Epidemiology and Surveillance Section, Canadian Food Inspection Agency, Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, 550 University Avenue, Charlottetown, PEI C1A 4P3, Canada.
Canadian Food Inspection Agency, 3200 rue Sicotte, C.P. 5000 Saint Hyacinthe, Quebac, Canada.
Prev Vet Med. 2014 May 1;114(2):132-44. doi: 10.1016/j.prevetmed.2014.01.023. Epub 2014 Feb 14.
Scenario tree models with temporal discounting have been applied in four continents to support claims of freedom from animal disease. Recently, a second (new) model was developed for the same population and disease. This is a natural development because surveillance is a dynamic process that needs to adapt to changing circumstances - the difficulty is the justification for, documentation of, presentation of and the acceptance of the changes. Our objective was to propose a systematic approach to present changes to an existing scenario tree model for freedom from disease. We used the example of how we adapted the deterministic Canadian Notifiable Avian Influenza scenario tree model published in 2011 to a stochastic scenario tree model where the definition of sub-populations and the estimation of probability of introduction of the pathogen were modified. We found that the standardized approach by Vanderstichel et al. (2013) with modifications provided a systematic approach to make and present changes to an existing scenario tree model. We believe that the new 2013 CanNAISS scenario tree model is a better model than the 2011 model because the 2013 model included more surveillance data. In particular, the new data on Notifiable Avian Influenza in Canada from the last 5 years were used to improve input parameters and model structure.
情景树模型结合了时间折扣，已在四大洲被用于支持免除动物疾病的主张。最近，针对同一人群和疾病，又开发了第二种（新的）模型。这是自然的发展，因为监测是一个动态的过程，需要适应不断变化的情况——困难在于对变化的合理性、记录、呈现和接受。我们的目的是提出一种系统的方法来展示对现有疾病自由情景树模型的更改。我们以如何调整 2011 年发布的加拿大可报告禽流感确定性情景树模型为例，将其改编为随机情景树模型，其中修改了亚人群的定义和病原体传入概率的估计。我们发现，Vanderstichel 等人（2013 年）的标准化方法经过修改后，可以系统地对现有情景树模型进行更改和呈现。我们认为，新的 2013 年 CanNAISS 情景树模型比 2011 年的模型更好，因为 2013 年的模型纳入了更多的监测数据。特别是，使用了过去 5 年加拿大可报告禽流感的新数据来改进输入参数和模型结构。
