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）：在此续签申请中，我们将扩展我们正在进行的研究，我们成功地使用卫星遥感来开发环境模型，以绘制和预测蚊子 - 传播疾病风险。与当前项目一样，我们的总体目标是通过开发新颖的生物信息学技术和工具来减少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视直接联系起来，扩展我们在环境建模和预测疟疾风险方面的工作。我们的总体假设是，结合了预警的要素（基于环境风险因素）和早期检测（基于疾病案例的模式）的疾病预测方法比单独使用的方法更有效，从而对任何一种方法都更有效，从而导致对公共卫生决策者的更准确的预测，因为我们已经选择了这一方法，因为我们已经选择了这一方法，因为我们已经选择了这一方法，因为我们选择了这一方法。关于该地区的公共卫生决策。我们将解决以下特定目的：SA1：开发基于网络的计算机系统，用于疟疾流行病预测，该系统将疟疾病例的流行病学监测与环境监测卫星的数据相结合； SA2：测试新颖的建模和决策支持方法，这些方法结合了基于季节性气候异常，对环境变异性的滞后响应以及疟疾流行病的早期检测的滞后反应； SA3：开发和测试界面，用于上传监视数据并在低频带宽度环境中可视化疟疾风险指标。我们将通过开发综合疾病和环境监测的流行病预后来实现这些目标，以进行综合评估（流行病）计算机系统。该系统将将我们现有的EASTWEB软件与新的子系统联系起来，以自动提交，处理和汇总疟疾监视数据。将开发和测试新颖的算法，以结合疟疾指标的环境风险因素和趋势来产生预测，并将创建公共卫生界面，以促进低带宽环境中T最终用户的数据获取和传播。流行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兵站点网络上实施和测试。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，以支持预防疟疾，控制和最终消除的疟疾。