One Health surveillance is often described as a data-sharing problem. Increasingly, it is not. The technology for connecting biological information is improving rapidly. The harder question is what happens when information crosses an institutional boundary and nobody has clear responsibility for what happens next.
The Technical Problem Is Becoming Solvable
Human health, veterinary medicine, food safety and environmental surveillance have historically developed their information systems separately.
There are good reasons for this. They serve different populations, operate under different legislation, collect different kinds of evidence and answer to different institutions.
Biology, however, does not respect those divisions.
A pathogen can move between wildlife, livestock and people. Antimicrobial resistance can emerge in one domain and become consequential in another. Foodborne outbreaks may require evidence from farms, food-production systems, genomic laboratories and hospitals before the underlying event becomes visible.
Connecting these observations has traditionally been technically difficult.
That is beginning to change.
Genomic surveillance, shared ontologies, structured metadata, persistent identifiers and increasingly interoperable information standards create the possibility of linking observations generated in very different biological environments.
The European Food Safety Authority and European Centre for Disease Prevention and Control provide an important example. Their work on One Health whole-genome sequencing infrastructure allows genomic information from human and non-human foodborne isolates to be considered together.
The significance is greater than the technology itself.
It demonstrates that the traditional boundary between a “human-health dataset” and an “animal or food dataset” becomes increasingly artificial when both contain evidence about the same biological event.
But solving that problem exposes another one.
Making information interoperable does not make institutions interoperable.
The Alert Arrives. Who Owns the Problem?
Imagine that an interoperable surveillance system works exactly as intended.
A veterinary laboratory identifies an unusual organism.
Genomic analysis establishes a relationship with sequences appearing elsewhere.
Environmental surveillance provides another signal.
A human-health system subsequently identifies related cases.
The information moves successfully.
The terminology is compatible.
The provenance is preserved.
The biological relationship is visible.
Technically, the system has succeeded.
Now what?
Who determines whether the combined evidence constitutes a significant threat?
Which institution owns the investigation?
At what threshold does a veterinary observation become a public-health concern?
Who has authority to request additional information?
Who communicates uncertainty?
Who decides whether precautionary intervention is justified?
Who bears the economic consequences if that intervention turns out to have been unnecessary?
And who is accountable if everyone receives the information but nobody acts?
These are not interoperability questions.
They are governance questions.
One Health Creates an Accountability Problem
One Health is compelling precisely because it recognises that human, animal and environmental health are interdependent.
Institutional responsibility is considerably less integrated.
Governments generally allocate authority through ministries, agencies, legislation and budgets organised around sectors.
Agriculture has responsibilities.
Public health has responsibilities.
Environmental authorities have responsibilities.
Food-safety organisations have responsibilities.
Local government may have others.
Each institution can perform its individual function competently while the system collectively performs badly.
This creates an important distinction between organisational competence and system competence.
A veterinary authority can correctly identify and report an animal-health event.
A public-health organisation can correctly determine that there is insufficient evidence for human intervention.
An environmental authority can correctly identify that an observation falls outside its statutory remit.
Every decision can be defensible within its institutional boundary.
The combined result can still be delayed recognition of an emerging threat.
One Health governance therefore cannot be reduced to encouraging organisations to collaborate.
It requires mechanisms for governing the spaces between institutional mandates.
More Data Does Not Resolve Authority
There is a tendency to assume that better surveillance will naturally produce better decisions.
Sometimes it will.
But information and authority are different resources.
A surveillance platform may establish with increasing confidence that events in several domains are biologically connected. It cannot determine which institution has legal authority to intervene.
Nor can an algorithm resolve competing institutional incentives.
An agriculture ministry may be concerned about the economic consequences of movement restrictions.
A public-health authority may prioritise precaution.
An environmental organisation may be operating under different evidential standards.
A laboratory may be comfortable reporting a biological relationship while being unwilling to infer its epidemiological significance.
The availability of better information can therefore expose disagreement rather than eliminate it.
This is not a failure of science.
It is a feature of governance under uncertainty.
The relevant question becomes not merely whether institutions share information, but whether the governance system has established in advance how responsibility changes when evidence crosses sectors.
