ArticlePloS one2023
A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Prediction, lag and mixture effects of meteorology and pollutants on the incidence of pulmonary tuberculosis in Jining City, China.BMC public health · 2026Article
- Epidemic trend and spatial-temporal analysis of pulmonary tuberculosis in Hotan prefecture, xinjiang, china, 2015-2021.Scientific reports · 2025Article
- Forecasting tuberculosis epidemics using an autoregressive fractionally integrated moving average model: a 17-year time series analysis.Journal of global health · 2025Article
- The association between pulmonary tuberculosis recurrence and exposure to fine particulate matter and residential greenness: A population-based retrospective study.One health (Amsterdam, Netherlands) · 2025Article
- A hybrid machine learning model for pulmonary tuberculosis forecasting of Chongqing with adjacent-region data.PloS one · 2025Article
- Epidemiological characteristics of respiratory diseases in emergency department patients from different ethnic groups in the Atushi region, Xinjiang.Frontiers in medicine · 2025Article
- Dynamic variations in and prediction of COVID-19 with omicron in the four first-tier cities of mainland China, Hong Kong, and Singapore.Frontiers in public health · 2023Article
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Authors and funding
7 authors.
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Abstract
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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