US/China Digital Government Collaboration: US-China Infectious Disease Informatics and BioSurveillance Workshop

该奖项将支持美国-中国的合作研讨会，以交流信息，并在传染病信息学的更大背景下制定综合征监测(定义如下)的研究议程。研讨会将于1997年底在北京中国举行，与会者包括美国和中国的研究人员和卫生从业人员，包括政府和学术专家。举办这一专题研讨会是适当的，因为人们越来越关注自然灾害或生物恐怖主义袭击造成的传染病的致命和代价高昂的威胁。需要新的方法来确定和跟踪新出现的传染病和流行病暴发。虽然传统的疾病监测往往依赖于耗时的实验室诊断，而且对应报告疾病的报告往往缓慢且不完整，但新型公共卫生监测系统有可能显著加快对疾病爆发的检测。这些新的、基于计算机的监测系统为医院以及州、地方和联邦卫生官员提供了有价值的及时信息。它们能够实时或接近实时地检测严重疾病和潜在的生物恐怖主义制剂暴露，从而能够对公共卫生做出快速反应。这种公共卫生监测方法通常被称为综合症监测，它被定义为“对针对‘综合征’的数据进行持续的、系统的收集、分析和解释，以便及早发现公共卫生异常。”症状监测背后的原理在于，可以通过可以及时显示的症状表现来监测感兴趣的特定疾病，例如护士电话、药品采购和学校或工作缺勤。除了早期发现和报告监测到的疾病外，综合征监测还提供了丰富的数据存储库和高度活跃的通信系统，以了解情况和确定事件特征。多个参与者提供不同和地理上分散的信息来源之间的相互联系，以促进对不断变化的局势的清楚了解。来自广泛背景的研究人员将参加，包括但不限于流行病学、统计学、应用数学、信息系统、计算机科学和机器学习/数据挖掘。大约有25人将参加。

This award will support a US-China collaborative workshop to exchange information and develop a research agenda for syndromic surveillance (defined below) within the larger context of infectious disease informatics. The workshop will take place in late 1997 in Beijing China, with attendees consisting equally of US and Chinese researchers and health practitioners, including government and academic experts. A workshop in this topic is appropriate because of increasing concern over the deadly and costly threats of infectious diseases caused by natural disasters or bioterrorism attacks. New methodologies are needed for identifying and tracking emerging infectious diseases and epidemic outbreaks. While traditional disease surveillance often relies on time-consuming laboratory diagnosis and the reporting of notifiable diseases is often slow and incomplete, a new breed of public health surveillance systems has the potential to significantly speed up detection of disease outbreaks. These new, computer-based surveillance systems offer valuable and timely information to hospitals as well as to state, local, and federal health officials. They are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures, allowing for a rapid public health response. This public health surveillance approach is generally called syndromic surveillance, which is defined as "an ongoing, systematic collection, analysis, and interpretation of 'syndrome'-specific data for early detection of public health aberrations." The rationale behind syndromic surveillance lies in the fact that specific diseases of interest can be monitored by syndromic presentations that can be shown in a timely manner such as nurse calls, medication purchases, and school or work absenteeism. In addition to early detection and reporting of monitored diseases, syndromic surveillance also provides a rich data repository and highly active communication system for situation awareness and event characterization. Multiple participants provide interconnectivity among disparate and geographically separated sources of information to facilitate a clear understanding of the evolving situation. Researchers from a wide range of backgrounds will participate, including but not limited to epidemiology, statistics, applied mathematics, information systems, computer science and machine learning/data mining. Approximately 25 individuals will participate.