Objective To construct time-series by adopting autoregressive integrated moving average (ARIMA) model for analyzing the trend and genotype characteristics of single-center human papillomavirus (HPV) infection in Tianjin area. Methods A total of 7 236 female patients who underwent HPV testing in a hospital from January 2018 to December 2022 were selected. HPV infection status and genotype distribution in Tianjin area from 2018 to 2022 were compared. ARIMA model time-series was constructed, and model fitting was analyzed. The number of HPV infections in 2023 was predicted and compared with the actual occurrence, the predictive performance of the model was evaluated. Results HPV infection rate in Tianjin area from 2018 to 2022 was 14.41%, with the highest rate (15.47%) in the age group of 31-40 years. Among the positive specimens, the proportion of single type HPV infection was the highest, accounting for 73.54% (767/1 043), with high-risk HPV being the main type. The highest infection rates of low-risk and high-risk types were type HPV-6 (2.59%) and type HPV-16 (16.06%), respectively. ARIMA model was constructed, and the optimal model was ARIMA (0,1,2)(0,1,1)₁₂, with akaike information criterion (AIC) and bayesian information criterion (BIC) values of 3.877 and 4.005, respectively. There was no statistical significance in Ljung-Box Q=8.828 showed by white noise test (P>0.05). The number of HPV infection in 2023 was predicted by the model. The overall trend of the actual value and the predicted value was basically consistent, RMSE, MAPE and MAE of the model were 6.289, 34.149 and 4.706, respectively, suggesting that the model had a good prediction effect. Conclusion Among the female population in Tianjin area, HPV infection is mainly caused by single, high-risk type, with HPV-16 having the highest infection rate. There is seasonal variation in HPV infection in Tianjin. ARIMA model has good prediction effect on the prevalence trend of HPV infection, which is suitable for short-term prediction.