One Health, One Data: Reimagining Pet Health Surveillance

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What if the case notes from your clinic could forecast tomorrow’s outbreak? We sit down with epidemiologist Dr. Lauren Grant to unpack a One Health vision that connects veterinary, human, and environmental data so we can spot risks sooner, act faster, and guide smarter decisions in practice.

We start by clarifying what “integrated companion animal health surveillance” really means and why Canada needs it. Today’s networks rely on selective reporting and expert panels, which are invaluable but miss the power of routine primary care records at scale. Lauren explains how systems like the UK’s VETCOMPASS and SAVSNET turn everyday consultations into population-level insight, building baselines and detecting anomalies that trigger timely investigation. The payoff is concrete: regional trend context to refine differentials, better testing choices, targeted client advice, and earlier alerts for zoonotic and reverse zoonotic threats.

The conversation gets real about barriers to data sharing: policy constraints, privacy, commercial concerns, and a cultural gap where clinicians don’t always see their notes as public health assets. We explore practical solutions—clear governance, de-identified pipelines, minimal viable data fields, and feedback loops that return value to contributing practices through dashboards and timely briefs. Lauren walks through a compelling example from the UK where an unusual spike in canine vomiting was picked up, investigated, and traced to a canine enteric coronavirus, illustrating how strong baselines and near real-time data can change outcomes.

If you’re a veterinarian, public health professional, or data-minded pet owner, this is a roadmap for making companion animals true sentinels of community health. Learn how a Canadian system could start with dogs and cats, build interoperability and trust, and ultimately help both pets and people. Enjoy the episode, share it with a colleague, and if it resonates, subscribe and leave a review so more listeners can find conversations like this.

JAVMA article: https://doi.org/10.2460/javma.25.09.0575

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