A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang.
A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang.
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DOI：
10.1371/journal.pone.0277314
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
本文分别构建了ARIMA、ARIMAX和RNN模型，对2014年1月至2018年12月新疆乌鲁木齐市大气污染物（如PM2. 5、PM10、CO、O3、NO2和SO2）对肺结核病例数是否存在影响进行了研究。此外，采用一种新的综合评价指标DISO对3种模型的性能进行比较，结果表明ARIMAX（1，1，2）×（0，1，1）12 + PM2. 5（lag = 12）模型为最优模型，并将其应用于乌鲁木齐市2019年1 - 12月肺结核病例数的预测。预测结果与实际肺结核病例数吻合较好，肺结核病例数明显下降，说明乌鲁木齐市近年来的环境保护和全民健康检查政策是行之有效的。
In this paper, we separately constructed ARIMA, ARIMAX, and RNN models to determine whether there exists an impact of the air pollutants (such as PM2.5, PM10, CO, O3, NO2, and SO2) on the number of pulmonary tuberculosis cases from January 2014 to December 2018 in Urumqi, Xinjiang. In addition, by using a new comprehensive evaluation index DISO to compare the performance of three models, it was demonstrated that ARIMAX (1,1,2) × (0,1,1)12 + PM2.5 (lag = 12) model was the optimal one, which was applied to predict the number of pulmonary tuberculosis cases in Urumqi from January 2019 to December 2019. The predicting results were in good agreement with the actual pulmonary tuberculosis cases and shown that pulmonary tuberculosis cases obviously declined, which indicated that the policies of environmental protection and universal health checkups in Urumqi have been very effective in recent years.
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影响因子：
3.9
作者：
Li, Xiaoming;Xu, Xianghui;Yuan, Juxiang
通讯作者：
Yuan, Juxiang
影响因子：
4.6
作者：
Kayama K;Kanno M;Chisaki N;Tanaka M;Yao R;Hanazono K;Camer GA;Endoh D
通讯作者：
Endoh D
影响因子：
3.7
作者：
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通讯作者：
Zhang, Xingyu
DOI：
10.1016/j.scitotenv.2020.143315
发表时间：
2021-03-20
期刊：
The Science of the total environment
影响因子：
--
作者：
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通讯作者：
Uddin MJ
DOI：
10.3390/ijerph17051522
发表时间：
2020-03-01
影响因子：
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作者：
Huang, Shuqiong;Xiang, Hao;Liu, Suyang
通讯作者：
Liu, Suyang