ONE HEALTH APPROACHES TO EMERGING INFECTIOUS DISEASE SURVEILLANCE: A SYSTEMATIC REVIEW

Background: Emerging and re-emerging infectious diseases frequently arise at interfaces connecting humans, domestic animals, wildlife, vectors, and shared environments. Conventional surveillance systems are commonly organized within sector-specific structures and may therefore fail to detect signals arising outside the human health system. One Health surveillance seeks to overcome this limitation by integrating epidemiological, veterinary, wildlife, vector, environmental, genomic, and increasingly digital data for earlier threat detection and coordinated response.The objective is to systematically examine One Health approaches used for emerging infectious disease surveillance, characterize the major surveillance models and technologies employed, evaluate their contribution to early warning and risk characterization, and identify recurrent barriers to operational integration. Materials and Methods: A systematic-review framework consistent with PRISMA 2020 was used. Eligible primary studies described an operational or evaluated surveillance approach incorporating at least two One Health domains—human, animal, vector, wildlife, or environmental health—and reported surveillance outputs, implementation outcomes, pathogen detection, risk characterization, or system performance. Purely conceptual articles, narrative reviews, single-sector surveillance studies without an integrative component, and studies without surveillance relevance were excluded. Because of substantial heterogeneity in pathogens, surveillance objectives, sampling strategies, technologies, and outcomes, findings were synthesized narratively. Results: A total of 1,917 records were identified. After removal of 502 duplicates, 1,415 records underwent title and abstract screening. Of 133 full-text reports assessed for eligibility, 121 were excluded and 12 primary studies were included in the qualitative synthesis. Principal approaches included risk-targeted wildlife surveillance; linked human-animal sentinel surveillance; integrated serosurveillance; vector and multispecies surveillance; wastewater and aggregated environmental surveillance; genomic and metagenomic surveillance; and multisectoral preparedness and predictive surveillance. Four studies were judged at low overall risk of bias, seven had some concerns, and one had high concern, principally because of incomplete cross-sector data or surveillance coverage. Integrated systems expanded situational awareness and supported source characterization, but few studies quantified gains in detection time, sensitivity, cost-effectiveness, or health outcomes attributable specifically to One Health integration. Conclusion: One Health surveillance expands infectious-disease intelligence beyond clinical case detection and is particularly valuable for zoonotic, vector-borne, and environmentally mediated threats. Its strongest applications combine risk-based sampling with rapid laboratory diagnostics, genomic characterization, interoperable information systems, and formal cross-sectoral decision pathways. Sustainable governance, standardized data sharing, environmental-sector participation, laboratory capacity, long-term financing, and prospective evaluation are required to translate One Health surveillance from a collaborative concept into an effective early-warning infrastructure.