One Health Surveillance

What is surveillance?

“Public health surveillance is the continuous, systematic collection, analysis and interpretation of related data for action.
WHO

For action. Surveillance is not simply the routine collection or display of data. It connects observation with assessment, communication and decisions: early warning, outbreak investigation, risk assessment, response or evaluation of control measures.

Data generation is usually decentralised. Signals originate in communities, health facilities, laboratories, farms, veterinary field services, food-control systems and environmental monitoring networks. They are verified, analysed or aggregated at subnational and national levels, where authorities coordinate action and meet reporting obligations. Feedback should return to the sites and communities that generated the information.

Why are surveillance systems mostly sectoral and diverse?

Current surveillance landscapes have developed over decades within different professional, legal and administrative structures. Human-health authorities, veterinary services, food-safety institutions, plant-health services and environmental agencies have distinct mandates, resources and international reporting obligations.

At the international level, surveillance is embedded in sector-specific legal, normative and reporting frameworks. These are not disease-specific surveillance systems themselves. Rather, they define national capacities, technical standards and pathways for international information exchange:

Public health – International Health Regulations (IHR): a legally binding framework requiring countries to maintain capacities to detect, assess, notify and respond to public-health risks and events with potential international implications.
Animal health – WOAH standards and WAHIS: WOAH standards define requirements for animal-disease surveillance and notification, while authorised national authorities report listed and emerging diseases in domestic and wild animals through the World Animal Health Information System.
Plant health – International Plant Protection Convention (IPPC): an international treaty framework for plant protection, pest surveillance and the reporting of relevant pest outbreaks or changes in pest status.
Environmental surveillance: information is distributed across specialised systems for water, wastewater, air, climate, soil, biodiversity, land use, vectors and wildlife rather than organised through one equivalent global notification framework.

Within these frameworks, countries operate multiple national and subnational surveillance programmes. These include case-based, syndromic and laboratory surveillance in human health; notifiable-disease, herd and wildlife surveillance in animal health; food-chain and plant-pest monitoring; and vector, water, wastewater, climate, and biodiversity surveillance. Data collection often begins locally, while verification, analysis, response and international notification take place at higher administrative levels.

These systems are designed for different purposes. Detecting a human outbreak requires different definitions, reporting intervals and data-protection arrangements from demonstrating freedom from an animal disease, monitoring food contamination or tracking wildlife populations. Specialised systems are therefore necessary and do not inherently indicate fragmentation or failure.

The One Health question is not whether existing surveillance systems should be replaced. It is where their information or functions need to be connected because a particular risk cannot be adequately understood or managed within one system alone

Figure 1. A hypothetical coordinated surveillance and information-sharing system. Illustrates one hypothetical way of connecting selected outputs from such systems through joint surveillance and information-exchange mechanisms. It should not be understood as a universal architecture or as a replacement for the underlying specialised systems.

Source: FAO, WHO and WOAH. Surveillance and Information Sharing Operational Tool, 2022, Figure 3. Reproduced unchanged

What makes surveillance One Health?

KEY MESSAGE Surveillance turns local observations into information for action. One Health becomes relevant where a defined surveillance purpose requires information or operational functions from more than one specialised system.

“One Health surveillance describes the systematic collection, validation, analysis, interpretation of data and dissemination of information collected on humans, animals and the environment to inform decisions for more effective, evidence- and system-based health interventions.” Stärk et al., 2015

OHHLEP does not provide a single universal definition of One Health surveillance. Instead, it describes a model One Health surveillance system that integrates surveillance across human, animal and environmental domains and extends pathogen- and disease-based surveillance to include drivers of disease emergence and spread.

The defining feature is collaboration across the sectors relevant to the surveillance objective. Collaboration may occur at one or several stages:

priority setting and surveillance design;
detection, reporting and verification;
sampling and laboratory testing;
information / data exchange and interoperability;
analysis, interpretation and joint risk assessment;
response, communication, feedback and evaluation.

