Surveillance for new and re-emerging animal diseases in England and Wales is based on post-mortem and syndromic analysis of laboratory data collated in a central database by the Animal Health and Veterinary Laboratories Agency (AHVLA), with the aim of providing early warning of disease events prior to clinical diagnosis. Understanding the drivers for participation in such systems is critical to the success of attempts to improve surveillance sensitivity. The aim of this study was to investigate the decision-making process governing the submission of biological samples on which this surveillance system is based by use of questionnaires. Data extracted were used to structure and parameterize scenario trees modelling the probability of generating an entry in the surveillance database. The mean probability for database entry per case ranged from 0.085 for neurological disorders to 0.25 for enteric disease. These findings illustrate the importance of on-farm decision making to the generation of surveillance data.