Recipient Organization
OHIO STATE UNIVERSITY - VET MED
1900 COFFEY ROAD, 127L VMAB
COLUMBUS,OH 43210
Performing Department
Preventive Medicine
Non Technical Summary
External biosecurity are measures that farmers put in place to prevent animals in a farm from getting diseases. One example is keeping records of farm visitors, because people and inanimate objects (e.g. clothing) may transmit diseases as they move from one farm to the other. However, keeping track of visitors is difficult and requires good compliance, as most farms rely on manual notes entered by the visitor. Our project will evaluate the use of geofencing technology using a swine system (farms, feed mills, etc.) as a model. Geofencing refers to creating virtual barriers in facilities that are recognizable via cell phones. The recognition process happens automatically, and a list of visitors could be available in near real-time as needed. If this technology works in the field, this could help with disease investigations and prevention of exotic diseases in the future, improving external biosecurity of agricultural systems.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
Goal 1: To facilitate the implementation of a geofencing technology system in swine sites under field conditions.Goal 2: To estimate the accuracy of a geofencing technology system to detect movement of people and vehicles between sites, including both sites housing animals and non-animal facilities (e.g. feed mills, truck wash stations, offices, etc.) under field conditions.Goal 3: To quantify the amount of movements occurring between swine sites in a daily basis, and identify target sites for disease surveillance using network analysis.
Project Methods
Participant Recruitment: Participants will be recruited both through invitations from the involved company and through the PI's network contact. Recruitment materials (e.g. flyer, e-mails) will be created and distributed through the investigator's contact network in the swine industry. The PI will contact potential participants and outline expectations including timeline, access to data, and overarching project objectives. Participants will be requested to participate in this study for a minimum period of three months. There will be no restrictions for geographical regions (besides being located within the US) for participation. Participants that are currently working and/ or under communications with the technology company will also be invited to participate in this third-party assessment. Upon agreement to participate, the installation of the technology will be coordinated by the company (please refer to support letter). In brief, virtual barriers - geofences - will be created for every farm or facility that is part of the project. Individuals selected to be part of this tracking will include veterinarians, truck drivers (e.g., animals, feed, etc.), service providers (e.g., plumbers, electricians, etc.), and others. This personnel will be asked to download an application on their cell phones that will be able to automatically detect when the geofences are crossed (i.e. movements occur), creating a virtual near real-time log book. For participants that do not own a company-specific device and do not feel comfortable downloading the app on their personal devices, a cell phone will be provided by the participating production system.Data collection: A minimum follow-up period of three months will be completed for all participants as part of this study. Funding for this period (except for graduate student labor) will be covered by the startup company (please refer to support letter). During this period, the research team will support implementation and participation as needed, helping with troubleshooting and bringing technical issues to the attention of the technology company as needed.Accuracy data: In order to estimate system accuracy, researchers will work with participants to record the "gold standard" for the purposes of movement capture during the study period. The current industry gold standard for visit recording is via manually recorded visitor log books, usually located in the entry of the farm. This will be used as the gold standard for accuracy calculations. In addition, since the current industry gold standard has been described as having limited reliability (Racicot et al., 2012), we will designate at least 5 people to manually record their visits for a period of 3 weeks (21 days). The PI for this project will be responsible for clearly outlining all data needs to accomplish the proposed objectives, and working with the technology company to assure these are delivered in a timely matter. To estimate accuracy, the following formula will be used: (true positive + true negative)/ total number of observations. The number of true positives will be defined as the number of movements detected by the system that were also recorded by the gold standard, and the number of true negatives will be defined by the absence of movements according to the geofencing system that were also not recoded by the gold standard. This will measure the proportion of the time in which the technology is correct.Sample size (Appendix 1): In order to be able to estimate an accuracy of 99%, with a 1% precision (defined as the allowable or acceptable error in the estimate) and 95% confidence, a minimum number of 381 movements is needed (Sergeant, 2018). Considering an average number of movements of 5 for each person/ device per day, and a minimum of 5 people using this device daily, our goal number of movements would be accomplished within 15-16 days (1/2 month). Therefore, we anticipate our proposed approach will collect more observations than enough for validation purposes. The sample size calculation is available on Appendix 1.Data management and network analysis: The technology company will facilitate all data access, and assure that participant identifiers are removed whenever possible to prevent confidentiality issues. All observations will have date and time of movement, person (anonymous/ non-identifiable if possible), person's role in the production system (e.g. truck driver, service provider, service technician, herd veterinarian, etc.), production company (anonymous), and farm/ facility visited (anonymous identification and type- e.g. breeding site, finisher site, feed mill, office, slaughter plant, etc.). Data will be delivered to project investigators for accuracy and network analysis. The use of network analysis allows not only for characterization of the network as a whole, but also for the description of members of such networks (e.g. swine sites) in terms of their importance to the network in spreading and 'receiving' diseases (Dube et al., 2011). Furthermore, it allows for the capture of indirect connections amongst swine sites that would otherwise go unnoticed. Knowledge of networks could also be of great use when designing cost-effective monitoring and risk-based surveillance strategies (Baudon et al., 2018) within regions or even countries. Results from this analysis will be summarized visually and using summary statistics using a combination of R, STATA, and UCINET software.