On 16 September, European Commission President Ursula von der Leyen will address the European Parliament in Strasbourg for the annual State of the European Union address, at a moment when preparedness has acquired a much broader meaning across the continent. Climate extremes, geopolitical instability, antimicrobial resistance, emerging infectious diseases and the experience of COVID-19 have forced governments to think differently about what resilience actually requires, and the European Commission’s health-crisis framework now explicitly emphasises anticipation, surveillance, early warning and cross-sectoral cooperation, while its wider Preparedness Union Strategy seeks to ready Europe for future civilian and military crises alike. Ahead of that address, calls are growing for animal health to become a genuine pillar of that preparedness architecture, and investment is a large part of that case. But preparedness also requires something else: the ability to connect and verify evidence across the human, animal and environmental health systems on which One Health depends.
There is a danger in thinking about health preparedness primarily through hospitals, medicines and human surveillance, because a substantial proportion of the threats Europe is preparing for may be visible somewhere else first — in a poultry house, a cattle herd, a wild bird, a mosquito population, a veterinary laboratory, or a genomic sequence generated hundreds of kilometres from the hospital that will eventually encounter the consequences. That is why animal health cannot simply be an adjunct to European health security. But there is another, less discussed problem: even if Europe detects those signals, can it connect the evidence?
The epidemiological case is well established. Long-standing estimates put the share of known human pathogens that are zoonotic at around 60% — a figure that traces to Taylor, Latham and Woolhouse’s landmark 2001 analysis and has been repeated across the literature since — while the World Organisation for Animal Health (WOAH) reports that approximately 75% of emerging infectious human diseases specifically have an animal origin. WHO similarly describes the human–animal interface as fundamental to global health security. None of this means every future pandemic will begin in livestock, or that every animal pathogen represents an imminent human threat. It means that separating animal health from human-health preparedness draws an artificial institutional boundary around a biological system that does not recognise one.
Europe already acknowledges this. The European Commission defines One Health as an integrated approach encompassing people, domestic and wild animals, plants and ecosystems, and its current architecture includes collaboration between public-health and veterinary authorities and the Cross-agency One Health Task Force — a joint initiative of ECDC, EFSA, EMA, EEA and ECHA — alongside programmes addressing zoonotic surveillance and preparedness. For zoonotic avian influenza specifically, the Commission describes animal and human surveillance alongside environmental monitoring as essential to rapid detection and coordinated response; Member States undertake compulsory animal surveillance, and European authorities increasingly combine epidemiological information with genomic surveillance. The principle, in other words, is no longer controversial — human, animal and environmental health are connected. The more difficult question is whether the information infrastructure supporting them is equally connected.
The financial imbalance is remarkable. WOAH’s 2026 State of the World’s Animal Health report estimates that animal health receives as little as 0.6% of global health spending, while bringing the Veterinary Services it has assessed up to international standards would require approximately US$2.3 billion annually. That sounds substantial until it is placed alongside the economic consequences of a major pandemic: WOAH compares the figure with the approximately US$3.6 trillion in economic losses attributed to COVID-19 in 2020 alone, meaning the annual investment required for Veterinary Services would amount to less than 0.05% of that single year’s losses. At WOAH’s 93rd General Session in Paris this May, ministers and senior government representatives endorsed a Ministerial Statement calling for greater investment in animal-health systems, describing them as part of the frontline defence against pandemics, food insecurity and economic disruption. That investment case deserves serious attention. But money alone will not produce One Health preparedness — we also have to ask what those better-funded surveillance systems produce, where that evidence goes, and whether it remains connected once it crosses institutional boundaries.
Recent events in Belgium illustrate the point particularly well. A large outbreak of Salmonella Enteritidis has been linked to eggs produced by Laerco BV in Geel, in Flanders; by late August, Belgian authorities had reported at least 306 illnesses, and the affected eggs prompted recalls extending into several other European countries. What is particularly interesting from an evidence-infrastructure perspective is how the outbreak was investigated. Salmonella was first identified in a dust sample collected from a poultry house, and whole-genome sequencing subsequently showed that the bacterial type found there matched the type found in human cases. The problem initially appeared confined to that one poultry house; when continuing human infections failed to decline as expected, further investigation implicated a second house, and controls were ultimately expanded across the whole site.
Consider the information chain implicit in that investigation: a farm environment produces an environmental sample, which a laboratory turns into a result and then an isolate; the isolate becomes a genomic sequence; that sequence is compared epidemiologically against human clinical isolates; the comparison feeds food-chain traceability; traceability informs a regulatory decision; and the decision becomes a product recall crossing national borders. No single database necessarily owns that complete story — and that is precisely the point. (It is not the only recent European egg-linked Salmonella outbreak to make exactly this point: a similar case in the UK earlier this year, which we examined in detail, ran for months with a precise genetic fingerprint in hand but no confirmed upstream source, because the supply chain behind it was never built to be traced.)
