The predictive effect of ARIMA model for occupational pneumoconiosis in Guangdong Province
10.20001/j.issn.2095-2619.20230406
- VernacularTitle:广东省职业性尘肺病ARIMA模型预测
- Author:
Yuhao HAN
1
;
Xi WU
;
Jinbi PENG
;
Yuhao WANG
;
Ru JING
;
Daoyu YANG
;
Yicen GU
;
Ningbin QUAN
;
Xudong LI
Author Information
1. School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
- Publication Type:Journal Article
- Keywords:
Pneumoconiosis;
ARIMA model;
Time series;
Incidence trend;
Prediction
- From:
China Occupational Medicine
2023;50(2):150-154
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To verify the accuracy of the autoregressive integrated moving average (ARIMA) in predicting the incidence of occupational pneumoconiosis (hereinafter referred as pneumoconiosis) and to predict the incidence of pneumoconiosis in Guangdong Province in the next five years. Methods: A follow-up survey was performed to collect data on pneumoconiosis patients reported in Guangdong Province from 1956 to 2021. Collected data from 1956 to 2016 were used as the training set to build an ARIMA model. Collected data from 2017 to 2021 were used as the prediction set to evaluate the predicting result of the ARIMA model. The ARIMA model was used to predict the incidence of pneumoconiosis in Guangdong Province in next five years. Results: The ARIMA (1,1,2) model was set up after model identification and order estimation. The model was used to predict the prediction set, and its result was good. The ARIMA result and actual values in 2021 were 213 and 210 cases, respectively, with a difference of only three cases. The number of pneumoconiosis cases predicted using the ARIMA model in Guangdong Province from 2022 to 2026 was 214, 204, 202, 194, and 191 cases, respectively, showing a trend of low-level prevalence. Conclusion: The ARIMA model demonstrates high accuracy in predicting pneumoconiosis incidence over a long period of time and with large sample sizes. The forecast results of the ARIMA(1,1,2) model indicate that the incidence of pneumoconiosis in Guangdong Province will be around 200 cases in the next five years, indicating a low-level prevalence.
