Mackinnon Project, Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Australia; Asia-Pacific Centre for Animal Health, Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Australia.
Asia-Pacific Centre for Animal Health, Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Australia.
Prev Vet Med. 2021 Mar;188:105262. doi: 10.1016/j.prevetmed.2021.105262. Epub 2021 Jan 8.
The challenge of animal health surveillance is to provide the information necessary to appropriately inform disease prevention and control activities within the constraints of available resources. Syndromic surveillance of farmers' disease observations can improve animal health data capture from extensive livestock farming systems, especially where data are not otherwise being systematically collected or when data on confirmed aetiological diagnoses are unavailable at the disease level. As it is rarely feasible to recruit a truly random sample of farmers to provide observational reports, directing farmer sampling to align with the surveillance objectives is a reasonable and practical approach. As long as potential bias is recognised and managed, farmers who will report reliably can be desirable participants in a surveillance system. Thus, one early objective of a surveillance program should be to identify characteristics associated with reporting behaviour. Knowledge of the demographic and managerial characteristics of good reporters can inform efforts to recruit additional farms into the system or aid understanding of potential bias of system reports. We describe the operation of a farmer syndromic surveillance system in Victoria, Australia, over its first two years from 2014 to 2016. Survival analysis and classification and regression tree analysis were used to identify farm level factors associated with 'reliable' participation (low non-response rates in longitudinal reporting). Response rate and timeliness were not associated with whether farmers had disease to report, or with different months of the year. Farmers keeping only sheep were the most reliable and timely respondents. Farmers < 43 years of age had lower response rates than older farmers. Farmers with veterinary qualifications and those working full-time on-farm provided less timely reports than other educational backgrounds and farmers who worked part-time on-farm. These analyses provide a starting point to guide recruitment of participants for surveillance of farmers' observations using syndromic surveillance, and provide examples of strengths and weaknesses of syndromic surveillance systems for extensively-managed livestock. Once farm characteristics associated with reliable participation are known, they can be incorporated into surveillance system design in accordance with the objectives of the system.
动物健康监测的挑战在于，在可用资源的限制下，提供必要的信息，以适当告知疾病的预防和控制活动。对农民疾病观察的综合征监测可以改善从广泛的畜牧业系统中获取动物健康数据，特别是在没有系统地收集数据的情况下，或者在疾病层面上无法获得关于确诊病因诊断的数据的情况下。由于很少有可行的方法可以招募真正随机的农民样本提供观察报告，因此将农民抽样与监测目标对齐是一种合理且实用的方法。只要认识到并管理潜在的偏差，那些能够可靠报告的农民就可以成为监测系统的理想参与者。因此，监测计划的早期目标之一应该是确定与报告行为相关的特征。了解好的报告者的人口统计学和管理特征，可以为招募更多的农场进入系统提供信息，或者帮助理解系统报告的潜在偏差。我们描述了 2014 年至 2016 年期间澳大利亚维多利亚州的农民综合征监测系统在头两年的运作情况。生存分析和分类回归树分析用于确定与“可靠”参与（纵向报告中的低非响应率）相关的农场层面因素。响应率和及时性与农民是否有疾病报告或一年中的不同月份无关。只养羊的农民是最可靠和最及时的回应者。年龄<43 岁的农民比年长的农民响应率低。具有兽医资格的农民和全职农场工人比其他教育背景和兼职农场工人的报告及时性更差。这些分析为使用综合征监测招募农民观察监测的参与者提供了一个起点，并为广泛管理的牲畜的综合征监测系统的优势和劣势提供了示例。一旦知道了与可靠参与相关的农场特征，就可以根据系统的目标将其纳入监测系统设计中。
