Canada West Swine Health Intelligence Network (CWSHIN) Inc., Winnipeg, Manitoba, Canada; Epidemiologic Surveillance and Analysis Consulting (EpiSAC), Charlottetown, Prince Edward Island, Canada.
Canada West Swine Health Intelligence Network (CWSHIN), Winnipeg, Manitoba, Canada.
Prev Vet Med. 2021 Sep;194:105444. doi: 10.1016/j.prevetmed.2021.105444. Epub 2021 Jul 24.
The Canada West Swine Health Intelligence Network (CWSHIN) is a surveillance system imbedded in an intelligence network. It has been conducting syndromic surveillance in the four western provinces of Canada since 2012. The quarterly activities include repeated clinical impression surveys, compilation of laboratory data, discussion of trends with an expert group (practitioners, laboratory diagnosticians) and swine health reports for producers and swine practitioners. However, due to the lack of standardized population identifiers across data sources usual methods of combining data could not be applied and the collated data were not being fully utilized and analysed. Therefore in 2019, CWSHIN underwent a substantial review resulting in the "Next Generation CWSHIN". The objectives of this study were to develop and evaluate a new data merging method to combine CWSHIN's clinical impression survey and laboratory data; and to provide examples of analyses and modeling based on these data. The data for analysis were restricted to repeated clinical impression surveys (2019-2020) from veterinary practitioners and laboratory diagnostic data (2016-2020). Merging surveillance data from existing sources can be challenging. Therefore, as an alternative to merge data using a hierarchy of population identifiers, we developed a Disease Map to link surveillance data from all our data-sources. The resulting Data Repository allowed monitoring of temporal trends of syndromes, clinical diseases, and laboratory identified organisms, but it cannot provide estimates of disease occurrence. Two main reasons were the lack of denominators and using existing data on routine diagnostic tests. Therefore, discussion in the expert group (veterinary practitioners, laboratory diagnosticians, swine health experts) was critical to the system's success. Based on repeated clinical impression surveys a stochastic scenario tree model for freedom from Foot and Mouth Disease (CWSHIN Blister model) was also developed. In conclusion, the method to link existing data systems from multiple divergent sources by means of a Disease Map improved CWSHIN's veterinary syndromic surveillance. Together the Data Repository and Disease map provided flexibility to monitor temporal trends, define populations and diseases, and allow analysis. However, it is critical that the surveillance is coupled with a good intelligence network that can help interpret the results and disseminate knowledge to veterinarians and producers.
加拿大西部猪健康情报网络（CWSHIN）是一个嵌入情报网络的监测系统。自 2012 年以来，它一直在加拿大四个西部省份开展综合征监测。季度活动包括重复临床印象调查、实验室数据汇编、与专家组（从业者、实验室诊断员）讨论趋势以及为生产者和养猪从业者提供猪健康报告。然而，由于各数据源之间缺乏标准化的人口标识符，通常的数据合并方法无法应用，整理后的数据也未得到充分利用和分析。因此，2019 年，CWSHIN 进行了重大审查，结果是“下一代 CWSHIN”。本研究的目的是开发和评估一种新的数据合并方法，以合并 CWSHIN 的临床印象调查和实验室数据；并提供基于这些数据的分析和建模示例。分析数据仅限于兽医从业者的重复临床印象调查（2019-2020 年）和实验室诊断数据（2016-2020 年）。合并现有来源的监测数据可能具有挑战性。因此，作为使用人口标识符层次结构合并数据的替代方法，我们开发了一种疾病图谱来链接我们所有数据源的监测数据。由此产生的数据库允许监测综合征、临床疾病和实验室鉴定生物的时间趋势，但不能提供疾病发生的估计。主要有两个原因：缺乏分母和使用常规诊断测试的现有数据。因此，专家组（兽医从业者、实验室诊断员、猪健康专家）的讨论对系统的成功至关重要。基于重复的临床印象调查，还开发了一种无口蹄疫（CWSHIN 水疱模型）的随机情景树模型。总之，通过疾病图谱将来自多个不同来源的现有数据系统连接起来的方法改进了 CWSHIN 的兽医综合征监测。数据库和疾病图谱一起提供了灵活性，可以监测时间趋势、定义人群和疾病，并允许进行分析。然而，至关重要的是，监测必须与良好的情报网络相结合，以帮助解释结果并将知识传播给兽医和生产者。
