ArticlePloS one2025
A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict the epidemic trends of scrub typhus in China.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Machine learning and time-series approaches for forecasting bacterial blight of pomegranate.Frontiers in plant science · 2026Article
- Modeling the seasonal epidemic of human brucellosis in China: A comparative time series analysis.PloS one · 2026Article
- Predictive and interpretable machine learning for COVID-19 resurgences: the role of SARS-CoV-2 variants in the post-pandemic era.BMC infectious diseases · 2025Article
- Prediction of Trends and Bioclimatic Factors Influencing the Monthly Incidence of Zoonotic Cutaneous Leishmaniasis Using Arima and Sarima Time Series Models in Maraveh Tappeh County, Golestan Province, Iran.Journal of arthropod-borne diseases · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
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.
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