Trust Is Part of the Infrastructure
There is another layer.
Interoperable systems allow information to move.
Institutions still have to trust it.
That trust may depend upon laboratory accreditation, sampling protocols, analytical methods, institutional reputation, legal authority and previous relationships between organisations.
During routine surveillance these differences can be negotiated slowly.
During an emerging biological event, they may need to be resolved in hours.
The quality of relationships established before a crisis therefore affects the value of information during one.
This is why trust should be considered part of biosecurity infrastructure.
A technically perfect data exchange between institutions that do not trust one another may have less operational value than a less sophisticated system connecting organisations with established mechanisms for joint interpretation and action.
Technical interoperability and institutional trust are therefore complements.
Neither substitutes for the other.
The Governance Layer
The emerging architecture of biological surveillance consequently needs two layers.
The first is informational.
Biological observations need common identifiers, structured metadata, provenance and standards capable of preserving meaning as information moves between systems.
Molecular Precision examines this technical problem in The Interoperability Gap in Biological Surveillance: Why Data Standards Are Biosecurity Infrastructure.
But technical interoperability eventually reaches a boundary.
The second layer is institutional.
Governance needs to determine:
- who receives cross-sector alerts;
- who has authority to convene a response;
- how uncertainty is communicated;
- which evidential thresholds trigger escalation;
- how responsibilities move between sectors;
- how disagreements are resolved;
- who can authorise precautionary measures; and
- where accountability ultimately rests.
These arrangements cannot sensibly be invented after a crisis has begun.
They are part of preparedness.
From Data Sharing to Decision Sharing
The language surrounding One Health surveillance frequently emphasises data sharing.
That is necessary, but insufficient.
The more difficult objective is decision sharing.
Institutions need mechanisms through which evidence generated across different sectors can become a common situational picture and, where necessary, a coordinated decision.
That does not require creating a single One Health super-agency.
Just as technical interoperability does not require putting every biological record into one global database, institutional interoperability does not require collapsing every responsible organisation into one bureaucracy.
It requires defined interfaces.
Who contacts whom.
Who can escalate.
Who convenes.
Who decides.
Who records the decision.
Who communicates it.
Who remains accountable.
Those interfaces are the institutional equivalent of technical standards.
The Next Surveillance Problem Is Institutional
Biological surveillance is becoming more capable.
Sequencing is becoming faster and cheaper. Environmental surveillance is expanding. Computational analysis can identify relationships across datasets at a scale that was previously impossible. Standards are gradually improving the ability of information systems to communicate.
That progress is welcome.
But it changes the nature of the problem.
As technical barriers to connecting biological information fall, institutional barriers become more visible.
The next major failure in One Health surveillance may not occur because nobody had the data.
It may occur because several organisations had it, every system successfully exchanged it, and responsibility for acting upon what it showed remained unclear.
That is why interoperability must ultimately mean more than connecting databases.
We need institutions capable of connecting decisions as effectively as our systems are beginning to connect data.
References
- World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Environment Programme & World Organisation for Animal Health (2022). One Health Joint Plan of Action (2022–2026): Working Together for the Health of Humans, Animals, Plants and the Environment. Geneva: World Health Organization.
- World Health Organization (2022). Global Genomic Surveillance Strategy for Pathogens with Pandemic and Epidemic Potential, 2022–2032. Geneva: World Health Organization.
- World Health Organization (2022). WHO Guiding Principles for Pathogen Genome Data Sharing. Geneva: World Health Organization.
- European Centre for Disease Prevention and Control (2024). ECDC One Health Framework. Stockholm: ECDC.
- European Food Safety Authority & European Centre for Disease Prevention and Control. One Health Whole Genome Sequencing System. EFSA/ECDC.
- Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. doi:10.1038/sdata.2016.18.
Key Takeaways
- One Health surveillance is usually framed as a data-sharing problem; the harder problem is institutional, not technical.
- Making information interoperable does not make institutions interoperable — someone still has to own the alert and decide who acts.
- Each organisation can perform its own role correctly while the system as a whole recognises a threat too slowly.
- Preparedness needs a governance layer defined in advance — who convenes, who escalates, where accountability rests — plus the institutional trust that gives shared information its value.