Enhancing the ATra Black Box Matching Algorithm: Use of All Names for Deduplication Across Jurisdictions.

Objectives: Achieving accurate, timely, and complete HIV surveillance data is complicated in the United States by migration and care seeking across jurisdictional boundaries. To address these issues, public health entities use the ATra Black Box-a secure, electronic, privacy-assuring system developed by Georgetown University-to identify and confirm potential duplicate case records, exchange data, and perform other analytics to improve the quality of data in the Enhanced HIV/AIDS Reporting System (eHARS). We aimed to evaluate the ability of 2 ATra software algorithms to identify potential duplicate case-pairs across 6 jurisdictions for people living with diagnosed HIV.

Cross-Jurisdictional Data Exchange Impact on the Estimation of the HIV Population Living in the District of Columbia: Evaluation Study.

Background: Accurate HIV surveillance data are essential to monitor trends to help end the HIV epidemic. Owing to strict policies around data security and confidentiality, HIV surveillance data have not been routinely shared across jurisdictions except a biannual case-by-case review process to identify and remove duplicate cases (Routine Interstate Duplicate Review, RIDR). HIV surveillance estimates for the District of Columbia (DC) are complicated by migration and care seeking throughout the metropolitan area, which includes Maryland and Virginia.