Effectiveness of One-Health surveillance for early pathogen detection
1
Faculty of Clinical Sciences, University of Nigeria Teaching Hospital, Enugu, Nigeria
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
INTRODUCTION:
The One-health approach integrates human, animal, and environmental surveillance to facilitate the detection of novel and re-emerging pathogens. Early-warning promise has risen with advances in wastewater-based epidemiology and genomic sequencing, but integration-related lead time analysis and its barriers have not been well established.
METHODS:
A wide-ranging narrative review of peer-reviewed literature, high-impact empirical studies, technical reports, and authoritative guidance published 2010–2025 was conducted. We prioritized empirical evaluations of wastewater and genomic surveillance, research linking animal or wildlife surveillance to human events, and analyses of governance, capacity, and data-sharing that affect signal integration.
RESULTS:
Wastewater-based surveillance consistently monitored community infection trends, and in several contexts yielded earlier signal lead time than clinical case counts and hospital admissions.¹,² Wastewater sequencing and targeted genomic pipelines identified variant-level mutations and revealed cryptic translation or emerging variants before widespread clinical recognition ³,⁴. Animal and wildlife surveillance evidence is promising for identifying reservoirs and risk mapping but is sporadic and unevenly linked to human systems. Common implementation barriers: dis-aggregated governance and legal structures; limited decentralized laboratory and sequencing capacity; non-standardized meta data; and financing gaps which impede multi-sectoral signal integration.³,⁵
RESULTS:
Integrated One-health surveillance has been shown to enhance early warning when wastewater and genomics pipelines are operationalized in connection with human and animal surveillance and when data governance, interoperability, and local capacity are within reach. To get from promise to practice, policy makers need to focus on interoperable metadata standards, routine wastewater–genomic pipelines, legally supported data-sharing agreements, investments in decentralized sequencing, and locally led participatory surveillance to address equity gaps.
The One-health approach integrates human, animal, and environmental surveillance to facilitate the detection of novel and re-emerging pathogens. Early-warning promise has risen with advances in wastewater-based epidemiology and genomic sequencing, but integration-related lead time analysis and its barriers have not been well established.
METHODS:
A wide-ranging narrative review of peer-reviewed literature, high-impact empirical studies, technical reports, and authoritative guidance published 2010–2025 was conducted. We prioritized empirical evaluations of wastewater and genomic surveillance, research linking animal or wildlife surveillance to human events, and analyses of governance, capacity, and data-sharing that affect signal integration.
RESULTS:
Wastewater-based surveillance consistently monitored community infection trends, and in several contexts yielded earlier signal lead time than clinical case counts and hospital admissions.¹,² Wastewater sequencing and targeted genomic pipelines identified variant-level mutations and revealed cryptic translation or emerging variants before widespread clinical recognition ³,⁴. Animal and wildlife surveillance evidence is promising for identifying reservoirs and risk mapping but is sporadic and unevenly linked to human systems. Common implementation barriers: dis-aggregated governance and legal structures; limited decentralized laboratory and sequencing capacity; non-standardized meta data; and financing gaps which impede multi-sectoral signal integration.³,⁵
RESULTS:
Integrated One-health surveillance has been shown to enhance early warning when wastewater and genomics pipelines are operationalized in connection with human and animal surveillance and when data governance, interoperability, and local capacity are within reach. To get from promise to practice, policy makers need to focus on interoperable metadata standards, routine wastewater–genomic pipelines, legally supported data-sharing agreements, investments in decentralized sequencing, and locally led participatory surveillance to address equity gaps.
| eISSN: | 2654-1459 |
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