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A model (BSurvE) for evaluating national surveillance programs for bovine spongiform encephalopathy
D J Prattley1, R S Morris, R M Cannon
1EpiCentre, Institute of Veterinary, Animal, and Biomedical Sciences, Massey University, Private Bag 11-222, Palmerston North, New Zealand. d.j.prattley@massey.ac.nz
Preventive Veterinary Medicine
|May 23, 2007
Summary
This study introduces the BSurvE model to estimate Bovine spongiform encephalopathy (BSE) prevalence in cattle. The model aids in designing cost-effective national surveillance programs by evaluating different testing strategies.
Area of Science:
- Veterinary epidemiology
- Animal health surveillance
- Risk assessment
Background:
- Bovine spongiform encephalopathy (BSE) poses a significant threat to cattle populations and public health.
- Effective national surveillance programs are crucial for early detection and control of BSE.
- Evaluating the efficiency of different surveillance strategies is essential for resource allocation.
Purpose of the Study:
- To develop and present the BSurvE spreadsheet model for estimating BSE prevalence in national cattle populations.
- To provide a tool for evaluating and comparing alternative strategies for national BSE surveillance programs.
- To rank surveillance tests based on their cost-effectiveness in detecting BSE.
Main Methods:
- Development of the BSurvE spreadsheet model.
- Assigning point values to individual surveillance tests based on demographic and epidemiological data.
- Calculating a target sum point value based on user-defined design prevalence, confidence level, and herd size.
- Ranking surveillance tests by points gained per unit cost.
Main Results:
- The BSurvE model provides a quantitative framework for estimating BSE prevalence.
- Individual surveillance tests are assigned point values reflecting their detection likelihood.
- A method for ranking tests by cost-effectiveness is established.
- The model facilitates the design of optimized national surveillance programs.
Conclusions:
- The BSurvE model is a valuable tool for designing and comparing national BSE surveillance strategies.
- Cost-effectiveness analysis of surveillance tests can guide resource allocation.
- The model supports informed decision-making for public health and animal safety.
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