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

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.

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Publication Details

Journal
Frontiers in Cellular and Infection Microbiology
Published
2026-02-23
DOI
https://doi.org/10.3389/fcimb.2026.1765305
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Na Zhang, Biao Wang, Huan Wei, Hui Zhang et al.
Frontiers in Cellular and Infection Microbiology
Influenza Virus Research Studies
article

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

Na Zhang, Biao Wang, Huan Wei, Hui Zhang, Huimin Zhang, Haojun Liang, Hong Shi
article en

Abstract

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.

Frontiers in Cellular and Infection MicrobiologyVol. 16
Gansu University of Traditional Chinese Medicine (CN), Gansu Provincial Hospital (CN), Taiwan Centers for Disease Control (TW), Gansu Provincial Center for Disease Control and Prevention (CN)
Openalex Percentile: Top 46%
Influenza Virus Research Studies
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