Quantitative decision making in animal health surveillance: Bovine Tuberculosis Surveillance in Belgium as case study.

INTRODUCTION: Despite eradication and control measures applied across Europe, bovine tuberculosis (bTB) remains a constant threat. In Belgium, after several years of official bTB-free status, routine movement testing, as currently practiced, revealed itself inadequate to detect some herds affected by sporadic breakdowns. The aim of this study was to assess different surveillance system components that strike a balance between cost and effectiveness and to identify sustainable alternatives, which substantiate a bTB-free claim whilst ensuring early detection too, as well as acceptance by various animal health stakeholders.

METHODS: A stochastic iteration model was first built to simulate the current surveillance system's expected performance in terms of detection sensitivity and specificity. These results were then descriptively compared with observed field results. Secondly, the cost and effectiveness of simulated alternative surveillance components were quantified. Sensitivity analyses were performed to measure key assumptions' impacts (i.e., regarding diagnostic tests and true prevalence).

RESULTS: Discrepancies between the observed and simulated expected performance of bTB surveillance in Belgium were observed. Secondly, simulated alternatives revealed that interferon gamma (IFN-γ), as well as serological testing with antibody - enzyme linked immunosorbent assay (Ab-ELISA), targeting at-risk herds would enable an increase in the overall cost effectiveness (sensitivity and specificity) of the Belgian bTB surveillance system. Sensitivity analyses showed that results remained constant despite the modification of some key assumptions.

DISCUSSION: Performance of the ongoing bTB surveillance system in Belgium, at the time of the study, was questionable. This exercise highlighted that not only sensitivity, but specificity also are key drivers of surveillance performance. The quantitative approach, taking into consideration various stakeholders' needs and priorities, revealed itself to be a useful tool in allowing evidence-based decision making for future tuberculosis surveillance in Belgium, which is in line with the international standards. This article is protected by copyright. All rights reserved.