Prevalence and Epidemiological Characteristics of Mycoplasma synoviae Infection in Chickens in Mainland China

Mycoplasma synoviae (MS) poses a continuous threat to the poultry industry in Mainland China, yet a comprehensive nationwide assessment remains lacking. This systematic review and meta-analysis quantified the pooled prevalence of MS and evaluated key epidemiological characteristics and sources of heterogeneity. Peer-reviewed studies were retrieved from multiple databases, and random-effects models were utilized to estimate and compare pooled seroprevalence and molecular detection prevalence. The results revealed a heavy MS infection burden characterized by a distinct diagnostic disparity: a high serological prevalence co-existed with a moderate molecular detection prevalence, reflecting widespread past exposure, chronic carrying, or vaccination. Geographically, the Northwest region exhibited the highest seroprevalence (61.8%), though inter-regional differences were not statistically significant (p = 0.152). Among production types, breeder flocks maintained a relatively high pooled prevalence of 69.6% (95% CI: 40.5–92.0%), although differences among production types were not statistically significant. Subgroup analysis demonstrated a statistically significant difference among age groups; however, the available data did not support definitive conclusions regarding age-specific risk patterns. Breeder flocks exhibited a relatively higher pooled prevalence than layers and broilers, suggesting a potential epidemiological role that warrants further investigation. In conclusion, MS appears to be widely distributed in chickens in mainland China. Differences between the serological and molecular detection results highlight the complexity of interpreting MS prevalence estimates. Given the substantial heterogeneity among studies, the findings should be interpreted cautiously. Future studies incorporating standardized surveillance and detailed vaccination histories are needed to better understand MS epidemiology and support evidence-based control strategies.