National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30333, USA,
Ecohealth. 2013 Sep;10(3):298-313. doi: 10.1007/s10393-013-0856-0. Epub 2013 Aug 6.
The ecology of infectious disease in wildlife has become a pivotal theme in animal and public health. Studies of infectious disease ecology rely on robust surveillance of pathogens in reservoir hosts, often based on serology, which is the detection of specific antibodies in the blood and is used to infer infection history. However, serological data can be inaccurate for inference to infection history for a variety of reasons. Two major aspects in any serological test can substantially impact results and interpretation of antibody prevalence data: cross-reactivity and cut-off thresholds used to discriminate positive and negative reactions. Given the ubiquitous use of serology as a tool for surveillance and epidemiological modeling of wildlife diseases, it is imperative to consider the strengths and limitations of serological test methodologies and interpretation of results, particularly when using data that may affect management and policy for the prevention and control of infectious diseases in wildlife. Greater consideration of population age structure and cohort representation, serological test suitability and standardized sample collection protocols can ensure that reliable data are obtained for downstream modeling applications to characterize, and evaluate interventions for, wildlife disease systems.
野生动物传染病生态学已成为动物和公共卫生的一个关键主题。传染病生态学的研究依赖于对宿主中病原体的强有力监测，通常基于血清学，即检测血液中的特定抗体，用于推断感染史。然而，由于各种原因，血清学数据在推断感染史时可能不准确。任何血清学检测中两个主要方面都会极大地影响抗体流行数据的结果和解释：交叉反应和用于区分阳性和阴性反应的截止值。鉴于血清学作为野生动物疾病监测和流行病学建模的工具的广泛应用，考虑血清学检测方法的优缺点以及结果的解释至关重要，特别是当使用可能影响野生动物传染病预防和控制的管理和政策的数据时。更多地考虑种群年龄结构和队列代表性、血清学检测适用性以及标准化样本采集协议，可以确保为下游建模应用程序获得可靠的数据，以对野生动物疾病系统进行描述和评估干预措施。