The degree of collaboration may differ within the same system. Planning can be undertaken jointly while routine data collection remains sectoral; laboratory methods may be harmonised without a shared database; and information collected separately may be interpreted jointly. Bordier and colleagues distinguish arrangements ranging from separate sectoral activities and consultation to joint implementation by multisectoral working groups or permanent bodies.

Figure 2. Possible degrees of collaboration across the surveillance process. Collaboration can occur with different intensity at each stage of surveillance. Planning, sampling, laboratory testing, data sharing, analysis and dissemination do not necessarily have to follow the same organisational model.

Source: Bordier et al. Characterisation of One Health surveillance based on a systematic literature review and expert-opinion elicitation, 2018; related review published in Preventive Veterinary Medicine

Existing organisational and technical setups

Coordinated sectoral systems: alerts, meetings, investigations or responses are linked while primary systems remain separate.
Shared information products: joint bulletins, dashboards, risk assessments or situation reports combine selected outputs.
Interoperable or federated systems: defined data are exchanged through standards, APIs or an interoperability layer while sectors retain their systems and data ownership.
Shared operational platforms: selected reporting, case, laboratory or response workflows are conducted in one application.
Hybrid or use-case-specific setups: shared functions coexist with specialist systems and only the sectors and data needed for a particular hazard are connected.

Example: Rift Valley fever illustrates how collaboration can change both detection and response. The mosquito-borne virus mainly affects livestock but can also infect people. Veterinary services may first observe clusters of abortions or deaths among young animals, while vector and environmental surveillance indicate conditions favourable for transmission; human cases may only become visible later. When these signals are shared, authorities can recognise that they are part of the same event, target laboratory testing and field investigations more quickly, and coordinate animal-health, vector-control and public-health measures. Without this exchange, early animal or environmental warnings may remain isolated and the outbreak may only be recognised once human illness is reported. Figure 3 illustrates this added value: a local animal or environmental signal can trigger joint investigation and information exchange across sectors and administrative levels, rather than waiting for each sector to identify the event independently.

Figure 3. One Health event-based surveillance from community detection to international reporting. Figure 3 illustrates a different aspect of collaboration than Figure 2. Rather than comparing degrees of integration, it follows an event through the surveillance pathway: a signal is detected at community level, may trigger coordinated human-, animal- and environmental-health investigation, and is reported through subnational and national structures. Results and recommendations flow back towards the local actors and communities from which the signal originated.

Source: Ghai et al. A generalizable One Health framework for the control of zoonotic diseases. Scientific Reports, 2022, Figure 3. CC BY 4.0; reproduced unchanged.

KEY MESSAGE One Health surveillance is defined by purposeful collaboration, not by the number of datasets stored in one place. Collaboration may be organisational, analytical, operational or technical and can occur at selected stages of the surveillance pathway.

How existing frameworks describe system design and implementation

Published frameworks address different but connected aspects of surveillance development: the information required for a defined decision, the broader development process and the organisation of multisectoral collaboration.

Surveillance design follows the reverse direction of operational surveillance. Once a system is running, surveillance activities generate information that informs an intervention and, ultimately, its intended outcome. During the design phase, however, the process begins with the health threat and the intervention or decision under consideration. From this, the required information is defined, followed by the surveillance activities needed to produce it. This reverse logic helps ensure that data collection is linked to a specific decision rather than becoming an objective in itself.

Figure 4. Surveillance system design derived from the intended intervention and information need. The upper pathway shows the operational sequence from surveillance to information and intervention. The lower pathway reverses this sequence for system design: the intended intervention determines the information required and, in turn, the surveillance activities to be established.

Source: EFSA. Coordinated surveillance system under the One Health approach for cross-border pathogens, 2023, Figure 1. CC BY-ND 4.0; reproduced unchanged.

OHHLEP places this design logic within a broader development process. Its six steps move from an agreed scope and defined data requirements through system design, governance and integrated protocols to a joint implementation roadmap. The framework also highlights system mapping, feedback mechanisms and the need for flexibility as risks, technologies and capacities change.

