A framework for decision support related to infectious diseases in slaughter pig fattening units
This paper analyzes the problem faced by managers of pig fattening units when the pigs are subject to common epidemic diseases, such as respiratory diseases or Swine Influenza. The problem is defined as a simultaneous optimization of the delivery policy and control strategies for disease control. As some disease controls, such as vaccination, are implemented at the batch level and last through the lifetime of the vaccinated pigs, the problem requires that decisions are addressed at multiple timescales. Using the framework of multi-level hierarchic Markov processes a general framework was defined. The elements defining the framework were the decisions at the tactical (batch) level and the operational (daily) level. Decisions at the strategic level, e.g., decisions lasting longer than the length of a batch, were considered as constraints to the lower levels of the decision problem and not optimized. The major components of the general framework were a stochastic growth model, an epidemic model to handle within-batch spread of disease, a transition model to handle the between-batch spread of disease, and link between the growth model and the disease model and a general set of control measures. The model was illustrated using an example with Swine Influenza in an all-in-all-out production system. Results show that the optimal delivery policy and control strategies for disease interact. This suggests that decision support must adopt an integrated approach to modelling the decision complex in pig production in order to represent the full complexity of the system.