tetano
Editor, Senior Moderator
Front Public Health
. 2025 Apr 14:13:1555430.
doi: 10.3389/fpubh.2025.1555430. eCollection 2025. Exploration of the impact of air pollutants on the influenza epidemic after the emergence of COVID-19: based on Jiangsu Province, China (2020-2024)
Chengxi Zheng[SUP] #[/SUP][SUP] 1 [/SUP], Xin Jiang[SUP] #[/SUP][SUP] 1 [/SUP], Yi Yin[SUP] #[/SUP][SUP] 1 [/SUP], Qigang Dai[SUP] 2 [/SUP], Shuhan Tang[SUP] 1 [/SUP], Jianli Hu[SUP] 2 [/SUP], Changjun Bao[SUP] 2 [/SUP], Haitao Yang[SUP] 2 [/SUP], Zhihang Peng[SUP] 1 3 4 [/SUP]
Affiliations
Background: Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic altered influenza transmission patterns, yet the age-specific effects of air pollutants on influenza dynamics remain unclear.
Methods: Utilizing influenza surveillance data of Jiangsu Province from 2020 to 2024, we integrated generalized additive quasi-Poisson regression model and distributed lag non-linear models (DLNM) to quantify lagged effects and exposure-response relationships between air pollutants (NO[SUB]2[/SUB], SO[SUB]2[/SUB], PM[SUB]2.5[/SUB]) and influenza risk across young, middle-aged, and older adult groups. Meteorological factors, including temperature and humidity, as well as the implementation stages of NPIs, were controlled in the model to isolate the impact of pollutants on influenza transmission.
Results: The NO[SUB]2[/SUB] and SO[SUB]2[/SUB] both showed significant positive effects in all age groups. The effect of NO[SUB]2[/SUB] is most significant in the young group (RR = 5.02, 95% CI: 4.69-5.37), while SO[SUB]2[/SUB] exhibited the most pronounced effects in middle-aged and older adult groups (RR = 4.22, 95% CI: 3.36-5.30; RR = 8.31, 95% CI: 5.77-11.96, respectively). PM[SUB]2.5[/SUB] elevated risks in young (RR = 1.99, 95% CI: 1.87-2.12) and older adult (RR = 1.45, 95% CI: 1.07-1.94) groups. Interactions between meteorological factors (temperature, humidity) and pollutants were statistically insignificant.
Conclusions: Air pollutant impacts on influenza transmission are age-dependent: NO[SUB]2[/SUB] dominates in younger populations, whereas SO[SUB]2[/SUB] disproportionately affects older adults. These findings highlight age-related vulnerability to air pollution and the need for targeted public health strategies for different population subgroups.
Keywords: COVID-19; DLNM; age-specific transmissibility; air pollutants; influenza.
. 2025 Apr 14:13:1555430.
doi: 10.3389/fpubh.2025.1555430. eCollection 2025. Exploration of the impact of air pollutants on the influenza epidemic after the emergence of COVID-19: based on Jiangsu Province, China (2020-2024)
Chengxi Zheng[SUP] #[/SUP][SUP] 1 [/SUP], Xin Jiang[SUP] #[/SUP][SUP] 1 [/SUP], Yi Yin[SUP] #[/SUP][SUP] 1 [/SUP], Qigang Dai[SUP] 2 [/SUP], Shuhan Tang[SUP] 1 [/SUP], Jianli Hu[SUP] 2 [/SUP], Changjun Bao[SUP] 2 [/SUP], Haitao Yang[SUP] 2 [/SUP], Zhihang Peng[SUP] 1 3 4 [/SUP]
Affiliations
- PMID: 40297024
- PMCID: PMC12034646
- DOI: 10.3389/fpubh.2025.1555430
Background: Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic altered influenza transmission patterns, yet the age-specific effects of air pollutants on influenza dynamics remain unclear.
Methods: Utilizing influenza surveillance data of Jiangsu Province from 2020 to 2024, we integrated generalized additive quasi-Poisson regression model and distributed lag non-linear models (DLNM) to quantify lagged effects and exposure-response relationships between air pollutants (NO[SUB]2[/SUB], SO[SUB]2[/SUB], PM[SUB]2.5[/SUB]) and influenza risk across young, middle-aged, and older adult groups. Meteorological factors, including temperature and humidity, as well as the implementation stages of NPIs, were controlled in the model to isolate the impact of pollutants on influenza transmission.
Results: The NO[SUB]2[/SUB] and SO[SUB]2[/SUB] both showed significant positive effects in all age groups. The effect of NO[SUB]2[/SUB] is most significant in the young group (RR = 5.02, 95% CI: 4.69-5.37), while SO[SUB]2[/SUB] exhibited the most pronounced effects in middle-aged and older adult groups (RR = 4.22, 95% CI: 3.36-5.30; RR = 8.31, 95% CI: 5.77-11.96, respectively). PM[SUB]2.5[/SUB] elevated risks in young (RR = 1.99, 95% CI: 1.87-2.12) and older adult (RR = 1.45, 95% CI: 1.07-1.94) groups. Interactions between meteorological factors (temperature, humidity) and pollutants were statistically insignificant.
Conclusions: Air pollutant impacts on influenza transmission are age-dependent: NO[SUB]2[/SUB] dominates in younger populations, whereas SO[SUB]2[/SUB] disproportionately affects older adults. These findings highlight age-related vulnerability to air pollution and the need for targeted public health strategies for different population subgroups.
Keywords: COVID-19; DLNM; age-specific transmissibility; air pollutants; influenza.