Figure 5. Six steps proposed by OHHLEP for developing a One Health surveillance system

Source: One Health High-Level Expert Panel. Developing One Health surveillance systems. One Health, 2023, Figure 1. [6] CC BY-NC-ND 4.0; reproduced unchanged.

Bordier and colleagues focus on where collaboration is organised. At the policy level, actors define the rationale, objectives and allocation of resources. At the institutional level, they establish roles, responsibilities and collaboration arrangements. At the operational level, these arrangements are translated into procedures, technical tools and routine activities. Contextual, organisational and sociological conditions influence all three levels.

Figure 6. Policy, institutional and operational organisation of multisectoral surveillance collaboration

Source: Bordier et al. One Health Surveillance: A Matrix to Evaluate Multisectoral Collaboration. Frontiers in Veterinary Science, 2019, Figure 2. CC BY 4.0; reproduced unchanged.

The SIS-OT applies a related process to existing national systems. Stakeholders gather information, assess 32 activities, prioritise gaps and develop a roadmap and development plan. The tool is designed to bridge existing systems rather than establish new sectoral surveillance structures.

Existing tools, platforms and assessment approaches

The available resources operate at different levels. Some provide an overarching concept for collaboration, others support governance, surveillance assessment or joint risk assessment, while digital platforms provide technical functions for data collection and outbreak managment. They are complementary but not interchangeable.

The Tripartite Zoonoses Guide, developed by FAO, WHO and WOAH, provides country-level guidance for addressing zoonotic diseases through multisectoral collaboration. Its operational tools address distinct but connected functions and may be used independently or together.

The Multisectoral Coordination Mechanism Operational Tool supports the establishment or strengthening of the governance structure through which ministries and agencies coordinate their activities.
The Surveillance and Information Sharing Operational Tool assesses existing arrangements for coordinated surveillance and information exchange. It supports stakeholder mapping, capacity assessment, prioritisation and the development of a roadmap and implementation plan. It is intended to bridge existing systems rather than replace them.
The Joint Risk Assessment Operational Tool provides a structured process through which representatives from relevant sectors jointly assess zoonotic-disease risks and translate the findings into aligned risk-management and communication options.

SORMAS and DHIS2 can both form part of a One Health setup, but neither is a complete One Health system by default. Their role depends on configuration, participating institutions, interfaces with mandatory systems and how the resulting information is used. SORMAS provides operational surveillance and response workflows; DHIS2 can be configured as an animal-health system, a shared environment or part of an interoperable architecture.

KEY MESSAGE Collaborative Surveillance provides a broad framework for multisource and multisectoral public-health intelligence. The Tripartite operational tools address specific governance, surveillance and risk-assessment functions, while platforms such as SORMAS and DHIS2 provide technical infrastructure. None of these elements alone constitutes a complete One Health surveillance system.

Examples from practice

The examples below are not equivalent in scope or maturity. Four describe operational surveillance programmes or platforms; two describe the government and information-architecture arrangements that enable cross-sectoral surveillance. Each case is presented with the limits of the available evidence.

Tanzania: AfyaData community surveillance

What was implemented. AfyaData was developed as a mobile and web-based participatory surveillance system in Morogoro and Ngorongoro districts. Trained community reporters and officials from the human- and animal-health sectors could submit events in near real time, review reports and return guidance to reporters.
What the evidence shows. During the first five months of deployment, 1,915 clinical events were reported: 1,816 in livestock and 99 in people. The study demonstrates that a shared reporting and feedback pathway can connect local signals with responsible authorities across the two sectors.
Scope and limitations. The publication reports early implementation and reporting volume. It does not provide a controlled comparison of detection speed, health outcomes or nationwide integration with the statutory human- and animal-health databases.

One Health collaboration begins at the point of detection rather than at a central data warehouse.
A single reporting tool can support both human- and animal-health events while preserving sector-specific follow-up.
Feedback to community reporters is part of the surveillance pathway, not an optional add-on.

