An Integrated System for the Epidemiological Application of Earth Observation Tec

项目摘要 在这次更新申请中，我们将扩大我们正在进行的研究，我们成功地使用了 利用卫星遥感技术开发环境模型，以绘制和预测蚊媒 疾病风险。在目前的项目中，我们的首要目标是减少地球观测与地球物理之间的差距。 通过开发新的生物信息学技术和工具，促进生物技术和生物医学领域的发展。的 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， 通过将我们现有的环境监测系统与公共卫生监督直接联系起来，我们可以降低疟疾风险。 我们的总体假设是，一种综合的疾病预测方法， 早期预警（根据环境风险因素）和早期检测（根据疾病模式） 案例）将比单独使用任何一种方法都更有效，从而产生更准确的预测， 对公共卫生决策者有用。为了这次更新，我们选择把重点放在埃塞俄比亚人身上。 高地，因为我们相信这种疾病预测的方法有可能使一个 对本地区公共卫生决策的影响尤为显著。我们将解决以下问题 具体目标：战略领域1：开发一个用于疟疾流行预测的网络计算机系统， 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; SA 2：测试结合了联合收割机多个风险指标的新型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 疟疾流行病; SA 3：开发和测试用于上传监测数据和显示疟疾的接口 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。 综合评估疾病预后和环境监测（流行病） 计算机系统.该系统将把我们现有的环境监测EASTWeb软件与 疟疾监测数据自动提交、处理和汇总的新子系统。 新的算法将被开发和测试，以产生预测使用的组合环境 疟疾指标的风险因素和趋势，并将建立一个公共卫生界面，以便利数据收集 在低带宽环境中从终端用户获取结果并将结果传播给终端用户。流行病 该系统将在埃塞俄比亚阿姆哈拉地区的一个哨点网络中实施和测试 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。我们希望新的 通过这项研究获得的工具和科学知识最终将推广到其他地区， 改善对未来疟疾流行的预测，支持疟疾预防、控制和 最终消灭。

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.