Characterizing the connection between swine production sites by personnel movements using a mobile application-based geofencing platform.

Biosecurity is critical to productivity and profitability in swine production systems and can be achieved by incorporating external (bioexclusion) and internal (biocontainment) practices. Although increasing threats of foreign animal diseases have justified the need of rigorous external biosecurity plans, their effectiveness highly depend on the compliance of on-farm employees, farm-related personnel, and visitors. In this study, we evaluated the uses of a mobile application-based geofencing platform in two swine production systems for accurately identifying personnel movements between swine production sites and detecting potential biosecurity breaches by violating required downtime between site visits. The geofencing platform accurately recognized 95.2% (379/398) of personnel entries comparing to physical entry logs. Further, among 1861 entries over a period of one month, 19 strongly connected components and 12 potential biosecurity breaches were identified. Personnel with duty in communications and information systems committed 75% of biosecurity breaches. The results reported herein demonstrated the possible uses of geofencing platforms for investigating connections among swine production sites by personnel movements and identifying biosecurity breaches.

Turnover events of animal caretakers and its impact on productivity in swine farms.

Attracting and retaining quality animal caretaking personnel is one of most pressing issues the US swine industry currently faces. On-farm employee turnover can be costly and have an impact on productivity. The primary objectives of this study were to describe the amount of animal caretaker turnover events that occurred in a single year in eleven swine farms, and to investigate associations between employee turnover events and two subsequent production parameters of interest: number of pigs weaned per sow (PWS) and pre-weaning mortality (PWM). A retrospective cohort study was conducted with eleven commercial farrow-to-wean swine farms belonging to two vertically integrated multi-site production systems within two swine production companies. Human resources and production data for the year of 2019 were obtained monthly from each farm. The primary predictor of interest was the occurrence of an employee turnover event, defined as 'voluntary' (employee decided to leave or quit) or 'involuntary' (employee was terminated by company decision). The primary outcomes of interest included the monthly average PWS and PWM. These associations were assessed with 1-, 2-, 3-, and 6-months between the turnover events and the outcome. Linear mixed effects models were fit in STATA 15, with system and farm included as random effects. To account for temporal and seasonal trends of production, season and the monthly production were included in the models. There were a total of 152 turnover events, with 4 and 148 turnover events in systems 1 and 2, respectively. The average turnover, calculated as a percent of total turnover among full time employee positions, was 92 % (SD = 62 %; Range = 8-217 %). Improved production efficiency in both monthly PWS (p = 0.01) and PWM (p = 0.02) was observed with the occurrence of an involuntary turnover event two months prior, after controlling for season, previous month production, farm, and system. For the PWS outcome, there was a significant interaction between an involuntary turnover event two months prior and monthly county-level unemployment rate (p = 0.02), indicative of the improved performance being most profound at the lowest levels of unemployment rate and diminishing at the highest levels. Turnover of animal caretaking personnel in farrow-to-wean farms was confirmed to be highly variable and high for the majority of farms in this study. Furthermore, animal caretaker turnover was associated with subsequent trends of production efficiency, warranting closer consideration of prioritizing managerial efforts in worker recruitment, training and retention.

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

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.