Improvement of survey and sampling methods to document freedom from diseases in Danish cattle population on both national and herd level

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Downloaded from orbit.dtu.dk on: Dec 17, 2017 Improvement of survey and sampling methods to document freedom from diseases in Danish cattle population on both national and herd level Salman, M.; Chriél, Mariann Publication date: 2002 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Salman, M., & Chriél, M. (2002). Improvement of survey and sampling methods to document freedom from diseases in Danish cattle population on both national and herd level. Dansk Fødevareforskning. (EpiLab report). General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Introductory Seminar Improvement of survey and sampling methods to document freedom from diseases in Danish cattle population on both national and herd levels Mo Salman Professor of Veterinary Epidemiology Colorado State University, Colorado, USA (m.d.salman@colostate.edu) Mariann Chriel Veterinarian, Danish Cattle (mc@meatboard.dk)

Disease Freedom in DK Theme 1 --- International EpiLab Aim is to initiate and validate a guideline for declaring a country free from a disease using existing survey and surveillance sources

Why important? Increased trade (exports and imports) animals and animal products More countries (regions) interested in new trade opportunities need for policy decisions based on scientifically-sound risk analyses

Disease Freedom in DK Three projects are closely related Cooperatively develop consistent approach for establishing disease freedom Each project concentrates on developing specific approaches/strategies of the overall methods Apply the approaches in three livestock systems (Poultry, Swine, and Cattle)

Definition Disease freedom commonly-used term but we really mean Absence of the Pathogen (free from pathogen)

Definition Free from a pathogen note that in some countries it actually means a herd prevalence < threshold value e.g. IBR free areas in the EU threshold is <0.2% (2 in 1000) positive herds

Freedom all species? Free from a pathogen Free from a pathogen strictest sense means absence of the pathogens from animals, the environment, and potential wildlife reservoirs

Demonstration of disease freedom Proof theoretically requires Perfectly sensitive test Testing of all animals in a country, region, state, zone etc Absolute proof is unrealistic

Evidence of disease freedom Evidence provided to trading partners who make judgements Importing countries make judgements about trade (animals and animal products) no trade trade with mitigations unrestricted trade

Evidence of disease freedom Based on considerations such as: Surveillance system neg. results Population survey that yields neg. results Other factors Awareness of producers, preparedness of practitioners, quality of vet services, lab system, historic performance in detection of disease, other disease risks

Two scenarios. 1. Country has historically been free of pathogen e.g Australia and PRRS in pigs geographical isolation, strict quarantine 2. Pathogen is being eradicated (or has been eradicated) e.g. CBPP in U.S.

Other diseases!!!.. For many diseases, need statistically valid population-based survey with internationallyrecognized test to increase confidence in the negative surveillance results Tests usually serologic (Se and Sp < 100) Expect to find 0 reactors in the survey

Survey caveats No survey is able to guarantee that a population is free of a pathogen Possible that a very small number of (or even a single) infected animal exists in a population and was not selected in a sample

Survey result as a test Absence - DZ Presence-DZ Freedom Not-Free Survey No DZ Result Correct Type I error Yes DZ Type II error Correct Pr (No DZ/Freedom) = Pr (S-/F) Pr (Yes DZ/ Not-Free) = Pr (S+/NF)

Interpreting a negative survey result Pr (S- F ) depends Pr (Freedom) before survey Threshold used for classification Sensitivity and Specificity of the used diagnostic system

Interpreting a negative survey result Pr (F S-) depends Pr (Freedom) before survey Pr (S-/F) and Pr (S+/NF) of survey Specificity of the diagnostic system for the survey

Survey-level diagnostic system Herd-level test sensitivity & specificity Herd prevalence Number of herds sampled Freedom from disease? Number of Expected test-positive herds

Herd-level test sensitivity and specificity Individual test sensitivity & specificity Number of samples per herd Threshold number of positive ind. tests Within-herd infection prevalence Herd size Herd-level test sensitivity & specificity

The current DK surveillance system (IBR as a disease model) Description of the population dynamic including cattle movement, production type, Description of the sampling strategies: slaughter surveillance vs. bulk tank milk surveillance The impact of the current sampling strategies if an IBR case herd exists Simulation models to assess the effectiveness of the current sampling strategies

Year 1998 through 2001 General statistics (Kvægdatabasen) ~9000 dairy herds; 23000 beef herds Spatial distribution Slaughter house information (export, domestic) Movement Slaughter Surveillance data 2000-2001 Milk tank Surveillance data 1998-2001

Herd size of DK cattle in 2002 Herd size of DK cattle in 2002 Dairy Beef 1 2 to 10 11 to 25 25 to 75 75 to 200 >200 60 50 40 30 20 10 0 Proportion

Proportion adult cows 2002 Proportion adult cows 2002 Dairy Beef 0 0 to 0,2 0,2 to 0,4 0,4 to 0,6 >0,6 60 50 40 30 20 10 0 Proportion

Proportion of herds received cattle in 2001 Dairy Beef 60 50 Proportion 40 30 20 10 0 0 1 2 to 10 11 to 30 30 to 100 >100

At export: Dairy 159 Beef 7 at domestic Dairy 137 Beef 14 Median herd size 2001 for slaughtered cattle

Age of slaughtered cattle (export) Beef Dairy 200000 150000 100000 50000 0 0 1 2 3 4 5 >5 Age (in years)

Age of slaughtered cattle (domestic) Beef Dairy 25000 20000 15000 10000 5000 0 0 1 2 3 4 5 >5 Age (in years)

IBR tested 2001(export) Slaughtered Tested 100000 80000 Number 60000 40000 20000 0 A B C D E Abbattoir

IBR tested 2001(domestic) Slaughtered Tested Number 1600 1400 1200 1000 800 600 400 200 0 a b c d e Abbattoir

IBR-milk testing 1998-2001 Percent 90 80 70 60 50 40 30 20 10 0 1998 1999 2000 2001 1 2 3 4 5 6 7 8 9 Number of samples

Description of the approach Phase I Description and assessment of the current surveillance system using the IBR as a disease model Phase II - Propose a sampling strategy for the national surveillance system for three exotic diseases. Propose a sampling strategy for the herd certification program for salmonellosis and paratuberculosis. Phase III Integration of the above approaches in a system for declaring the country free from specific diseases

A sampling strategy for the national surveillance system Enzootic Bovine Leukosis (EBL), Infectious Bovine Rhinothracheitis (IBR), and Bovine Virus Diarrhea (BVD) Disease characteristics will be considered such as clustering and rare event Simulation models will be considered to determine the impact of the sampling strategy on the detection of the disease if a case exists Cost effectiveness will be a determinant factor in the selection of a strategy

A sampling strategy for the herd certification program Certification program depends on the confidence in the negative results of the testing system Salmonellosis and Paratuberculosis Targeted high risk population will be considered Simulation models will be considered to determine the impact of the sampling strategy on the detection of the disease if a case exists Cost effectiveness will be a determinant factor in the selection of a strategy

Integration above findings in a comprehensive system A comprehensive system for declaring the country free from specific diseases is needed The system should be cost effective, scientifically based, and acceptable by the trade counterparties

Conclusion The broad application of this approach to other animal and public health problems such as food safety The application of this method of the region to be declared free from a specific disease The integration of veterinary services with a diagnostic laboratory system for better understanding of the disease status in a country