Evaluating the impact of avian paramyxovirus type 1 infection in poultry at live bird markets in Nigeria: defining hurdles to sustainable agriculture

作者：Abel B. Ekiri, A. M. Wakawa, Scott M. Reid, Joe James, Craig S. Ross, Alexander M. P. Byrne, Tom Lewis, Joshua G. Lynton‐Jenkins, Kehinde Adebowale, Erik Mijten, Gabriel Varga, Ian H. Brown, Ashley C. Banyard, A. J. C. Cook · 发表于：BMC Veterinary Research · 年份：2025 · DOI：10.1186/s12917-025-04508-2 · 被引用次数：6 · 研究领域：Virology and Viral Diseases、Respiratory viral infections research、Microbial infections and disease research

BACKGROUND: Infectious diseases including Newcastle disease (ND) impair poultry productivity and represent a significant burden to sustainable agriculture in Nigeria. This study aimed to investigate the active circulation and seroprevalence of Newcastle disease virus (NDV) caused by virulent forms of avian paramyxovirus type-1 (APMV-1) in poultry at live bird markets (LBMs) across Nigeria. METHODS: A cross-sectional study of 18 LBMs was conducted within three states in Nigeria (Kano, Oyo, and Abuja). Paired swab and tissue samples (n = 413) were collected from birds on FTA cards and tested for APMV-1 using real-time reverse transcription polymerase chain reaction (rRT-PCR). A subset of rRT-PCR-positive samples were selected for whole genome sequencing based on the originating species (chicken, duck, geese), date, and market location to provide a broad range of isolates for characterisation. Blood samples (n = 405) were also collected from birds and the seroprevalence of APMV-1 antibodies was measured using an enzyme-linked immunosorbent assay (ELISA). RESULTS: APMV-1 RNA was detected in 21.5% (89/413) of samples from LBMs by rRT-PCR. At least one APMV-1 positive sample was detected in 55.6% (10/18) of LBMs. The largest proportion of APMV-1-positive markets was in Kano (83.3%, 5/6), whereas the lowest was in Oyo (16.7%, 1/6). Assessment of genetic data demonstrated that genotype XIV.2 APMV-1 was circulating within Nigeria with the viruses detected clustering closely with other...