One Health evaluation of human and animal tuberculosis surveillance system in Kwara State, Nigeria

In Nigeria, inadequacies in human and animal disease surveillance continue to impede attempts to control tuberculosis (TB), which is still a persistent public health problem. This study was designed using a mixed-methods approach utilising a globally validated disease surveillance system evaluation tool (quantitative) and in-person interviews of TB surveillance stakeholders (qualitative) in Kwara State, north-central Nigeria, within a One Health framework. Key evaluation metrics included usefulness, flexibility, stability, acceptability, data quality, timeliness, sensitivity, positive- and negative- predictive value (PPV and NPV). All analyses were done in SPSS v.29. Our findings revealed significant disparities between the human and animal TB surveillance systems and the absence of One Health collaboration, communication, or coordination between both sectors. The human TB surveillance system was significantly better in terms of usefulness (90.5%), flexibility (66.7%), stability (77.8%), data quality (67.3%), and timeliness (68.6%). The system had very high sensitivity, robust case detection with a high PPV and NPV (100%). The animal TB surveillance system, on the other hand, demonstrated limited functionality, with inadequate adaptability (37.5%) and usefulness (47.0%). It relied only on postmortem examination without laboratory validation, ante-mortem testing, or traceability. Analyses of abattoir data in Kwara State for obvious TB lesions among slaughtered cows reported a percentage ranging from 4.1% (887/21,709) to 3.2% (900/28,138) in 2024 and 2025, respectively. Overall, there was no functional connectivity between the human and animal health systems, indicating a significant flaw in the implementation of One Health in TB surveillance. To improve tuberculosis detection and match Kwara State’s surveillance system with international best practices, it is imperative to strengthen diagnostic capacity, increase animal-level surveillance, and create integrated human-animal reporting channels.