A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict the epidemic trends of scrub typhus in China

• Published in: PloS one Vol. 20; no. 6; p. e0325905
• Main Authors: Peng, Pei-Ying, Duan, Hui-Ying, Xu, Lei, Sun, Ji-Qin, Ma, Li-Juan, Zu, Ya, Yan, Ting-Liang
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 23.06.2025; Public Library of Science (PLoS)
• Subjects: Analysis; Autoregressive moving-average models; Biology and Life Sciences; China; China - epidemiology; Communicable diseases; Data collection; Disease control; Distribution; Engineering and Technology; Epidemic models; Epidemics; Epidemiological Models; Epidemiology; Female; Forecasting; Forecasting - methods; Forecasting models; Forecasting techniques; Forecasts and trends; Health surveillance; Humans; Infectious diseases; Male; Medicine and Health Sciences; Models, Statistical; Morbidity; Moving averages; Orientia tsutsugamushi; People and Places; Physical Sciences; Prediction models; Research and Analysis Methods; Scrub typhus; Scrub Typhus - epidemiology; Seasonal variations; Seasons; Software; Time series; Trends; Typhus; White noise; China; United States > US
• DOI: 10.1371/journal.pone.0325905
• ISSN: 1932-6203

Scrub typhus is a deadly infectious disease that is frequently underdiagnosed. Forecasting the emergence of infectious diseases using epidemiological models has emerged as a crucial instrument for comprehending the dynamics of their occurrence. This research aimed to investigate epidemic traits and create a predictive model for scrub typhus in mainland China, employing the Seasonal Autoregressive Integrated Moving Average (SARIMA) time series method. Monthly records of scrub typhus cases were gathered from the China Center for Disease Control and Prevention, covering the timeframe from 2006 to 2019. From 2006 to 2018, a total of 142849 scrub typhus cases were reported in China, the females’ morbidity was higher than the males’ one ( P < 0.001). The ideal model was SARIMA (1, 0, 2) (1, 1, 1) 12 with its residual being white noise ( P > 0.05). This method forecasted scrub typhus cases between January and December 2019, with the predicted values for 2019 falling within the 95% confidence range. The research indicates that the SARIMA model accurately simulated the epidemiological patterns of scrub typhus across mainland China. Utilizing the SARIMA model is a practical approach for tracking scrub typhus cases in mainland China.