The economization of surveillance methods for documenting freedom from disease is an important international research topic. Resources of veterinary services for disease surveillance are more and more constraint, but the spread of emerging infectious diseases due to globalization and climate change represents an increasing challenge. TS with testing selected high-risk population strata is a promising approach for a reliable but cost-efficient surveillance strategy. But to our knowledge, it has not been worked out and tested thoroughly within the scope of national surveillance programs.
In this project, the application of TS shall be worked out for infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) in Swiss cattle population. An epidemiological analysis for those case studies IBR and EBL, respectively, will be conducted to figure out all risk factors for infection. According to the identified risk factors, the cattle population, i.e. cattle herds in Switzerland will be stratified and split up into different risk strata. A scoring system to weight the importance of each risk factor for infection has to be worked out in parallel. This scoring system will allow to quantify the information yield we gain by testing a herd having a higher risk for infection compared to a herd with lower risk for infection.
Based on the stratification of the cattle population and the developed scoring system, a new generic quantitative model will be developed based on the stochastic scenario tree model of Hadorn & Stärk (submitted). The developed model shall provide the number of required herds for the documentation of freedom from IBR and EBL, respectively, given that the sampling is conducted exclusively in the appropriate high-risk strata.
Scenarios of different arrangements between TS and RS will be created. The relative effectiveness of these scenarios in detection of disease will be evaluated by mathematical modeling (VenSim®) and the calculation of their potential cost-effectiveness. With the population model, different epidemics will be simulated stochastically, and the detection power of the scenarios will be measured. The theIn a cost-benefit analysis, the expected benefit of TS will be quantified.
The annual surveys in Swiss cattle population for IBR and EBL are conducted in one sampling round. For this reason, it would be of interest to know if the surveys can be conducted on the same farms. Therefore, as a last step in the project, the population strata and the resulting quantitative model for IBR and EBL will be compared. If common risk factors exist for both diseases and if the high-risk strata for both diseases are identical, a general model can be developed including the parameters for IBR as well as EBL. In this case, the sampling procedure will be the same for both diseases. In case that TS for IBR and EBL seems to be beneficial compared to RS, TS will be implemented in the annual national survey in Switzerland.
