Expert opinion on whole genome sequencing for public health surveillance
Strategy to harness whole genome sequencing to strengthen EU outbreak investigations and public health surveillanceThis document sets out the ECDC vision for using whole genome sequencing (WGS) technology within the context of its agreed strategy and roadmap for integrating typing data into EU level surveillance and cross-border outbreak assessment over the next five years.
The main focus of the discussion is on the strengths and weaknesses of WGS-based typing compared to other molecular typing methods; the current state and medium-term outlook for the development and harmonisation of WGS-based typing and the strategy and proposed role of ECDC in collaboration with the EU and global players leading the technical development and public health applications of WGS-based typing.
In the last decade, there has been a shift from microbial genotyping to Next-Generation Sequencing technology. Whole Genome Sequencing (WGS) has transformed public health surveillance and outbreak investigations by providing more accurate pathogen identification, antimicrobial resistance profiling, transmission tracking and biological risk assessment.
However, WGS application for multicentre surveillance still faces many challenges. ECDC has therefore provided, jointly with Member State experts, this expert opinion on whole genome sequencing for public health surveillance.
The obstacles to be overcome range from differences in the sequencing platforms, inter-laboratory comparability, lack of standard bioinformatics pipelines, definition of WGS-derived strain nomenclature, comparability with older typing techniques, and translation of epidemiological and genomic sequence data into meaningful information for public health decision-making. In addition, the public health laboratory access to WGS technology differs between and within Member States. Hence, investments at national level should provide the required technical resources and expertise.
To support Member States in the transition to WGS from earlier technologies, and to ensure that WGS is adopted without compromising continuity of national and EU-level surveillance, ECDC proposes to:
- Map other WGS-based public health initiatives and engage partnerships;
- Lead on the integrated analysis of microbiological data and epidemiological data;
- Provide guidance on and validation of WGS-based methods for surveillance and;
- Develop, run and evaluate selected pilot implementation studies.
ECDC has also published a roadmap for integration of molecular and genomic typing into EU surveillance and epidemic preparedness. This updated version of the roadmap recommends priority diseases and WGS-based surveillance implementation processes based on ranking options by public health added-value as well as feasibility within resources available in Member States and at ECDC.
ECDC’s Chief Microbiologist, Marc Struelens states ECDC’s vision that:
‘In five years’ time, ECDC should have contributed to establish standards and manage systems enabling the EU-wide use of WGS as the method of choice for typing of microbial pathogens, replacing other methods. This will improve the accuracy and effectiveness of disease surveillance, outbreak investigation and evaluation of prevention policies by enhanced assessment of disease and drug resistance transmission dynamics’.
Drug-resistant tuberculosis in eastern Europe and central Asia: a time-series analysis of routine surveillance dataRead more
Collection and analysis of whole genome sequencing data from food-borne pathogens and other relevant microorganisms isolated from human, animal, food, feed and food/feed environmental samples in the joint ECDC–EFSA molecular typing database
29 May 2019 - This report identifies and compares potential platforms/solutions for the set-up and running of a joint ECDC–EFSA database to collect and analyse whole genome sequencing (WGS) data for Listeria monocytogenes, Salmonella and Escherichia coli. In particular, WGS introduces the need for specific components for storage and analysis of these data.