The research, led by the Institut de Ciències del Mar (ICM-CSIC) in collaboration with the University of Girona and the Germans Trias i Pujol Hospital, identifies atmospheric pressure and relative humidity as key pandemic risk indicators.
An international research team, led by the Institut de Ciències del Mar (ICM-CSIC) in collaboration with the University of Girona and the Germans Trias i Pujol Hospital, has identified how environmental variables such as atmospheric pressure and relative humidity significantly influence the spread of SARS-CoV-2 (COVID-19). The findings, recently published in Frontiers in Public Health, could prove instrumental in forecasting outbreaks of the disease under conditions of restricted mobility and moderate social distancing.
The study employed epidemiological data collected via PCR testing between September 2020 and February 2021. The team then examined its correlation with meteorological variables recorded by a network of 187 automatic stations across Catalonia. Using linear regression models, they assessed the infection rate against nine atmospheric variables. Results revealed that atmospheric pressure and relative humidity are the most critical factors for predicting outbreaks.
Key Findings
The research demonstrated that low atmospheric pressure, common in early autumn, was associated with a significant increase in infections approximately seven days later. Similarly, low relative humidity was linked to a rise in cases roughly three days after the onset of these conditions. These findings suggest that declining atmospheric pressure and relative humidity often precede spikes in COVID-19 incidence, reinforcing the use of these variables as early pandemic risk indicators.
According to the researchers, the predictive model performed consistently well for both atmospheric pressure and relative humidity during the second and third waves of COVID-19, the periods used for model calibration. During these waves, the model explained between 14% and 45% of infection rate variability across the eight health regions analysed.
The model was further validated with data from Catalonia’s third pandemic wave (November 2020 to February 2021). Despite the inherent challenges of daily infection reporting and fluctuating social restrictions, it showed strong predictive accuracy, explaining between 11% and 22% of observed variability. Importantly, the model identified infection patterns linked to atmospheric changes, influencing both outdoor viruses spread and the conditions facilitating transmission during indoor events.
Implications for Public Health
“Our work demonstrates that climatic factors have a measurable impact on the spread of SARS-CoV-2, particularly in contexts where mobility restrictions are limited,” explains Josep L. Pelegrí, a researcher at ICM-CSIC. “This knowledge could help develop predictive tools and guide preventive measures ahead of future pandemic waves.”
Ignasi Vallès adds, “These findings highlight the importance of incorporating climate influences into epidemiological models. Understanding how environmental factors affect virus transmission enables us to better anticipate and tailor mitigation strategies.”
Jesús Planella emphasises, “The interdisciplinary approach we’ve applied—blending climate science, epidemiology, and data analysis—not only enhances our understanding of the current pandemic but also paves the way for addressing future health challenges related to climate change.”
The team underscores the importance of considering the combined effects of atmospheric changes on infection susceptibility and human behaviour. Specifically, they note that adverse weather conditions, such as low pressure and humidity, may increase interactions in indoor spaces, where the virus is more likely to thrive.