环境监测的流行病预后综合评估（EPIDEMIA）计算机系统来实现这些目标。该系统将把我们现有的用于环境监测的 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连接起来。将开发和测试新的算法，以结合环境风险因素和疟疾指标趋势来生成预测，并将创建公共卫生界面，以促进低带宽环境中最终用户的数据采集和结果传播。 EPIDEMIA 系统将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，在埃塞俄比亚阿姆哈拉地区的哨点网络进行实施和测试。我们预计通过这项研究获得的新工具和科学知识最终将扩展到其他地区，以改善对未来疟疾流行病的预测，支持疟疾预防、控制和最终消除的努力。