A distributed, privacy-preserving platform for linkage of epidemiological data with pathogen genome sequences

Efficient and secure integration of epidemiological data with pathogen genome sequence data is essential for identification of transmission clusters, monitoring of emerging mutations and targeting public health responses. However, this information is often collected across different organisations: epidemiological data is collected by public health units while genome sequence data is collected by diagnostic laboratories. Linking these sources often requires manual or semi-manual approaches, leading to unnecessary delays in identifying emerging outbreaks. To address this, we developed a proof-of-concept privacy-preserving distributed platform, SecureEpiLink, for automatic linkage of pathogen genome sequences and notification data across public health and diagnostic laboratories. SecureEpiLink uses cryptographic hashing to establish linkage, without exposing personal identifying information. This ensures that the resulting linked data can be used to identify the emergence of transmission clusters without identification of individuals comprising each cluster. The original identifiable data can continue to be stored at source labs. We benchmarked SecureEpiLink against manual linkage and another linkage service using HIV and HCV datasets from New South Wales, Australia. SecureEpiLink performed similarly to manual linkage and outperformed previously used linkage algorithms, with all errors attributable to data entry errors in the underlying dataset. Lastly, we demonstrate how SecureEpiLink can be integrated with automated genomic epidemiology pipelines. SecureEpiLink is available from https://github.com/jolenefarrell/SecureEpiLink. Author summaryLinkage of epidemiological data collected in public health units with pathogen genome sequence data generated by diagnostic labs in real-time is essential for targeted public health responses. However, linkage creates risks of stigmatisation and criminalisation for individuals. We have designed, implemented and tested a privacy preserving real-time system for linking pathogen genome sequence data with public health notification data within different jurisdictions.