RESUMO
Classical swine fever (CSF) is a highly contagious pig disease that causes economic losses and impaired animal welfare. Improving the surveillance system for CSF can help to ensure early detection of the virus, thereby providing a better initial situation for controlling the disease. Economic analysis is required to compare the benefits of improved surveillance with the costs of implementing a more intensive system. This study presents a comprehensive economic analysis of CSF surveillance in the Netherlands, taking into account the specialized structure of Dutch pig production, differences in virulence of CSF strains and a complete list of possible surveillance activities. The starting point of the analysis is the current Dutch surveillance system (i.e. the default surveillance-setup scenario), including the surveillance activities 'daily clinical observation by the farmer', 'veterinarian inspection after a call', 'routine veterinarian inspection', 'pathology in AHS', 'PCR on tonsil in AHS', 'PCR on grouped animals in CVI' and 'confirmatory PCR by NVWA'. Alternative surveillance-setup scenarios were proposed by adding 'routine serology in slaughterhouses', 'routine serology on sow farms' and 'PCR on rendered animals'. The costs and benefits for applying the alternative surveillance-setup scenarios were evaluated by comparing the annual mitigated economic losses because of intensified CSF surveillance with the annual additional surveillance costs. The results of the cost-effectiveness analysis show that the alternative surveillance-setup scenarios with 'PCR on rendered animals' are effective for the moderately virulent CSF strain, whereas the scenarios with 'routine serology in slaughterhouses' or 'routine serology on sow farms' are effective for the low virulent strain. Moreover, the current CSF surveillance system in the Netherlands is cost-effective for both moderately virulent and low virulent CSF strains. The results of the cost-benefit analysis for the moderately virulent CSF strain indicate that the current surveillance system in the Netherlands is adequate. From an economic perspective, there is little to be gained from intensifying surveillance.
Assuntos
Vírus da Febre Suína Clássica/patogenicidade , Peste Suína Clássica/economia , Monitoramento Epidemiológico/veterinária , Animais , Peste Suína Clássica/epidemiologia , Peste Suína Clássica/virologia , Vírus da Febre Suína Clássica/genética , Análise Custo-Benefício , Feminino , Modelos Teóricos , Países Baixos/epidemiologia , Suínos , VirulênciaRESUMO
Decision making on hazard surveillance in livestock product chains is a multi-hazard, multi-stakeholder, and multi-criteria process that includes a variety of decision alternatives. The multi-hazard aspect means that the allocation of the scarce resource for surveillance should be optimized from the point of view of a surveillance portfolio (SP) rather than a single hazard. In this paper, we present a novel conceptual approach for economic optimization of a SP to address the resource allocation problem for a surveillance organization from a theoretical perspective. This approach uses multi-criteria techniques to evaluate the performances of different settings of a SP, taking cost-benefit aspects of surveillance and stakeholders' preferences into account. The credibility of the approach has also been checked for conceptual validity, data needs and operational validity; the application potentials of the approach are also discussed.
Assuntos
Doenças dos Animais/economia , Doenças dos Animais/epidemiologia , Gado , Vigilância da População/métodos , Animais , Técnicas de Apoio para a Decisão , Modelos Econômicos , Alocação de Recursos , Medição de Risco/economiaRESUMO
Economic analysis of hazard surveillance in livestock production chains is essential for surveillance organizations (such as food safety authorities) when making scientifically based decisions on optimization of resource allocation. To enable this, quantitative decision support tools are required at two levels of analysis: (1) single-hazard surveillance system and (2) surveillance portfolio. This paper addresses the first level by presenting a conceptual approach for the economic analysis of single-hazard surveillance systems. The concept includes objective and subjective aspects of single-hazard surveillance system analysis: (1) a simulation part to derive an efficient set of surveillance setups based on the technical surveillance performance parameters (TSPPs) and the corresponding surveillance costs, i.e., objective analysis, and (2) a multi-criteria decision making model to evaluate the impacts of the hazard surveillance, i.e., subjective analysis. The conceptual approach was checked for (1) conceptual validity and (2) data validity. Issues regarding the practical use of the approach, particularly the data requirement, were discussed. We concluded that the conceptual approach is scientifically credible for economic analysis of single-hazard surveillance systems and that the practicability of the approach depends on data availability.
Assuntos
Agricultura , Doenças dos Animais/economia , Doenças dos Animais/epidemiologia , Gado/fisiologia , Modelos Econômicos , Animais , Vigilância da População , Medição de Risco , Medicina Veterinária/economiaRESUMO
Dairy processors face numerous challenges resulting from both unsteady dairy markets and some specific characteristics of dairy supply chains. To maintain a competitive position on the market, companies must look beyond standard solutions currently used in practice. This paper presents a comprehensive dairy valorization model that serves as a decision support tool for mid-term allocation of raw milk to end products and production planning. The developed model was used to identify the optimal product portfolio composition. The model allocates raw milk to the most profitable dairy products while accounting for important constraints (i.e., recipes, composition variations, dairy production interdependencies, seasonality, demand, supply, capacities, and transportation flows). The inclusion of all relevant constraints and the ease of understanding dairy production dynamics make the model comprehensive. The developed model was tested at the international dairy processor FrieslandCampina (Amersfoort, the Netherlands). The structure of the model and its output were discussed in multiple sessions with and approved by relevant FrieslandCampina employees. The elements included in the model were considered necessary to optimally valorize raw milk. To illustrate the comprehensiveness and functionality of the model, we analyzed the effect of seasonality on milk valorization. A large difference in profit and a shift in the allocation of milk showed that seasonality has a considerable impact on the valorization of raw milk.