Approach for Qualitative Validation Using Aggregated Data for a Stochastic Simulation Model of the Spread of the Bovine Viral-Diarrhoea Virus in a Dairy Cattle Herd
Qualitative validation consists in showing that a model is able to mimic available observed data. In population level biological models, the available data frequently represent a group status, such as pool testing, rather than the individual statuses. They are aggregated. Our objective was to explore an approach for qualitative validation of a model with aggregated data and to apply it to validate a stochastic model simulating the bovine viral-diarrhoea virus (BVDV) spread within a dairy cattle herd. Repeated measures of the level of BVDV-specific antibodies in the bulk-tank milk (total milk production of a herd) were used to summarise the BVDV herd status. First, a domain of validation was defined to ensure a comparison restricted to dynamics of pathogen spread well identified among observed aggregated data (new herd infection with a wide BVDV spread). For simulations, scenarios were defined and simulation outputs at the individual animal level were aggregated at the herd level using an aggregation function. Comparison was done only for observed data and simulated aggregated outputs that were in the domain of validation. The validity of our BVDV model was not rejected. Drawbacks and ways of improvement of the approach are discussed.
Key Words:validation aggregated data stochastic model virus spread
Unable to display preview. Download preview PDF.
- Anon. (2001). Agreste — Recensement agricole 2000. French Ministry of Agriculture and Fishery, Paris.Google Scholar
- Beaudeau, F., S. Assie, H. Seegers, C. Belloc, E. Sellal and A. Joly (2001). Assessing the within-herd prevalence of cows antibody-positive to bovine viral diarrhoea virus with a blocking ELISA on bulk tank milk. Veterinary Record 149: 236–240.Google Scholar
- Houe, H. (1995). Epidemiology of bovine viral diarrhea virus. Veterinary Clinics of North America: Food Animal Practice 11: 521–547.Google Scholar
- Joly, A., F. Beaudeau and H. Seegers (2001). Evaluation de la prévalence et de la dynamique de l'infection BVD en Bretagne à l'aide d'un test ELISA sur lait de grand mélange. Epidémiologie et Santé Animale 40: 7–14.Google Scholar
- Law, A.M. and W.D. Kelton (1991). Simulation Modelling and Analysis. 2nd edn. McGraw-Hill series in industrial engineering and management science, McGraw-Hill, New-York.Google Scholar
- Meyling, A., H. Houe and A.M. Jensen (1990). Epidemiology of bovine virus diarrhoea virus. Revue Scientifique et Technique de l'Office International des Epizooties 9: 75–93.Google Scholar
- Paton, D.J., K.H. Christiansen, S. Alenius, M.P. Cranwell, G.C. Pritchard and T.W. Drew (1998). Prevalence of antibodies to bovine virus diarrhoea virus and other viruses in bulk tank milk in England and Wales. Veterinary Record 142: 385–391.Google Scholar
- Radostits, O.M. and I.R. Littlejohns (1988). New concepts in the pathogenesis, diagnosis and control of diseases caused by the Bovine Viral Diarrhea Virus. Canadian Veterinary Journal 29: 513–528.Google Scholar
- SAS Institute (1989). SAS/STAT User's Guide, Version 6, 4th edn. Cary, SAS Institute.Google Scholar
- Viet, A.F., C. Fourichon, H. Seegers, C. Jacob and C. Guihenneuc-Jouyaux (2003). Influence of the separation into subgroups on the transmission of Bovine Viral Diarrhoea Virus. Society for Veterinary Epidemiology and Preventive Medicine, 31st March–2nd April, Warwick.Google Scholar