Abstract
Goose circovirus (GoCV) is a recently identified pathogen in geese that is known to cause slow growth, feather disorder syndrome, and immunosuppression. Infection with GoCV may increase the risk of coinfections with multiple pathogens, leading to significant economic losses in the goose industry. However, due to a lack of serological detection methods, analysis of viral nucleic acids has been widely used in GoCV epidemiological surveys, which has limited accurate monitoring of the prevalence of GoCV. In this study, we developed and optimized an indirect ELISA method based on the prokaryotic-expressed recombinant GoCV capsid protein (△Cap-iELISA). The △Cap-iELISA was then used to test 349 goose serum samples collected from Guangdong, Shandong, and Fujian provinces during 2023 and 2024. The results showed that the positive rate of GoCV antibodies in the sampled geese was 71.06%. Further analysis indicated that the positive rate of GoCV antibodies increased with the age of the geese. In conclusion, we have developed a novel iELISA method that is well-suited for large-scale clinical detection and early diagnosis of GoCV infection. Notably, a significant correlation between age and the positive rate of GoCV antibodies among geese was observed based on this newly established method.