A quantitative assessment of the validity of animal-health surveys using stochastic modelling

This paper presents a stochastic simulation model to evaluate the efficacy of regional or national surveys aimed at identifying infection in populatio ns of animals, The process of evaluation involves specification or calculat ion of cluster-level test sensitivity and specificity, which are derived fr om two probability distributions of the number of individual-level positive tests expected from non-infected and infected clusters, respectively. Prob ability distributions for the number of positive clusters expected in a sit uation of freedom from infection and under various levels of cluster preval ence are specified and used to determine survey properties (the survey bein g considered a diagnostic system), and ROC curves are drawn. Likelihood rat ios allow investigators to state the extent to which a survey result is mor e likely to be observed if the region or country is infected at a given pre valence than if it is free from infection. The result of a survey carried o ut to investigate the presence of porcine reproductive and respiratory synd rome (PRRS) in Switzerland is used to illustrate this approach. The model c an be adapted to a wide range of survey designs. (C) 1999 Elsevier Science B.V. All rights reserved.