AusVet Animal Health Services, 140 Falls Road, Wentworth Falls, 2782, NSW, Australia.
Prev Vet Med. 2012 Aug 1;105(4):280-6. doi: 10.1016/j.prevetmed.2012.01.009. Epub 2012 Feb 3.
Output-based surveillance standards provide a mechanism to achieve harmonised and comparable surveillance (which meets a defined objective) while allowing flexible approaches that are adapted to the different populations under surveillance. When correctly implemented, they can result in lower cost and greater protection against disease spread. This paper presents examples of how risk-based sampling can improve the efficiency of surveillance, and describes the evolution of output-based surveillance standards for demonstration of freedom from disease in terms of three generations of approach: surveillance sensitivity, probability of freedom, and expected cost of error. These three approaches progressively capture more of the factors affecting the final outcome. The first two are relatively well accepted but the third is new and relates to the consequences of infection. There has been an increased recognition of the value of risk-based sampling for demonstration of freedom from disease over the last decades, but there has been some disagreement about practical definitions and implementation, in particular as to whether 'risk-based' implies probability of infection or probability and consequences. This paper argues that risk-based sampling should be based solely on the probability of infection of a unit within the population, while the consequences of infection should be used to set the target probability of freedom. This approach provides a quantitative framework for planning surveillance which is intuitively understandable. The best way to find disease, if it is present, is to focus on those units that are most likely to be infected. However, if the purpose of surveillance includes mitigating the risk of a disease outbreak, we want to ensure that that risk is smallest in those populations where the consequences of failure to detect are greatest.
基于产出的监测标准提供了一种机制，可以实现协调和可比的监测（符合既定目标），同时允许采用灵活的方法，适应不同的监测人群。如果正确实施，它们可以降低成本，并更有效地防止疾病传播。本文介绍了基于风险的抽样如何提高监测效率的实例，并描述了基于产出的监测标准在疾病消除证明方面的三代方法的演变：监测敏感性、无病概率和错误预期成本。这三种方法逐步纳入了更多影响最终结果的因素。前两种方法已经得到了相对广泛的认可，而第三种方法则是新的，与感染的后果有关。在过去几十年中，人们越来越认识到基于风险的抽样对于疾病消除证明的价值，但在实践定义和实施方面存在一些分歧，特别是在“基于风险”是指感染概率还是概率和后果方面。本文认为，基于风险的抽样应该仅基于群体内单位的感染概率，而感染的后果应用于设定无病的目标概率。这种方法为规划监测提供了一个直观易懂的定量框架。如果存在疾病，最好的发现方法是关注最有可能感染的单位。但是，如果监测的目的包括减轻疾病爆发的风险，我们希望确保在检测失败后果最大的人群中，风险最小。