EVIDENCE BOUNDARY A promising operational model at community level; evidence of comparative effectiveness remains limited.

Italy: integrated West Nile virus surveillance in Emilia-Romagna

What was implemented. The regional system has combined surveillance in people, horses, wild birds and mosquitoes since 2009. From 2013, confirmed virus circulation in any monitored species within a province could trigger nucleic-acid testing of blood donations, rather than waiting for a human clinical case.
What the evidence shows. In 2013 and 2014, animal and vector surveillance provided warning that enabled six infected blood donations to be identified before the first reported human cases in the same provinces. For 2009-2015, an economic evaluation estimated a net saving of EUR 160,921 compared with a human-surveillance-only scenario and EUR 1.21 million in avoided blood-testing costs.
Scope and limitations. This is a mature but highly specific regional system. Its benefits depend on local West Nile epidemiology, blood-safety rules and the existing surveillance network; the economic estimates should not be transferred directly to other hazards or settings.

Signals from animal and vector surveillance directly change a human-health intervention.
Collaboration can produce earlier warning than clinical surveillance alone.
The added value has been examined in operational and economic terms.

DOCUMENTED ADDED VALUE Earlier warning supported targeted blood screening and prevented reliance on the first recognised human case as the trigger for action.

Denmark: DANMAP antimicrobial resistance surveillance

What was implemented. The Danish Integrated Antimicrobial Resistance Monitoring and Research Programme (DANMAP) was established in 1995 by the ministries responsible for food, agriculture and health. It combines data on antimicrobial consumption and antimicrobial resistance in bacteria from food animals, food and people and publishes joint annual assessments.
What the evidence shows. The programme supports comparison of resistance patterns across reservoirs, analysis of associations between antimicrobial use and resistance, and identification of possible transmission routes. A published review reports that DANMAP monitoring and associated research contributed to restrictions or bans on several antimicrobial agents used in food animals in Denmark and the European Union.
Scope and limitations. DANMAP is a focused national programme for antimicrobial use and resistance. Its integration lies in harmonised surveillance and joint interpretation; it is not a shared case-management platform for all One Health hazards.

Several specialist data streams can remain distinct while producing one national assessment.
Long-term continuity allows trends in use and resistance to be examined across sectors.
The surveillance output is explicitly linked to research and policy, not only annual reporting.

MATURE NATIONAL MODEL DANMAP shows sustained cross-sectoral surveillance built around a defined problem rather than a universal One Health database.

Malawi: DHIS2-based One Health Surveillance Platform

What was implemented. Malawi developed the One Health Surveillance Platform using DHIS2 as the technical backbone for electronic Integrated Disease Surveillance and Response. The work reused earlier eIDSR experience and national digital-health infrastructure and was expanded nationally during the COVID-19 pandemic.
What the evidence shows. The 2026 implementation study reports that weekly IDSR completeness reached 97.8% and timeliness 74.5% in 2024. The platform could be adapted during an emergency and sustained for routine reporting after the initial pandemic response.
Scope and limitations. The measured results relate mainly to human-health IDSR. The authors describe interoperability with animal- and environmental-health systems as a further development priority. The case therefore documents a national digital foundation for One Health surveillance, not a completed multisectoral integration.

Existing national infrastructure and technical capacity were reused rather than replaced.
The platform was developed iteratively and adapted to an emerging emergency.
A system may carry a One Health architecture and ambition before all sectoral connections are operational.

IMPORTANT DISTINCTION The paper demonstrates stronger electronic surveillance; it does not yet demonstrate full human-animal-environment data integration.

