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:
- Full document (version 1.0, pdf, July 2006) - includes all three chapters, introductory material, and glossary. Supporting appendices can be accessed below.
- Standards for key components of a surveillance system (Chapter 1) - this Chapter provides standards and guidelines to facilitate surveillance system planning and evaluation.
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Data standards for animal health management and surveillance programs (Chapter 2) - this Chapter provides guidelines for the types of data to collect for animal health management and surveillance programs and standards for data terminology and formatting.
- Disease/Condition Codes (appendix A) (pdf, July 2006)
- Subject (Animal) Taxonomy (appendix B) (pdf, May 2010) - this appendix provides value sets and guidelines for standardizing subject taxonomy concepts as Linnaean categories, and animal groups, breeds and strains.
- Subject (Animal) Descriptors (apppendix C) (pdf, January 2011) - this appendix provides value sets and guidelines for standardizing subject descriptors including polled status, color, color patterns, breed purpose, and size.
- Gender Codes (appendix E)(pdf, July 2006)
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Subject Use/Function Codes (appendix F) (pdf, May 2010) - This appendix provides the value set and guidelines for standardizing current subject use or
function (e.g., dairy, breeding, ornamental, zoo, and many other animal 'uses') - Sample Type Codes (appendix G) (pdf, July 2006)
- Result Interpretation Codes (appendix H) (pdf, July 2006)
- Geographic Data Element Standards (appendices K, L, M)- coordinate type codes, validation codes, and match source codes (pdf, July 2006)
- Standards for animal health database systems (Chapter 3) - this Chapter provides guidelines for developing information management systems to support surveillance programs.
Developing Animal Health Surveillance Plans
- Guidelines for Developing Animal Health Surveillance Plans (pdf, 10/1/06)
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
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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.