Much of the One Health debate understandably concerns institutional cooperation: veterinarians need to communicate with physicians, public-health authorities need access to animal-health intelligence, environmental monitoring needs to inform epidemiological assessment, and laboratories need to exchange sequence data rapidly. The Commission itself recognises this, referring explicitly to cooperation between human-health and veterinary authorities, data exchange, joint assessments, surveillance, rapid detection and coordinated response. The same underlying argument is being made one level up, about biological data infrastructure generally rather than animal health specifically: at the European Parliament’s Committee on Public Health on 8 September 2026, imec’s Liesbet Lagae argued that Europe’s investment in AI and health data needs to be matched by infrastructure capable of generating the underlying experimental biological data at scale — a case we set out in more detail in Europe Needs a Biological Data Infrastructure. It Also Needs an Evidence Infrastructure. But exchanging data and preserving an evidence chain are not quite the same thing.
Imagine a novel pathogen identified tomorrow. A veterinary sample is collected on a farm; a regional laboratory performs the initial assay; a national reference laboratory sequences it; the sequence is uploaded to a repository; another institution performs phylogenetic analysis; an environmental surveillance programme identifies related material; a hospital subsequently identifies a human infection; European agencies conduct a joint risk assessment; an AI system is used to identify epidemiological relationships; a regulator ultimately makes a decision; and months later, researchers reassess the event using improved analytical methods. At that point, access to the resulting datasets is not enough. We need to be able to ask where the evidence originated, which sample generated it, which laboratory produced the result, which version of the sequence was analysed, what transformation occurred, which computational pipeline produced the derivative, which reference dataset was used, who authorised or attested to each step, what information was available when a particular decision was made — and, critically, whether the chain can be independently verified later. That is a provenance problem, and it is the same one we set out in more general terms in Europe Is Building the Infrastructure for AI Biology. It Should Build the Evidence Chain With It.
None of this means Europe’s surveillance infrastructure is fundamentally deficient — quite the opposite. Europe possesses sophisticated veterinary, food-safety, genomic and public-health surveillance capabilities, and the Commission’s avian-influenza framework already brings veterinary and medical authorities together while explicitly recognising genomic surveillance as part of the response architecture. The challenge is that increasingly sophisticated science creates increasingly complex evidence chains. Whole-genome sequencing is a good example: a genomic result is not simply a sequence, but exists within a context of the biological sample, the sampling location and time, sample handling, laboratory methods, sequencing platform, quality-control procedures, bioinformatics pipeline, reference genome, software versions, metadata, subsequent transformations and the interpretations derived from it. Remove enough of that context and the sequence may remain scientifically useful, but its evidential history becomes progressively harder to reconstruct — a distinction that matters more as surveillance becomes more distributed, international and computationally intensive.
This is the problem The BioChain is interested in. The proposition is deliberately not to create another veterinary database, genomic repository, laboratory information management system or public-health platform — Europe already has important systems performing those jobs. The question is what happens between them. BioChain is being developed as an evidence and provenance layer capable of recording the history of evidence as it moves across systems and organisational boundaries: a sample becomes a collection event, which becomes laboratory evidence, which is sequenced, quality-controlled and turned into a genomic record, transformed, analysed, interpreted epidemiologically, and finally acted upon through a regulatory or public-health decision. Each event can reference the evidence that preceded it while creating a verifiable record of what happened next, and the underlying data do not have to move into BioChain to make that possible: a veterinary laboratory can remain a veterinary laboratory, a sequence repository can remain a sequence repository, a food-safety authority and a national public-health organisation can each retain their own systems. The provenance layer connects the evidence without attempting to replace the systems that created it — a principle we set out at greater length in Who Owns the Evidence Chain?, and one that applies just as directly to cross-border food-chain traceability, which we explored recently in the context of the EU’s Brazil meat delisting.
Preparedness is often discussed in terms of capacity — how many laboratories, how quickly sequencing can be performed, how many veterinarians are available, how rapidly a vaccine can be deployed. Those questions matter. But another dimension is evidence latency: how long it takes before information generated in one part of the system becomes usable and trustworthy somewhere else. Consider two hypothetical outbreaks in which the pathogen is detected on the same Monday. In the first, the relevant veterinary, genomic, environmental and human-health records remain fragmented, and analysts spend valuable time reconciling identifiers, determining which sequence belongs to which sample, establishing dataset versions and reconstructing analytical histories. In the second, those systems remain operationally independent, but the evidence carries persistent provenance relationships throughout. The scientific capabilities may be identical in both cases. The preparedness capability is not — which is why provenance should be considered part of preparedness infrastructure, not merely an academic requirement for reproducibility.
There is a useful conceptual shift available here. One Health is normally represented as three interconnected domains — human health, animal health and environmental health — and perhaps we should add something running through all three: evidence. Integration at the policy level means little if the evidence generated within those domains cannot be connected operationally. A veterinarian observing an unusual syndrome may generate the first signal; a laboratory may turn that signal into molecular evidence; genomic surveillance may reveal its relationship to previous outbreaks; environmental data may explain its geographical movement; human surveillance may identify spillover; epidemiology may establish transmission; and only then can policymakers act. One Health is therefore not simply the coexistence of three disciplines. It is an evidence chain running through them.
