The swine industry collects a vast and ever-expanding amount of data. Considering the existing knowledge on determinants of disease and its effect on pathogen ecology, it is possible to use historical data to forecast upcoming health-related events. For instance, existing data can forecast the probability of pathogen introduction into herds and/or regions. Similarly, it is possible to forecast the effects of the three way interaction between host-environment-pathogen on the health and productivity of swine populations.
Disease Forecasting
We believe that forecasting tools enable decision-makers to guide their decision trees, positively influencing swine health, welfare & productivity through data-driven decisions:
Forecast Manuscripts
- Development of a pig wean-quality score
- Comparing forecasting models for predicting nursery mortality
- Whole-herd risk factors associated with WTF mortality
- Machine-learning algorithms to identify PRRS outbreak
- Utilizing productivity and health information with disease diagnostic data to identify risk factors