The implementation of Whole Genome Sequencing (WGS) in Canada has significantly transformed the landscape of cluster detection and outbreak response, particularly for enteric pathogens. The transition from traditional subtyping methods, like Pulse-Field Gel Electrophoresis (PFGE), to WGS has had a profound impact on how outbreaks are identified, investigated, and managed. This shift has been a critical advancement, improving the accuracy and efficiency of Canada's public health response to foodborne illnesses.

Enhanced Cluster Detection and Source Attribution

WGS offers superior discriminatory power compared to PFGE, enabling more precise identification of genetic linkages between cases. For pathogens like Salmonella, WGS has been instrumental in linking outbreaks to specific food sources, such as frozen raw breaded chicken products. Between 2017 and 2019, WGS played a pivotal role in identifying these products as the source of 16 Salmonella outbreaks, leading to policy changes aimed at improving food safety (Morton et al., 2019). These changes included new interventions for controlling Salmonella in poultry, highlighting how WGS not only improves scientific understanding but also drives public health policy.

In contrast to traditional PFGE, which provides only a rough approximation of relatedness, WGS offers an exact genetic profile, allowing for more accurate cluster detection and better epidemiological conclusions (Angelo et al., 2017; Reimer et al., 2011). A retrospective analysis of Listeria monocytogenes clusters, for instance, revealed that many previously identified clusters were not genetically related when reassessed with WGS (Kandar et al., 2018). This emphasizes the importance of transitioning to WGS for more reliable outbreak detection.

Continuous Surveillance and One Health Approach

One of the key advantages of WGS is its ability to support continuous, long-term surveillance. While PFGE clusters were typically closed after a certain period with no new matches, WGS allows for ongoing comparisons across time, facilitating the identification of clusters even after extended periods. This continuous surveillance model has proven essential for the identification of long-standing outbreaks that might otherwise go undetected.

Additionally, WGS enables the integration of a One Health approach to outbreak investigations. This approach considers not only human isolates but also nonhuman sources such as animals and the environment. By including these nonhuman isolates, WGS helps to identify genetic diversity across various sources, making it easier to trace outbreaks originating from animal or environmental contamination. This holistic method has improved the ability to pinpoint outbreaks that may have more complex, multiple-source origins (Miller et al., 2020).

Increased Investigative Capacity and International Collaboration

With the adoption of WGS, Canada has enhanced its ability to collaborate internationally. Data sharing through platforms like the NCBI Pathogen Detection pipeline has enabled Canadian health authorities to compare domestic outbreak data with international cases, strengthening global surveillance efforts (Pettengill et al., 2020). WGS data has also facilitated the identification of cross-border outbreaks and the tracking of foodborne pathogens across different countries, showcasing Canada’s leadership in public health surveillance.

However, the shift to WGS also posed challenges. Increased cluster detection led to an increased workload at the national level, requiring more resources to manage the surge in identified outbreaks. Furthermore, the complexity of interpreting WGS data necessitated extensive training for laboratory and epidemiological teams. To address these challenges, Canada introduced new tools and processes to prioritize clusters based on factors such as cluster size, case distribution, and suspected sources.

A Model for the Future

Despite the challenges, the successful implementation of WGS in Canada has positioned the country as a global leader in pathogen surveillance. By improving the accuracy of cluster detection, enhancing the ability to track outbreaks over time, and facilitating international collaboration, WGS has transformed Canada’s response to foodborne illnesses.

The transition to WGS serves as a model for other countries, demonstrating the value of integrating advanced genetic technologies into public health surveillance systems. Furthermore, WGS’s ability to provide actionable, real-time data is crucial for future disease management and outbreak response strategies.

Canada’s experience with WGS highlights both the promise and the challenges of adopting new technologies in public health. While obstacles remain, such as the need for continuous data quality and timely exposure information, WGS has undoubtedly enhanced Canada’s ability to respond to foodborne illness outbreaks with greater accuracy, speed, and collaboration. The transition to WGS has not only improved outbreak detection but also reshaped Canada’s approach to public health surveillance, setting a standard for future advancements in the field.