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Comparing the performance of time series models with or without meteorological factors in predicting incident pulmonary tuberculosis in eastern China 被引量:7

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摘要 Background: Many studies have compared the performance of time series models in predicting pulmonary tuberculosis(PTB),but few have considered the role of meteorological factors in their prediction models.This study aims to explore whether incorporating meteorological factors can improve the performance of time series models in predicting PTB.Methods:: We collected the monthly reported number of PTB cases and records of six meteorological factors in three cities of China from 2005 to 2018.Based on this data,we constructed three time series models,including an autoregressive integrated moving average(ARIMA)model,the ARIMA with exogenous variables(ARIMAX)model,and a recurrent neural network(RNN)model.The ARIMAX and RNN models incorporated meteorological factors,while the ARIMA model did not.The mean absolute percentage error(MAPE)and root mean square error(RMSE)were used to evaluate the performance of the models in predicting PTB cases in 2018.Results: Both the cross-correlation analysis and Spearman rank correlation test showed that PTB cases reported in the study areas were related to meteorological factors.The predictive performance of both the ARIMA and RNN models was improved after incorporating meteorological factors.The MAPEs of the ARIMA,ARIMAX,and RNN models were 12.54%,11.96%,and 12.36%in Xuzhou,15.57%,11.16%,and 14.09%in Nantong,and 9.70%,9.66%,and 12.50%in Wuxi,respectively.The RMSEs of the three models were 36.194,33.956,and 34.785 in Xuzhou,34.073,25.884,and 31.828 in Nantong,and 19.545,19.026,and 26.019 in Wuxi,respectively.Conclusions: Our study revealed a possible link between PTB and meteorological factors.Taking meteorological factors into consideration increased the accuracy of time series models in predicting PTB,and the ARIMAX model was superior to the ARIMA and RNN models in study settings.
出处 《Infectious Diseases of Poverty》 SCIE 2020年第6期106-106,共1页 贫困所致传染病(英文)
基金 This study was funded by the National Natural Science Foundation of China(81973103) National Key R&D Program of China(2017YFC0907000) Qing Lan Project of Jiangsu Province(2019) Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD) The funding agencies had no role in the study design,data collection,analysis,decision to publish,or preparation of the manuscript.
作者简介 Correspondence:Jian-Ming Wang,jmwang@njmu.edu.cn;contributed equally:Zhong-Qi Li;contributed equally:Hong-Qiu Pan;contributed equally:Qiao Liu。
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