This is where we believe Europe has an opportunity. The BioChain is developing provenance infrastructure across the UK and EU, with work centred between Oxford in the United Kingdom and our European R&D office in Ghent, Belgium. Our current public demonstrator begins deliberately far away from an active outbreak, in ancient DNA — an environment that lets us explore how samples, metadata, public genomic datasets, transformations and research outputs can be connected through a persistent provenance model without interfering with operational clinical or veterinary systems. Ancient pathogens provide an obvious research environment in their own right, but the architectural question is ultimately a contemporary one: can biological evidence remain verifiable as it crosses laboratories, repositories, analytical pipelines, organisations and jurisdictions? If it can, the implications reach well beyond archaeogenomics, into food safety, animal-health surveillance, genomic epidemiology, biobanks, cross-border research, emerging pathogens and ultimately One Health preparedness itself. It is also why our own tested work today — genomic-research provenance, and livestock-health monitoring through the Applied Livestock consortium and our ADOPT-funded on-farm pig-health trial — sits in real, if narrower, domains rather than as a claim of readiness across every sector this article describes.
The objective should not be to create one gigantic European database into which every animal, environmental and human-health dataset must be deposited — that would simply create a larger silo. A more interesting architecture is one in which systems remain distributed while the evidence relationships between them become interoperable, which matters particularly in Europe, where information routinely crosses institutional and national boundaries and operates within different legal, scientific and operational contexts. The question, then, is whether Europe can create an evidence architecture that lets distributed systems remain authoritative while making the provenance between them independently verifiable. We believe that question deserves experimentation.
The BioChain is therefore interested in working with organisations across the European One Health ecosystem to test this proposition — veterinary laboratories, animal-health organisations, universities, genomic surveillance programmes, food-safety organisations, public-health agencies, research infrastructures, sequencing facilities and technology organisations among them. The objective would not be to arrive with a finished system and ask institutions to adapt around it; it would be to build demonstrators around real scientific workflows and ask what provenance needs to look like when evidence genuinely crosses organisational boundaries. What information needs to be recorded? What should remain within the source system? How should identity be established, transformations be represented and sensitive information be protected? How should evidence be verified across jurisdictions, and what does a veterinary epidemiologist, genomic scientist, regulator or public-health investigator actually need to see? Those are not questions a technology company can answer alone; they require collaboration with the people who generate, interpret and act upon the evidence, much as the wildlife–livestock interface work we discussed in At the Wildlife-Livestock Boundary, Genomic Data Needs a Provenance Trail depends on ecologists, veterinarians and laboratory scientists working from a shared evidence base rather than separate ones.
The central argument being made ahead of this year’s State of the European Union is correct: animal health deserves a much more prominent place in crisis preparedness. WOAH’s figures make the economic argument difficult to dismiss — animal-health systems receive a remarkably small proportion of global health expenditure despite their importance to food security, livelihoods and emerging-disease detection — and Europe already recognises One Health institutionally, with its scientific advisers recommending more integrated preventive action, surveillance and risk assessment, greater policy coherence, and stronger research and innovation. The next challenge is operational. More surveillance will generate more evidence; more sequencing will generate more evidence; environmental monitoring will generate more evidence; and AI will derive still more evidence from the evidence we already possess. The important question is whether we will still be able to reconstruct how all of it connects. A resilient Europe needs strong animal-health systems. A functioning One Health system needs those systems connected to human and environmental health. And a trustworthy One Health system needs the evidence connecting them to remain verifiable — an infrastructure problem worth solving before the next crisis begins.
No. The architectural proposition is the opposite. Existing laboratory, veterinary, genomic, food-safety and public-health systems should continue performing the functions for which they were designed. BioChain is exploring whether a separate provenance layer can preserve relationships between evidence generated across those systems.
Audit logs are extremely valuable inside individual systems. The more difficult problem occurs when evidence leaves one organisational or technical environment and is subsequently transformed elsewhere. Cross-system provenance requires the history of those relationships to survive those transitions.
Because a genomic observation can acquire multiple derivative forms as it passes through quality control, assembly, alignment, annotation, comparison and phylogenetic analysis. Reconstructing which source and processing history underpins a downstream conclusion is therefore increasingly important.
No. Provenance establishes history, not scientific truth. A perfectly documented analysis can still be wrong. What provenance can do is make it easier to establish what evidence was used, how it was processed, and therefore how a conclusion might be reproduced, challenged or revised.
One useful model would connect a limited number of existing systems across an actual research or surveillance workflow — for example, veterinary sampling, laboratory testing, sequencing and downstream analysis — while leaving the underlying systems and data-ownership arrangements intact, then test whether a persistent evidence chain can survive those institutional transitions.
If your organisation generates, manages, analyses or governs biological evidence and would be interested in participating in a UK or European provenance demonstrator, The BioChain would welcome the conversation.
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