Tanzania: governmental One Health coordination

What was implemented. Tanzania established a National One Health Platform under the Prime Minister’s Office. The structure includes the One Health Coordination Desk, a national multisectoral technical committee and four technical working groups, one of which focuses on surveillance. The desk and the National One Health Strategic Plan were formally launched in 2018; the coordination function was elevated to a One Health Section in 2022.
What the evidence shows. The published case study documents how One Health collaboration was embedded in government structures, with defined links to sector ministries, subnational authorities and outbreak-response functions. The platform provides a forum for joint planning, information sharing and coordination across institutions that retain their own operational mandates.
Scope and limitations. This is an example of institutionalisation rather than a shared surveillance database. Published evidence describes the structure and implementation process, while quantitative effects on routine detection and response have not been established for the platform as a whole.

Governmental placement can provide a formal home for cross-sectoral surveillance coordination.
Surveillance collaboration may be organised through committees, focal points and agreed responsibilities without a common software system.
Institutional design must fit existing public-administration, staffing and budgeting rules.

GOVERNANCE EXAMPLE The Tanzanian platform enables coordinated surveillance and response but should not be described as a surveillance application.

KEY MESSAGE One Health surveillance has been implemented through very different arrangements. The common feature is not a single platform, but a defined connection between sectoral information and joint action. The strength of the evidence varies: it is strongest for long-running disease-specific and AMR programmes, and more limited for newer digital and continental architectures.

African Union: One Health Data Alliance Africa and the AU Digital One Health Platform

What was implemented. The African Union One Health Data Alliance Africa project produced a continental Digital One Health Information Policy, an associated information-architecture framework and the African Union Digital One Health Platform (AU-
DOHP). The architecture is domain-oriented and federated: countries and sectoral domains retain responsibility for their data while common standards and services support exchange and analysis.
What the evidence shows. The policy and architecture were endorsed through African Union processes, and AU-IBAR reports the rollout of the digital platform in 2025. Subsequent regional consultations have focused on connecting national and Regional Economic Community surveillance data to the platform.
Scope and limitations. AU-OHDAA is best understood as continental governance, architecture and platform implementation rather than one central surveillance database. Public documentation describes policy adoption, platform development and rollout.

A continental approach can connect national systems without transferring ownership of all primary data to one institution.

Policy, governance, standards, capacity development and technology are treated as parts of the same implementation effort.
The current evidence concerns architecture and rollout more than demonstrated surveillance outcomes.

MATURITY The continental framework and platform have moved beyond concept development, while integration with national and regional data sources remains an ongoing process.

Challenges, facilitators and existing responses

Reported barriers are organisational as well as technical. OH-EpiCap assessments of eleven European multisectoral systems found recurring weaknesses in shared leadership, harmonised indicators, data practices and evidence of impact. A systematic review of integration mechanisms identified heterogeneous data, limited resources, inconsistent procedures, weak laboratory capacity and different reporting policies.

These tools structure assessment and collaboration but do not remove differences in authority, financing, incentives or technical capacity. Most published outputs are roadmaps, agreements, procedures, reporting indicators or user-experience measures. Evidence on long-term human, animal and ecosystem outcomes remains more limited.

Figure 7. Challenges reported for four integration mechanisms

Source: George et al. A systematic review on integration mechanisms in human and animal health surveillance systems. One Health Outlook, 2020, Table 4. CC BY 4.0; reproduced unchanged.

Key international resources and documentation

WHO disease surveillance – Definition and functions of public-health surveillance.
International Health Regulations – Binding public-health capacities and notification framework.
WOAH WAHIS – International animal-disease reporting and information.
WHO Collaborative Surveillance – Collaboration across data sources, systems, sectors and levels.
Tripartite Zoonoses Guide – Multisectoral management of zoonotic diseases.
SIS-OT – Assessment and roadmap development for coordinated surveillance and information sharing.
MCM OT – Multisectoral coordination mechanisms.
JRA OT – Joint risk assessment for zoonotic disease threats.
OHHLEP surveillance framework – Six-step framework and broader system components.
SORMAS – Open-source operational surveillance and outbreak-response platform.
DHIS2 One Health – Animal-health toolkit and options for shared or interoperable systems.
AU Digital One Health framework – Continental policy and federated information architecture.