Literature DB >> 27836031

Surveillance of cattle health in the Netherlands: Monitoring trends and developments using routinely collected cattle census data.

I M G A Santman-Berends1, H Brouwer-Middelesch2, L Van Wuijckhuise2, A J G de Bont-Smolenaars2, G Van Schaik3.   

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.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cattle health; Census data; Monitoring and surveillance systems; Trend analysis

Mesh:

Year:  2016        PMID: 27836031     DOI: 10.1016/j.prevetmed.2016.10.002

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  6 in total

1.  Monitoring and Surveillance of Small Ruminant Health in The Netherlands.

Authors:  Eveline Dijkstra; Piet Vellema; Karianne Peterson; Carlijn Ter Bogt-Kappert; Reinie Dijkman; Liesbeth Harkema; Erik van Engelen; Marian Aalberts; Inge Santman-Berends; René van den Brom
Journal:  Pathogens       Date:  2022-05-31

2.  Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle.

Authors:  Alberto L Barriuso; Gabriel Villarrubia González; Juan F De Paz; Álvaro Lozano; Javier Bajo
Journal:  Sensors (Basel)       Date:  2018-01-02       Impact factor: 3.576

3.  Zoonotic risks of pathogens from sheep and their milk borne transmission.

Authors:  René van den Brom; Aarieke de Jong; Erik van Engelen; Annet Heuvelink; Piet Vellema
Journal:  Small Rumin Res       Date:  2020-05-15       Impact factor: 1.611

4.  Control and Eradication Programs for Six Cattle Diseases in the Netherlands.

Authors:  I M G A Santman-Berends; M H Mars; M F Weber; L van Duijn; H W F Waldeck; M M Biesheuvel; K M J A van den Brink; T Dijkstra; J J Hodnik; S A J Strain; A de Roo; A M B Veldhuis; G van Schaik
Journal:  Front Vet Sci       Date:  2021-08-18

5.  Using routinely collected data to evaluate risk factors for mortality of veal calves.

Authors:  I M G A Santman-Berends; A J G de Bont-Smolenaars; L Roos; A G J Velthuis; G van Schaik
Journal:  Prev Vet Med       Date:  2018-05-25       Impact factor: 2.670

6.  Added Value of Meat Inspection Data for Monitoring of Dairy Cattle Health in the Netherlands.

Authors:  Anouk M B Veldhuis; Debora Smits; Martijn Bouwknegt; Heleen Worm; Gerdien van Schaik
Journal:  Front Vet Sci       Date:  2021-07-15
  6 in total

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