Zoonotic threats emerge where humans, animals, and the environment interact—through livestock production systems, wildlife interfaces, food chains, markets, and ecological conditions that shape exposure opportunities. That is why One Health surveillance is not an “add-on” to epidemic intelligence; it is the core operating model for detecting spillover early enough to prevent amplification.
When surveillance focuses only on human case detection, it often detects outbreaks late, after transmission has already occurred and response options have narrowed. Integrating animal health and environmental signals can identify risk upstream. In avian influenza, for example, unusual poultry die-offs or outbreaks in backyard flocks may precede human exposure. In Nipah, spillover risk is tightly linked to bat ecology and exposure pathways—such as contamination of food or environments, where bat–human contact becomes more likely.
For many zoonoses, animal morbidity and mortality function as leading indicators. Monitoring livestock and wildlife health—poultry flock die-offs, swine respiratory syndromes, unusual illness in wildlife, or shifts in veterinary reporting—can flag risk days to weeks before human cases appear. A One Health approach, therefore, improves both the timeliness and specificity of data, helping distinguish whether human clusters plausibly connect to an active animal epizootic or to unrelated respiratory disease circulation.
Global animal databases and platforms such as FAO EMPRES-i and the WOAH WAHIS contribute animal health data, references, and structured signals that are essential for interpreting zoonoses and can complement human-focused data and information.
From spillover signals to regional situational awareness: ABVC’s role in zoonoses surveillance
In 2025, two different zoonotic events happened almost at the same time that may pose threats to ASEAN’s regional health security. The outbreaks may begin locally, but their implications can become regional quickly. In India’s Kerala State, the World Health Organization (WHO) reported four confirmed Nipah virus cases (two deaths) between 17 May and 12 July 2025, prompting intensive contact tracing and heightened hospital alerts across multiple districts. Meanwhile, Cambodia faced recurrent human avian influenza A(H5N1) infections. The WHO documented 11 laboratory-confirmed cases notified between 1 January and 1 July 2025, with an unusual concentration in June and exposures frequently linked to handling sick or dead backyard poultry. Together, these events—one outside ASEAN but epidemiologically relevant, one within ASEAN with direct cross-border implications—illustrate why the ASEAN Biological Threats Surveillance Centre (ABVC) exists: to convert early warning signals into coherent, decision-ready information that supports timely action.
ABVC’s work is based on epidemic intelligence and biological threats surveillance. Its surveillance workflow is intentionally designed to be repeatable, rapid, and standardised across diseases and countries: collect structured and event-based signals, clean and validate, analyse trends and risks, visualise patterns for quick comprehension, and report outputs to stakeholders. In practice, ABVC operationalises this through scripted pipelines—methods that reduce manual friction, improve reproducibility, and allow the Centre to refresh analyses as new data emerges.
ABVC’s reports blend two complementary surveillance modes. Indicator-based surveillance draws on routine, structured data—time-series trends, case counts, and other standardised indicators that can be tracked over time. These feeds are essential for identifying abnormal increases, shifts in seasonality, and geographic spread patterns.
Event-based surveillance captures unstructured or semi-structured signals—such as subnational reports, alerts, official statements, and credible outbreak notifications. Event-based intelligence is particularly important in the early phase of outbreaks, when formal reporting may lag, definitions may still be evolving, or epidemiologic details may emerge in fragments.
To support this dual approach, ABVC pulls from established open and platform sources.: Bluedot Platform, WHO EIOS, and FluNet. This selection reflects a practical design principle: ABVC needs sources that are (a) sufficiently broad to cover multi-country risk, (b) frequently updated, and (c) structured enough to feed analytic workflows without excessive manual handling.
The purpose of this collection layer is not just to gather “more data.” It is to create an integrated and traceable evidence base—one that can be refreshed quickly, checked against other sources, and transformed into standardised representations across ASEAN Member States.
Analysis: Translating signals into risk-relevant indicators
ABVC’s analytic layer focuses on turning heterogeneous records into comparable regional indicators and operationally relevant narratives. In the avian influenza pipeline, the analytic steps include typical transformations such as standardising column names, deriving analytic fields, and separating animal- and human-impact signals. That last step is particularly important for zoonoses: signals may originate in animal health systems before they appear in human case reports, and those two streams must be analysed in relationship—not in isolation.
For zoonoses specifically, ABVC’s analytic posture also prioritises exposure narratives—animal contact, contaminated environments, or limited human-to-human transmission—because these details translate directly into practical actions: clinician alerts, infection prevention and control (IPC) reminders, animal health coordination, and risk communication targeted to the right settings.
Zoonotic surveillance for regional readiness
Zoonoses surveillance is a race against time and ambiguity. Early signals are noisy, definitions differ across systems, and response capacity is uneven. ABVC’s structured workflow—spanning data collection, validation, analysis, visualisation, and reporting—reduces friction at each stage, enabling ASEAN stakeholders to move more quickly from signal to a shared understanding.
In a year when Nipah events in South Asia and avian influenza spillovers within ASEAN both tested regional vigilance, the strategic case for ABVC is straightforward: early warning is only as good as the system that translates warnings into timely, coordinated readiness. By institutionalising repeatable pipelines and embedding One Health thinking into epidemic intelligence, ABVC strengthens ASEAN’s ability to anticipate zoonotic risk, communicate it clearly, and support decisive action before local spillover becomes a wider regional threat.
Learn more about the ASEAN Biological Threats Surveillance Centre: https://asean-phe.org/asean/data-publications/disease-alert
