ArticleBMC public health2025
Nonlinear and potential driving impacts of meteorological and air pollution factors on influenza-like illness in Jinan, China.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors.
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Abstract
backgroundWhile many studies have explored the correlation between environmental factors and influenza, research on their potential causal associations remains limited. Further, the impact of temperature changes between neighboring days (TCN) has not been thoroughly investigated.
methodsInfluenza-like illness (ILI) data, meteorological indicators, and air pollutant levels were collected in Jinan, China (2015-2019). Gradient boosting decision trees (GBDT) were used to identify key environmental variables. The distributed lag nonlinear models (DLNM) and empirical dynamic modeling (EDM) framework were then applied to explore their nonlinear associations with and potential causal effects on influenza infection. Subgroup analysis was also performed by different age groups.
resultsGBDT identified absolute humidity (AH), atmospheric pressure (AP), sulfur dioxide (SO
conclusionThis study demonstrated that both the DLNM and EDM methods consistently revealed the complex and nonlinear effects of specific environmental factors on influenza infection. Specifically, TCN > 5 ℃, AP > 1100 hPa, and SO
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