Association between different types of within-farm worker movements and number of pigs weaned per sow in U.S. Swine farms

Abstract

The integration and intensification of modern swine production has amplified the importance of biosecurity, as diseases are more easily able to spread and persist in large swine farms, resulting in economic losses. Advancements in accessible technology and computational methods offer new applications for precision livestock farming, such as monitoring internal movements to better understand biosecurity compliance on farm. In this study, a beacon-sensor based internal movement system (PigChamp Pro Europa®) was utilized to investigate the association between weekly within-farm movements of workers and an important production parameter: average weekly number of pigs weaned per sow (PWS), on three US swine farms. Sensors were installed in each room of each farm and Bluetooth-based beacons were distributed individually to farm employees. Movement data was collected for approximately one year and production data was extracted from each farm retrospectively. A linear mixed effects model was fit in STATA 15 with the primary outcome as the average weekly number of pigs weaned per sow and farm included as a random effect. The main predictors included the weekly frequency of three movement types thought to be risky with respect to disease transmission and maintenance in the herd. The frequency values of the three movements were categorized based on the tertile values for each farm. The movement with the highest average frequency was between farrowing rooms for all three farms. The medium frequency of movements category between farrowing rooms the two-weeks preceding the outcome was significantly associated with a decrease in PWS by nearly 1-pig for every 5-sows after controlling for farm, pre-weaning mortality, PWS the week prior, and season (p = 0.03). The random effect variance estimate for the model was 0.21 with a standard error of 0.18. The intraclass correlation coefficient was 0.67 with a standard error of 0.19, indicating that 67% of the unexplained variability in PWS could be attributed to the farm level. This study demonstrates the application of beacon-sensor technology to monitor internal personnel movements in swine production.Technological applications to monitoring trends of within farm movements of farm personnel, such as the system used here, may have the potential to identify specific movements related to farm-specific biosecurity protocol allowing corrective measures and facilitating focused efforts on disease control and mitigation; in turn maintaining productivity and improving overall animal health.