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Resources for Conducting Animal Health Surveillance

Resources for Conducting Animal Health Surveillance

Surveillance and Data Standards
Developing Animal Health Surveillance Plans
Evaluating Animal Health Surveillance Systems
Software and Documentation for Surveillance Applications

Surveillance and Data Standards

Surveillance and Data Standards for USDA APHIS Veterinary Services were developed by the Centers for Epidemiology and Animal Health (VS CEAH) in July 2006. These standards focused on (1) standards for key components of a surveillance system, (2) data standards for surveillance systems, and (3) information management system standards for surveillance systems. The full document or individual chapters or appendices may be downloaded below:

Developing Animal Health Surveillance Plans

Evaluating Animal Health Surveillance Systems

Surveillance system evaluation is the systematic collection and review of information about a surveillance system undertaken to assess the extent to which the system fulfills its stated objectives and meets accepted surveillance standards. Within Veterinary Services, the surveillance system evaluation process identifies program strengths and areas for improvement, and evaluation findings are intended to be a tool to improve program quality and efficiency, to facilitate integration of the system into the National Animal Health Surveillance system, and to identify the system’s contributions relative to the VS Strategic Plan. The Surveillance and Data Standards for USDA APHIS Veterinary Services (Chapter 1) are used as a benchmark for the evaluation process.

Software and Documentation for Surveillance Applications

  • Monte-Carlo approaches for determining power and sample size in low-prevalence applications: software module (.txt file, updated 5/14/07)

    Many epidemiological investigations focus on comparing the prevalence of a disease in an exposed and unexposed population, where the prevalence is low in both populations. Determination of the necessary sample size from each population requires consideration of the power to detect biologically relevant differences in the prevalence. Many of the existing solutions to this problem assume the distribution of the test statistic approaches a Normal distribution. However, in low-prevalence applications, this is rarely the case. This software module implements a Monte Carlo-based approach to determining the sample size from each population. A more detailed description can be found in: Williams, M. S., Ebel E. D., and Wagner, B. A. 2007. Monte-Carlo approaches for determining power and sample size in low-prevalence applications. Preventative Veterinary Medicine 81 (2007) 70-79.

 

 



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