A Probabilistic Transmission Model of Salmonella in the Primary Broiler Production Chain

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Abstract
Annual data from the Finnish National Salmonella Control Programme were used to build up a probabilistic transmission model of salmonella in the primary broiler production chain. The data set consisted of information on grandparent, parent, and broiler flock populations. A probabilistic model was developed to describe the unknown true prevalences, vertical and horizontal transmissions, as well as the dynamical model of infections. By combining these with the observed data, the posterior probability distributions of the unknown parameters and variables could be derived. Predictive distributions were derived for the true number of infected broiler flocks under the adopted intervention scheme and these were compared with the predictions under no intervention. With the model, the effect of the intervention used in the programme, i.e., eliminating salmonella positive breeding flocks, could be quantitatively assessed. The 95% probability interval of the posterior predictive distribution for (broiler) flock prevalence under current (1999) situation was [1.3%–17.4%] (no intervention), and [0.9%–5.8%] (with intervention). In the scenario of one infected grandparent flock, these were [2.8%–43.1%] and [1.0%–5.9%], respectively. Computations were performed using WinBUGS and Matlab softwares.