Objective To analyze the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Liupanshui from 2010 to 2024, and to provide scientific basis for the prevention and control of HFMD. Methods The surveillance data of HFMD in Liupanshui from 2010 to 2024 were collected and analyzed. The descriptive epidemiological method was used to analyze the epidemic characteristics, and the SARIMA model was established for prediction. Results From 2010 to 2024, a total of 47 884 HFMD cases were reported in Liupanshui, with an average annual incidence rate of 108.74/100 000. There were 847 severe cases, with a severe case rate of 1.77%. There were 27 deaths. HFMD remained prevalent and showed a high incidence trend every other year, with the peak incidence mostly from April to July. The district with the highest number of cases was Zhongshan District (17 625 cases, 36.81%), and the district with the lowest number of cases was Liuzhi Special District (3 620 cases, 7.56%). The high-risk groups were mainly scattered children (37 941 cases, 79.24%), followed by children in kindergartens and nurseries (8 103 cases, 16.92%) and students (1 730 cases, 3.61%). The median age of onset was 2 (1, 3) years, especially with a high incidence in the 0-5 years age group (45 209 cases, 94.41%). The male-to-female ratio was 1.54∶1. From 2010 to 2014, the dominant strains of HFMD in Liupanshui were alternately prevalent. After 2015, other enteroviruses became the main dominant strains. The SARIMA (1, 0, 1)(0, 1, 1)₁₂ model was an applicable model, and it is predicted that the incidence rate of HFMD will be 86.53 per 100 000 in 2025. Conclusions Children aged 5 years and under are the key target for the prevention and control of HFMD in Liupanshui. The SARIMA (1, 0, 1) (0, 1, 1)₁₂ model can effectively predict the incidence trend, and its predictive performance can be enhanced through continuous optimization. It is recommended to strengthen health education for key populations, promote EV-A71 vaccination, and improve the etiological surveillance network to achieve precise prevention and control.