Use Case - Contact Tracing Study Sets Benchmark for Future Preparedness

A joint research team from the Centre for Epidemic Research and Modelling (CERM) at the Saw Swee Hock School of Public Health, National University of Singapore and the National Centre for Infectious Diseases (NCID), leveraged TRUST’s secure data-sharing capabilities to analyse and compare various contact tracing approaches.

The team developed sophisticated simulation models to evaluate contact tracing methods across different scenarios, addressing the varied implementation of strategies observed globally during the pandemic. Their analysis encompassed key components, including case detection, isolation protocols, contact identification, and quarantine requirements.

The findings demonstrated that contact tracing achieves optimal effectiveness when implemented with high case-ascertainment rates and contact quarantine measures. Under these conditions, disease transmission can be halted early, making tracing operations more manageable and cost-effective.

The study's methodology was strengthened by TRUST's secure infrastructure, enabling direct analysis of parameter estimates from contact tracing data. This integration of real-world data enhanced the precision of simulation models executed under high-performance computing systems.

The research findings are expected to contribute significantly to Singapore's emergency preparedness planning, particularly in developing adaptive contact tracing strategies for future public health challenges. Through secure data sharing and analysis capabilities, this collaborative research advances our understanding of effective public health responses.