Abstract
We describe a method for de-identifying point location data used for disease spread modeling to allow data custodians to share data with modeling experts without disclosing individual farm identities. The approach is implemented in an open-source software program that is described and evaluated here. The program allows a data custodian to select a level of de-identification based on the K-anonymity statistic. The program converts a file of true farm locations and attributes into a file appropriate for use in disease spread modeling with the locations randomly modified to prevent re-identification based on location. Important epidemiological relationships such as clustering are preserved to as much as possible to allow modeling similar to those using true identifiable data. The software implementation was verified by visual inspection and basic descriptive spatial analysis of the output. Performance is sufficient to allow de-identification of even large data sets on desktop computers available to any data custodian.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.