Objective To analyze the epidemiological characteristics and changing trends of reported cases of brucellosis in Yanchi, Ningxia, in order to provide scientific basis for optimizing brucellosis prevention and control measures and formulating the next stage of prevention and control plans. Methods The data of reported brucellosis cases with current residential address in Yanchi County were retrospectively extracted from the information system of Yanchi County People’s Hospital and the infectious disease network direct reporting system of Yanchi County Center for Disease Control and Prevention from 2014 to 2025. The epidemiological characteristics and changing trends of brucellosis were analyzed in terms of time, region and population. Results A total of 4271 brucellosis cases were reported in Yanchi County from 2014 to 2025, with an average annual incidence rate of 225.4 per 100000 population. The annual number of cases fluctuated: the peak during the study period was observed in 2022 (522 cases), followed by consecutive declines from 2023 to 2025, with 479, 256 and 193 cases respectively. Cases were mainly concentrated in Huamachi Town, Dashuikeng Town and Wanglejing Township, accounting for 56.75% of all reported cases in the county. The male-to-female ratio was 2.20∶1. The age of patients ranged from 10 months to 88 years. Each 5-year age group within 40-64 years had more than 300 cases, summing to 2880 cases and accounting for 67.43% of the total. Farmers constituted the dominant occupational group (92.25%). Conclusions The number of reported brucellosis cases in Yanchi County fluctuated from 2014 to 2025, with a continuous decline after reaching the peak in 2022. Cases were mainly concentrated in Huamachi Town, Dashuikeng Town and Wanglejing Township. Most patients were aged 40-64 years, and male cases outnumbered female cases. Farmers constituted the predominant occupational group. It is necessary to strengthen surveillance, health education, and personal protection in key areas and among relevant occupational groups according to the distribution characteristics of cases.