Evidence map›Paper›PMID 39720619›Full record

ArticleInfection and drug resistance2024

Comparison of ARIMA and Bayesian Structural Time Series Models for Predicting the Trend of Syphilis Epidemic in Jiangsu Province.

Fengquan Zhang, Yanyan Li, Xinxiao Li, Bingjie Zhang, Chenlu Xue, Yongbin Wang

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Article in Infection and drug resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Fengquan Zhang *Center for Experimental Teaching, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Yanyan Li *Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Xinxiao LiDepartment of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Bingjie ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Chenlu XueDepartment of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Yongbin WangDepartment of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study sets out to explore the forecasting value in syphilis incidence of the Bayesian structural time series (BSTS) model in Jiangsu Province. Methods: The seasonal autoregressive integrated moving average (ARIMA) and BSTS models were constructed using the series from January 2017 to December 2021, and the prediction accuracy of both models was tested using the series from January 2022 to November 2022. Results: From January 2017 to November 2022, the total number of syphilis cases in Jiangsu Province was 170629, with an average monthly notification cases of 2403. The optimal model was ARIMA (1,0,0) (0,1,1) 12 (AIC = 663.12, AICc = 664.05, and BIC = 670.60). The model coefficients were further tested: AR1 = 0.48 (t = 3.46, P < 0.001), and SMA1 =-0.48 (t =-2.32, P = 0.01). The mean absolute deviation, mean absolute percentage error, root mean square error, and root mean square percentage error from the BSTS model were smaller than those from the ARIMA model. The total number of syphilis cases predicted by the BSTS model from December 2022 to December 2023 in Jiangsu Province was 29902 (95% CI: 16553 ~ 42,401), with a monthly average of 2300 (95% CI: 1273 ~ 3262) cases. Conclusion: Syphilis is a seasonal disease in Jiangsu Province, and its incidence is still at a high level. The BSTS model is superior to the ARIMA model in dynamically predicting the incidence trend of syphilis in Jiangsu Province and has better application value.

Indexed as

ARIMA modelBSTS modelforecastsyphilistrends

Identifiers

PMID39720619
PMCPMC11668328

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