CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES >
Trend prediction on the detection rate of newly discovered echinococcosis patients in Sichuan Province based on ARMA and GM (1,1) models
Received date: 2021-01-13
Revised date: 2021-03-12
Online published: 2021-04-30
Supported by
Sichuan Science and Technology Program(2018SZ0116)
Objective To explore a model suitable for predicting the detection rate of newly discovered echinococcosis patients in Sichuan Province, and to provide scientific basis for formulating prevention and control strategies for echinococcosis. Methods The detection rate data of newly discovered echinococcosis patients in Sichuan Province from 2007 to 2020 were collected, and ARMA and GM (1,1) models were established respectively to predict the detection rate from 2021 to 2023. Meanwhile, the fitting and prediction effects of the two models were compared using the coefficient of determination, mean absolute error and mean-square error. Results The ARMA model was established, and the errors between fitting and actual values of detection rate in 2017—2020 were 12.44, 26.04 and 33.30, respectively. The predicted detection rates in 2021, 2022 and 2023 using this model were 50.14/100 000, 50.04/100 000 and 49.99/100 000, respectively. Uing the GM(1,1) model, the errors between fitting and actual values of detection rate in 2017—2020 were 6.51, 2.94 and -1.20, respectively, and the predicted detection rates in 2021, 2022 and 2023 were 20.55/100 000, 17.65/100 000 and 15.77/100 000, respectively. Evaluation of fitting effects showed that the GM(1,1) had better prediction performance than the ARMA model. Conclusion The GM (1,1) model can predict the detection rate of newly discovered echinococcosis patients in Sichuan Province. Although the predicted detection rate show a trend of decrease, new cases are continuously being detected. Therefore, measures should be taken to strength prevention and control of echinococcosis and consolidate the achievements of disease control.
Key words： Sichuan Province; Echinococcosis; ARMA model; GM (1,1) model; Prediction
Wei HE , Qi WANG , Wen-jie YU , Yan HUANG , Guang-jia ZHANG , Sha LIAO , Liu YANG , Ren-xin YAO , Rui-rui LI , Yang LIU , Bo ZHONG , Qian WANG . Trend prediction on the detection rate of newly discovered echinococcosis patients in Sichuan Province based on ARMA and GM (1,1) models[J]. CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES, 2021 , 39(2) : 185 -190 . DOI: 10.12140/j.issn.1000-7423.2021.02.010
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