Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115937
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dc.contributorDepartment of Applied Mathematics-
dc.creatorWang, X-
dc.creatorHu, J-
dc.creatorWang, Z-
dc.creatorCai, Y-
dc.creatorHe, D-
dc.date.accessioned2025-11-18T06:48:14Z-
dc.date.available2025-11-18T06:48:14Z-
dc.identifier.issn2468-2152-
dc.identifier.urihttp://hdl.handle.net/10397/115937-
dc.language.isoenen_US
dc.publisherKeAi Publishing Communications Ltd.en_US
dc.rights© 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Wang, X., Hu, J., Wang, Z., Cai, Y., & He, D. (2025). Interactive effects of meteorological factors and ambient air pollutants on influenza incidences 2019–2022 in Huaian, China. Infectious Disease Modelling, 10(4), 1384–1397 is available at https://doi.org/10.1016/j.idm.2025.07.010.en_US
dc.subjectAmbient air pollutantsen_US
dc.subjectInfluenzaen_US
dc.subjectInteractive effectsen_US
dc.subjectMeteorological factorsen_US
dc.titleInteractive effects of meteorological factors and ambient air pollutants on influenza incidences 2019-2022 in Huaian, Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1384-
dc.identifier.epage1397-
dc.identifier.volume10-
dc.identifier.issue4-
dc.identifier.doi10.1016/j.idm.2025.07.010-
dcterms.abstractBackground: Influenza is a global public health and economic burden. Its seasonality patterns differ considerably between geographic regions, but the factors underlying these differences are not well characterized.-
dcterms.abstractMethods: The data on influenza were obtained from 2019 to 2022 in Huaian. A descriptive study was used to describe the epidemiological characteristics.The DLNM(distributed lag nonlinear model) model was established to further analyze the relationship between influenza cases, meteorological factors and pollutants. In addition, the attribution risk analysis and the interaction analysis further explored the interaction between the attributable risk and meteorological factors of influenza in terms of meteorological factors.-
dcterms.abstractResults: A total of 9205 cases of influenza were reported in Huaian City from 2019 to 2022, Jiangsu province, of which 4938 cases were males and 4267 cases were females.The DLNM results showed an inverted U-shaped relationship between PM2.5(Fine Particulate Matter) and temperature and influenza.The low concentration of PM2.5 and O3(Ozone) showed decreased risks, and the maximum effect values appeared on the 8th day (RR(Relative Ris) = 0.35,95 %CI(Confidence Interval): 0.25–0.49) and the 2nd day (RR = 0.63,95 %CI: 0.52–0.77). At the high concentration, the cumulative RR values of PM2.5 and O3 reached their maximum on the 8th day (RR = 1.93,95 %CI: 1.47–2.54) and the 9th day (RR = 2.58,95 %CI: 1.63–4.09). The attribution analysis based on DLNM showed that the AF(attributable fraction) value of influenza attributable to the high concentration of PM2.5 exposure was 15.90 %, equivalent to 1456 cases. AF of the high concentration of O3 was 8.12 % (743 cases). The AF of low temperature effect was 30.91 % (2830 cases). The interaction analysis showed that high temperature reduced the influence of PM2.5 on the onset of influenza, showing an antagonistic effect (RR = 0.31, 95 %CI: 0.15–0.65), IRR(interaction relative risk) and RERI(interaction relative risk) were 0.17 (95 %CI: 0.08–0.37) and −1.62 (95 %CI: 2.65∼-0.68), respectively.-
dcterms.abstractConclusion: The results show that low temperature significantly increases the risk of influenza. At the low concentration of PM2.5, the risk of influenza increases with increasing concentration but decreases at the high concentrations. At the high concentration of O3, the risk of influenza increases rapidly. 15.90 % of influenza cases may be attributed to the high concentration of PM2.5, equivalent to 1456 cases; temperature-induced cases mainly come from the low-temperature effect, with an AF value of 30.91 %, equivalent to 2830 cases. In addition, high temperature can effectively mitigate the impact of PM2.5 on influenza incidence, and outdoor exposure time should be minimized in low temperature and high PM2.5 weather.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInfectious disease modelling, Dec. 2025, v. 10, no. 4, p. 1384-1397-
dcterms.isPartOfInfectious disease modelling-
dcterms.issued2025-12-
dc.identifier.scopus2-s2.0-105011745254-
dc.identifier.eissn2468-0427-
dc.description.validate202511 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research was supported by the National Natural Science Foundation of China (Grant No. 12071173 and 12171192), the Scientific Research Project of Jiangsu Provincial Health Commission (No. DX202302) and Huaian Key Laboratory for Infectious Diseases Control and Prevention, China (HAP201704).en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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