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| Content Provider | frontiers |
|---|---|
| Author | Zhang, Yu Wang, Shijun Feng, Zhangxian Song, Yang |
| Description | BackgroundInfluenza is a serious public health problem, and its prevalence and spread show significant spatiotemporal characteristics. Previous studies have found that air pollutants are linked to an increased risk of influenza. However, the mechanism of influence and the degree of their association have not been determined. This study aimed to determine the influence of the air environment on the spatiotemporal distribution of influenza.MethodsThe kernel density estimation and Getis-Ord Gi* statistic were used to analyze the spatial distribution of the influenza incidence and air pollutants in China. A simple analysis of the correlation between influenza and air pollutants was performed using Spearman's correlation coefficients. A linear regression analysis was performed to examine changes in the influenza incidence in response to air pollutants. The sensitivity of the influenza incidence to changes in air pollutants was evaluated by performing a gray correlation analysis. Lastly, the entropy weight method was used to calculate the weight coefficient of each method and thus the comprehensive sensitivity of influenza incidence to six pollution elements.ResultsThe results of the sensitivity analysis using Spearman's correlation coefficients showed the following ranking of the contributions of the air pollutants to the influenza incidence in descending order: SO2 >NO2 >CO> PM2.5 >O3 >PM10. The sensitivity results obtained from the linear regression analysis revealed the foll... |
| Abstract | BACKGROUND: Influenza is a serious public health problem, and its prevalence and spread show significant spatiotemporal characteristics. Previous studies have found that air pollutants are linked to an increased risk of influenza. However, the mechanism of influence and the degree of their association have not been determined. This study aimed to determine the influence of the air environment on the spatiotemporal distribution of influenza. METHODS: The kernel density estimation and Getis-Ord Gi* statistic were used to analyze the spatial distribution of the influenza incidence and air pollutants in China. A simple analysis of the correlation between influenza and air pollutants was performed using Spearman’s correlation coefficients. A linear regression analysis was performed to examine changes in the influenza incidence in response to air pollutants. The sensitivity of the influenza incidence to changes in air pollutants was evaluated by performing a gray correlation analysis. Lastly, the entropy weight method was used to calculate the weight coefficient of each method and thus the comprehensive sensitivity of influenza incidence to six pollution elements. RESULTS: The results of the sensitivity analysis using Spearman’s correlation coefficients showed the following ranking of the contributions of the air pollutants to the influenza incidence in descending order: SO2>NO2>CO> PM2.5>O3>PM10. The sensitivity results obtained from the linear regression analysis revealed the following ranking: CO>NO2>SO2>O3>PM2.5>PM10. Lastly, the sensitivity results obtained from the gray correlation analysis showed the following ranking: NO2>CO>PM10>PM2.5>SO2>O3. According to the sensitivity score, the study area can be divided into hypersensitive, medium-sensitive, and low-sensitive areas. CONCLUSION: The influenza incidence showed a strong spatial correlation and associated sensitivity to changes in concentrations of air pollutants. Hypersensitive areas were mainly located in the southeastern part of northeastern China, the coastal areas of the Yellow River Basin, the Beijing-Tianjin-Hebei region and surrounding areas, and the Yangtze River Delta. The influenza incidence was most sensitive to CO, NO2, and SO2, with the occurrence of influenza being most likely in areas with elevated concentrations of these three pollutants. Therefore, the formulation of targeted influenza prevention and control strategies tailored for hypersensitive, medium-sensitive, low-sensitive, and insensitive areas are urgently needed. |
| ISSN | 22962565 |
| DOI | 10.3389/fpubh.2022.1071229 |
| Volume Number | 10 |
| Journal | Frontiers in Public Health |
| Language | English |
| Publisher Date | 2022-12-02 |
| Access Restriction | Open |
| Subject Keyword | Influenza incidence Air Pollutants China Sensitivity Sensitive division |
| Content Type | Text |
| Resource Type | Article |
| Subject | Public Health, Environmental and Occupational Health |
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