Privacy of Study Participants in Open-access Health and Demographic Surveillance System Data: Requirements Analysis...

Area of Science:

• Health Informatics
• Data Science
• Epidemiology

Background:

• Data anonymization and sharing are crucial for global research.
• Open-access sharing of sensitive data requires preserving utility while minimizing disclosure risk.

Purpose of the Study:

• To address challenges in anonymizing health surveillance event history data.
• To propose solutions for sharing longitudinal data with multiple event dates and time-varying variables.

Main Methods:

• Sequential noise addition to event dates to maintain order and time intervals.
• Distance-based matching for risk estimation.
• Limiting intermediate statuses or achieving k-anonymity for time-varying variables.
• Application to Karonga Health and Demographic Surveillance System (HDSS) data (1995-2016).

Main Results:

• Created anonymized event history data with high utility and acceptable disclosure risk.
• High data utility was maintained even with increased noise in event dates.
• The sequential noise addition preserved event order and time between events.

Conclusions:

• The proposed anonymization method enables sharing of longitudinal event history data as public use data.
• Low disclosure risk was demonstrated even under worst-case attack scenarios.
• Beneficial for researchers in low- and middle-income countries and those working with longitudinal data.