文献类型：期刊文献

英文题名：A study on the climate-driven spatiotemporal dynamics of influenza in Lanzhou spanning the COVID-19 era

作者：Shi, Hong[1];Zhang, Na[2];Wei, Huan[3];Liang, Haojun[4];Zhang, Hui[3];Zhang, Huimin[3];Wang, Biao[3,4]

第一作者：Shi, Hong

通信作者：Zhang, H[1];Zhang, HM[1];Wang, B[1];Wang, B[2]

机构：[1]Lanzhou Ctr Dis Control & Prevent, Microbiol Lab, Lanzhou, Peoples R China;[2]Gansu Prov Peoples Hosp, Dept Radiotherapy, Lanzhou, Peoples R China;[3]Gansu Prov Ctr Dis Control & Prevent, Lanzhou, Peoples R China;[4]Gansu Univ Chinese Med, Publ Hlth Sch, Lanzhou, Peoples R China

第一机构：Lanzhou Ctr Dis Control & Prevent, Microbiol Lab, Lanzhou, Peoples R China

通信机构：[1]corresponding author), Gansu Prov Ctr Dis Control & Prevent, Lanzhou, Peoples R China;[2]corresponding author), Gansu Univ Chinese Med, Publ Hlth Sch, Lanzhou, Peoples R China.|[10735]甘肃中医药大学;

年份：2026

卷号：16

外文期刊名：FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY

收录：;Scopus(收录号：2-s2.0-105032132187);WOS:【SCI-EXPANDED(收录号:WOS:001708735100001)】；

基金：The author(s) declared that financial support was received for this work and/or its publication. This study was supported by the Gansu Provincial Disease Prevention and Control Research Project (No.: GSJKKY2025-44).

语种：英文

外文关键词：COVID-19 pandemic; influenza; Lanzhou China; meteorological factors; spatiotemporal evolution

摘要：Objective The COVID-19 pandemic has profoundly altered global influenza circulation. This study aimed to examine how meteorological factors influenced influenza transmission in Lanzhou, China, across three distinct phases: before, during, and after the COVID-19 pandemic.Methods We collected weekly influenza surveillance data and corresponding meteorological indicators for Lanzhou from January 2014 to December 2024. An explainable machine-learning framework integrating XGBoost with Shapley Additive exPlanation (SHAP) values was used to quantify the dynamic impact of environmental factors on influenza virus positivity rates.Results From 2014 to 2019, influenza circulation in Lanzhou followed typical northern hemisphere seasonality, with annual winter-spring peaks usually dominated by a single subtype. From 2020 to 2024, however, influenza activity displayed a clear "disruption-to-reconstruction" trajectory. During the COVID-19 pandemic (2020-2022), stringent non-pharmaceutical interventions (NPIs) caused influenza positivity rates and case numbers to collapse, with seasonal peaks nearly disappearing. In the post-pandemic period (2023-2024), influenza epidemics reemerged, but the environmental drivers of transmission-particularly for the dominant Influenza A/H3N2 subtype-shifted substantially. SHAP analyses and relative-contribution assessments consistently showed that environmental influences were strongly masked by NPIs during the pandemic, resulting in markedly reduced explanatory power. After NPIs were lifted, preliminary observation environmental effects resurfaced but in a reshaped pattern: temperature became the predominant driver, with its contribution increasing to nearly 40%, while the influence of humidity, sunshine, and other factors weakened. Although the characteristic winter peak persisted before and after the pandemic, the previously complex, multifactorial environmental model simplified into a more temperature-centric structure in the post-pandemic era.Conclusion This study demonstrates that COVID-19 not only temporarily interrupted influenza transmission but also altered the long-term ecological drivers of influenza. Post-pandemic influenza epidemics are entering a new phase, now dominated by a simplified temperature-centered environmental model, suggesting that the climate-influenza relationship has changed after probably major societal intervention. Thus, in Lanzhou and similar climates, the effectiveness of early warning systems based on historical static models requires reassessment and dynamic recalibration. Future influenza surveillance and forecasting will require more flexible frameworks that integrate multi-source data-environmental factors, viral evolution, population immunity, and social behavior-to better address the evolving infectious disease ecosystems.