First, we will aim to better understand the cellular mechanisms of the immune response and how they relate to the susceptibility and infectiousness of the host. We will determine which components of the immune response and which levels of these components are associated with specific patterns of pathogen dynamics. We then will model the within-host immune response using a compartmental model whose parameters will be estimated from data that currently are being collected from an experimental infection of SPF pigs with PRRSv. In this experiment, several immunological variables are investigated. First, their correlation with the pig infectious status will be established. Preliminary results suggest that early events in the immune response might be pivotal. Therefore, additional data will be collected from another experiment focusing on the first days following PRRSv infection. Additionnally, data will be collected from a follow-up study in naturally PRRSv infected herds to validate the model under field conditions. This will help in assessing the effectiveness of control measures at the individual level by determining the thresholds that must be reached in terms of intensity of the immune response.
Second, we will represent the pathogen spread at the herd level. A model will be built, taking into account host variability in terms of immune status, as well as the population structure of the farm. An individual-based model could be considered, but it might generate problems related to the high dimensionality when transposing it at the supply chain level in WP2, especially as pig herds are generally managed in batches, which already induces a strongly structured herd (Lurette at al., 2008b). Hence, several degrees of simplification and aggregation will be tested to determine which can best represent the host heterogeneity and the herd global response with the simplest possible structure. The data collected from the follow-up study described above also will provide information on change over time in within-herd infection dynamics, which will enable the model to be validated. This immuno-epidemiological model then will be used to evaluate control strategies of PRRSv infection at the herd level (vaccination, biosecurity, etc.).