Abstract

BackgroundPathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control. However, to date, there are limited data regarding (i) the optimal models for integration of genomic data into epidemiological investigations and (ii) how to quantify and evaluate public health impacts resulting from genomic epidemiological investigations.MethodsWe developed the Pathogen Genomics in Public HeAlth Surveillance Evaluation (PG-PHASE) Framework to guide examination of the use of WGS in public health surveillance and disease control. We illustrate the use of this framework with three pathogens as case studies: Listeria monocytogenes, Mycobacterium tuberculosis and SARS-CoV-2.ResultsThe framework utilises an adaptable whole-of-system approach towards understanding how interconnected elements in the public health application of pathogen genomics contribute to public health processes and outcomes. The three phases of the PG-PHASE Framework are designed to support understanding of WGS laboratory processes, analysis, reporting and data sharing, and how genomic data are utilised in public health practice across all stages, from the decision to send an isolate or sample for sequencing to the use of sequence data in public health surveillance, investigation and decision-making. Importantly, the phases can be used separately or in conjunction, depending on the need of the evaluator. Subsequent to conducting evaluation underpinned by the framework, avenues may be developed for strategic investment or interventions to improve utilisation of whole genome sequencing.ConclusionsComprehensive evaluation is critical to support health departments, public health laboratories and other stakeholders to successfully incorporate microbial genomics into public health practice. The PG-PHASE Framework aims to assist public health laboratories, health departments and authorities who are either considering transitioning to whole genome sequencing or intending to assess the integration of WGS in public health practice, including the capacity to detect and respond to outbreaks and associated costs, challenges and facilitators in the utilisation of microbial genomics and public health impacts.

Highlights

  • Pathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control

  • We developed the Pathogen Genomics in Public HeAlth Surveillance Evaluation (PG-PHASE) Framework, underpinned by the principles of implementation science, to examine the impact of WGS on public health

  • The three phases of our evaluation framework are designed to support understanding of WGS laboratory processes, analysis, reporting and data sharing, and how genomic data are utilised in public health practice

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Summary

Introduction

Pathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control. Whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide. Two major applications of pathogen WGS in disease control are (i) identifying and investigating outbreaks and (ii) genomic surveillance of pathogens of public health importance. A key advantage of WGS is the transferability of sequence data, which allows for rapid and interoperable national, international and cross-sectoral data sharing. This enhances the capacity of surveillance systems to quickly detect related cases where epidemiological links are difficult to identify. Epidemiological links may be difficult to identify in the case of geographically dispersed clusters, such as for food-borne illnesses caused by wide food dispersion, or temporally dispersed clusters, caused by pathogens with long incubation periods [11,12,13,14]

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