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Objectives: While COVID-19 continues to challenge the world, meteorological variables are thought to impact COVID-19 transmission. Previous studies showed evidence of negative associations between high temperature and absolute humidity on COVID-19 transmission. Our research aims to fill the knowledge gap on the modifying effect of vaccination rates and strains on the weather-COVID-19 association.
Methods: Our study included COVID-19 data from 439 cities in 22 countries spanning 3 February 2020 - 31 August 2022 and meteorological variables (temperature, relative humidity, absolute humidity, solar radiation, and precipitation). We used a two-stage time-series design to assess the association between meteorological factors and COVID-19 incidence. For the exposure modeling, we used distributed lag nonlinear models with a lag of up to 14 days. Finally, we pooled the estimates using a random effect meta-analytic model and tested vaccination rates and dominant strains as possible effect modifiers.
Results: Our results showed an association between temperature and absolute humidity on COVID-19 transmission. At 5 °C, the relative risk of COVID-19 incidence is 1.22-fold higher compared to a reference level at 17 °C. Correlated with temperature, we observed an inverse association for absolute humidity. We observed a tendency of increased risk on days without precipitation, but no association for relative humidity and solar radiation. No interaction between vaccination rates or strains on the weather-COVID-19 association was observed.
Conclusions: This study strengthens previous evidence of a relationship of temperature and absolute humidity with COVID-19 incidence. Furthermore, no evidence was found that vaccinations and strains significantly modify the relationship between environmental factors and COVID-19 transmission.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11557119 | PMC |
http://dx.doi.org/10.1097/EE9.0000000000000338 | DOI Listing |
Environ Int
August 2025
Spanish Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health-CIBERESP), Madrid, Spain; Department of Statistics and Computational Research. Universitat de València, València, Spain.
Background: The rise in hot nights over recent decades and projections of further increases due to climate change underscores the critical need to understand their impact. This knowledge is essential for shaping public health strategies and guiding adaptation efforts. Despite their significance, research on the implications of hot nights remains limited.
View Article and Find Full Text PDFSensors (Basel)
August 2025
School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China.
Driven by the increasing global population and rapid urbanization, aircraft noise pollution has emerged as a significant environmental challenge, impeding the sustainable development of the aviation industry. Traditional noise prediction methods are limited by incomplete datasets, insufficient spatiotemporal consistency, and poor adaptability to complex meteorological conditions, making it difficult to achieve precise noise management. To address these limitations, this study proposes a novel noise prediction framework based on a hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory-Attention (CNN-BiLSTM-Attention) model.
View Article and Find Full Text PDFTransbound Emerg Dis
August 2025
School of Public Health, Shantou University, Shantou 515041, China.
The COVID-19 pandemic disrupted global influenza transmission. We aimed to elucidate how meteorological and air pollution drivers influenced seasonal influenza A subtypes and B lineage in Southern China pre-, during-, and postpandemic. We analyzed weekly influenza surveillance data from Southern China (2011-2024) and corresponding meteorological data.
View Article and Find Full Text PDFMicrobiol Spectr
August 2025
Viral Gastroenteritis Branch, Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia.
We investigated the infectivity and persistence of SARS-CoV-2 on environmental surfaces by enlisting human beta-coronavirus OC43 as a surrogate. This study evaluated its stability on nonporous stainless steel surfaces under two absolute humidity (AH) conditions when embedded in three mucin concentrations to mimic natural contamination with bodily fluids commonly occurring in healthcare environments.Stainless steel coupons were inoculated with OC43 in artificial saliva with mucin concentrations of 0%, 0.
View Article and Find Full Text PDFJ Dairy Sci
August 2025
University of Georgia, Athens, GA; Institute for Integrative Precision Agriculture, Athens, GA. Electronic address:
The objectives of this study were 2-fold: (1) to investigate the associations among variables derived from automated milking systems (AMS), rumination collars (SCR Heatime), and public weather stations; and (2) to assess how combinations of specific data types (e.g., AMS, SCR, or weather data) influence the predictive accuracy of 7-d average milk yield (DMY7) using different machine learning methods.
View Article and Find Full Text PDF