ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics
ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics
复制标题
ORBiT：橡树岭公共卫生动态生物监测工具包
作者：
A. Ramanathan;L. Pullum;Tanner C. Hobson;C. Steed;Shannon P. Quinn;C. Chennubhotla;Silvia Valkova
通过电子健康记录（EHR）和电子医疗报销索赔实现健康相关信息的数字化，以及通过社交媒体自我报告的健康信息的持续增长，为开发有效的生物监测工具提供了巨大的机遇和挑战。随着世界各地不断报告新出现的传染病，有必要建立能够及时跟踪、监测和报告此类事件的系统。此外，确定新出现疾病可能产生重大影响的易感地理区域和人口也很重要。在本文中，我们介绍了橡树岭生物监测工具包（ORBiT）的概述，我们专门为解决公共卫生监测领域的数据分析挑战而开发了该工具包。特别是，ORBiT提供了一个可扩展的环境，将不同的大规模数据集聚集在一起，并对它们进行分析，以确定各种生物监测相关任务的空间和时间模式。我们展示了ORBiT在2009-2010年H1N1流感大流行季节使用索赔数据自动提取少量时空模式的实用性。这些模式为流感大流行如何在全国不同地区传播的动态提供了定量的见解。我们发现，索赔数据显示出多尺度模式，从中我们可以确定美国（US）的少数州作为“桥梁区域”，为一种或多种特定的流感传播模式做出贡献。与之前的研究类似，这些模式表明，美国东南部地区受到H1N1流感大流行的广泛影响。这些东南部州中的几个充当了桥梁地区，在流感发生方面连接了美国东北部和中部。这些定量分析表明，当流行病在全国蔓延时，索赔数据与新的分析技术相结合如何为决策者提供重要信息。综合起来，ORBiT为公共卫生监测提供了一个可扩展的平台。
The digitization of health-related information through electronic health records (EHR) and electronic healthcare reimbursement claims and the continued growth of self-reported health information through social media provides both tremendous opportunities and challenges in developing effective biosurveillance tools. With novel emerging infectious diseases being reported across different parts of the world, there is a need to build systems that can track, monitor and report such events in a timely manner. Further, it is also important to identify susceptible geographic regions and populations where emerging diseases may have a significant impact. In this paper, we present an overview of Oak Ridge Biosurveillance Toolkit (ORBiT), which we have developed specifically to address data analytic challenges in the realm of public health surveillance. In particular, ORBiT provides an extensible environment to pull together diverse, large-scale datasets and analyze them to identify spatial and temporal patterns for various biosurveillance-related tasks. We demonstrate the utility of ORBiT in automatically extracting a small number of spatial and temporal patterns during the 2009-2010 pandemic H1N1 flu season using claims data. These patterns provide quantitative insights into the dynamics of how the pandemic flu spread across different parts of the country. We discovered that the claims data exhibits multi-scale patterns from which we could identify a small number of states in the United States (US) that act as "bridge regions" contributing to one or more specific influenza spread patterns. Similar to previous studies, the patterns show that the south-eastern regions of the US were widely affected by the H1N1 flu pandemic. Several of these south-eastern states act as bridge regions, which connect the north-east and central US in terms of flu occurrences. These quantitative insights show how the claims data combined with novel analytical techniques can provide important information to decision makers when an epidemic spreads throughout the country. Taken together ORBiT provides a scalable and extensible platform for public health surveillance.
DOI：
10.4269/ajtmh.2012.11-0597
发表时间：
2012-01-01
影响因子：
3.3
作者：
Chunara, Rumi;Andrews, Jason R.;Brownstein, John S.
通讯作者：
Brownstein, John S.