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Research in veterinary science · 2026

Utility of saliva in rapid post-mortem rabies diagnosis in animals by lateral flow assay.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Bhalke Preeti Soundarya, Chandel Shubhangi, Reddy Vijayalakshmi, Lodha Lonika, Gupta Shipra, Kavya P, Lakshman Dilip, Chandrashekar Balaji, Sharada R, Ashwini M A, Isloor Shrikrishna, Mani Reeta S

Аннотация

INTRODUCTION: Animal rabies diagnosis traditionally relies on direct fluorescent antigen (DFA) test on post-mortem brain tissue, but its use is limited by infrastructure and accessibility. Saliva offers a simple, non-invasive alternative suitable for field testing. This study evaluates saliva-based rabies detection using lateral flow assay (LFA) and LN34 real-time RT-PCR, with the aim of developing practical, decentralized diagnostic tools with reliable sensitivity and specificity for resource-limited settings.

METHODS: The study included paired post-mortem animal brain and saliva samples. LFA and LN34 RT-PCR were performed on both sample types, while DFA was performed on brain samples. The performance of saliva as a screening sample was assessed by comparison with brain DFA results.

RESULTS: Compared with DFA, LFA performed on 239 brain samples showed 100% sensitivity (95% CI: 97.98-100) and 94.83% specificity (95% CI: 85.62-98.92), with kappa value of 0.94. The diagnostic performance of LFA and RT-PCR on saliva was assessed only in cases where DFA and RT-PCR results were concordant in the corresponding brain tissue. In saliva samples, LFA demonstrated a sensitivity of 89.50% (95% CI: 84.09-93.56) and a specificity of 93.88% (95% CI: 83.13-98.72) when compared with brain DFA and RT-PCR results.

CONCLUSIONS: Field surveillance is critical for rabies control. Saliva-based LFA detected 90% of rabies positive cases compared with brain DFA, offering a practical, non-invasive option where brain sampling is not feasible. Although specificity is lower, combining saliva LFA with RT-PCR as a tiered diagnostic approach can improve surveillance, case detection, and diagnostic capacity in resource-limited endemic settings.

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