Surveillance of cattle health in the Netherlands: Monitoring trends and developments using routinely collected cattle census data.
Prev Vet Med 2016;
134:103-112. [PMID:
27836031 DOI:
10.1016/j.prevetmed.2016.10.002]
[Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Revised: 09/30/2016] [Accepted: 10/04/2016] [Indexed: 11/21/2022]
Abstract
Since 2002, a national cattle health surveillance system (CHSS) is in place that consists of several surveillance components. The CHSS combines enhanced passive reporting, diagnostic and post-mortem examinations, random surveys for prevalence estimation of endemic diseases and quarterly data analysis. The aim of the data-analysis component, which is called the Trend Analysis Surveillance Component (TASC), is to monitor trends and developments in cattle health using routine census data. The challenges that were faced during the development of TASC and the merits of this surveillance component are discussed, which might be of help to those who want to develop a monitoring and surveillance system that includes data analysis. When TASC was developed, there were process-oriented challenges and analytical related issues that had to be solved. Process-oriented challenges involved data availability, confidentiality, quality, uniformity and economic value of the data. Analytical issues involved data validation, aggregation and modeling. Eventually, the results had to provide information on cattle health that was intuitive to the stakeholders and that could support decision making. Within TASC, both quarterly analysis on census data and, on demand, additional in-depth analysis are performed. The key monitoring indicators that are analyzed as part of TASC all relate to cattle health and involve parameters such as mortality, fertility, udder health and antimicrobial usage. Population-Averaged Generalized Estimating Equations, with the appropriate distribution (i.e. Gaussian, Poisson, Negative Binomial or Binomial) and link function (independent, log or logit), are used for analysis. Both trends in time and associations between cattle health indicators and potential confounders are monitored, discussed and reported to the stakeholders on a quarterly level. The flexibility of the in-depth analyses provides the possibility to conduct additional analyses when anomalies in trends of cattle health occur or when developments in the cattle industry need further investigation. In addition, part of the budget for the in-depth analysis can also be used to improve the models or add new data sources. The TASC provides insight in cattle health parameters, it visualizes trends in time, can be used to support or nuance signals that are detected in one of the other surveillance components and can provide warnings or initiate changes in policy when unfavorable trends occur.
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