Predicting undetected infections during the 2007 foot-and-mouth disease outbreak
Predicting undetected infections during the 2007 foot-and-mouth disease outbreak
复制标题
DOI：
10.1098/rsif.2008.0433
复制
发表时间：
2009-12-06
影响因子：
3.9
通讯作者：
Roberts, G. O.
中科院分区：
文献类型：
--
作者：
Jewell, C. P.;Keeling, M. J.;Roberts, G. O.
流行病期间的主动疾病监测对于快速发现和消除新病例至关重要，针对高风险个体进行此类监测被认为比采用随机策略更有效。接触者追踪已被用作高风险目标的一种形式，各种数学模型表明它可能非常有效。然而，对于快速传播的流行病，资源限制限制了当局有效执行和跟进接触者追踪的能力。作为替代方案，我们提出了一种新颖的实时贝叶斯统计方法来确定当前未检测到的（隐匿性）感染。对于 2007 年英国口蹄疫 (FMD) 疫情，我们使用根据英国 FMD 疫情之前的知识合成的实时疫情数据来预测在疫情爆发期间的任何时间点，哪些场所可能已被感染，但尚未被发现。这既提供了在资源有限的情况下进行有针对性的监测的框架，也提供了当前流行病严重程度和空间范围的指标。我们预计这种方法将在未来的疫情爆发中带来巨大好处，在有针对性的手动监测和随机或空间针对性策略之间提供折衷方案。
Active disease surveillance during epidemics is of utmost importance in detecting and eliminating new cases quickly, and targeting such surveillance to high-risk individuals is considered more efficient than applying a random strategy. Contact tracing has been used as a form of at-risk targeting, and a variety of mathematical models have indicated that it is likely to be highly efficient. However, for fast-moving epidemics, resource constraints limit the ability of the authorities to perform, and follow up, contact tracing effectively. As an alternative, we present a novel real-time Bayesian statistical methodology to determine currently undetected (occult) infections. For the UK foot-and-mouth disease (FMD) epidemic of 2007, we use real-time epidemic data synthesized with previous knowledge of FMD outbreaks in the UK to predict which premises might have been infected, but remained undetected, at any point during the outbreak. This provides both a framework for targeting surveillance in the face of limited resources and an indicator of the current severity and spatial extent of the epidemic. We anticipate that this methodology will be of substantial benefit in future outbreaks, providing a compromise between targeted manual surveillance and random or spatially targeted strategies.