An analytical evaluation of contact tracing systems using real-world individual-level data

Area of Science:

• Public Health
• Epidemiology
• Infectious Disease Control

Background:

• Contact tracing is crucial for controlling contagious diseases.
• Automated contact tracing (ACT) systems were developed during COVID-19, but real-world data for evaluation is limited.
• The effectiveness of semi-automated and concurrently adopted tracing systems needs further investigation.

Purpose of the Study:

• To compare and evaluate automated, manual, and semi-automated contact tracing systems.
• To analyze system performance using real-world, individual-level data.
• To assess privacy protection and contact actions within different tracing systems.

Main Methods:

• Individual-level data collected from September 2020 to February 2021 at a US university.
• Empirical analysis of case coverage, contact completeness, timeliness, and precision.
• Investigation of privacy aspects and actions taken by contacts.

Main Results:

• Manual tracing showed highest case coverage (51%) and precision (41% positive tests).
• Automated and semi-automated systems excelled in timeliness with 0-day and 1-day delays, respectively.
• Low overlap (15% case coverage, 11% contact completeness) between systems; 93% of notified individuals took action.

Conclusions:

• No single contact tracing system is superior in all aspects.
• Automated, semi-automated, and manual systems have complementary strengths and weaknesses.
• Concurrent adoption of all three systems is advisable for comprehensive COVID-19 control.