Journal
ENVIRONMENTAL RESEARCH
Volume 196, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2021.110977
Keywords
Temperature; Humidity; COVID-19; Distributed lag non-linear model; Meta-analysis
Funding
- Medical Research Council-UK [MR/R013349/1]
- Natural Environment Research Council UK [NE/R009384/1]
- European Union [820655]
- NERC [NE/R009384/1] Funding Source: UKRI
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This study found a nonlinear association between COVID-19 cases and temperature, with increased risk at lower temperatures. Absolute humidity and relative humidity also showed correlations with elevated risk of COVID-19 cases. This suggests that meteorological variables likely play a role in influencing the development of COVID-19 cases in England.
Background: SARS-CoV-2 caused the COVID-19 pandemic in 2020. The virus is likely to show seasonal dynamics in European climates as other respiratory viruses and coronaviruses do. Analysing the association with meteo-rological factors might be helpful to anticipate how cases will develop with changing seasons. Methods: Routinely measured ambient daily mean temperature, absolute humidity, and relative humidity were the explanatory variables of this analysis. Test-positive COVID-19 cases represented the outcome variable. The analysis included 54 English cities. A two-stage meta-regression was conducted. At the first stage, we used a quasi-Poisson generalized linear model including distributed lag non-linear elements. Thereby, we investigate the explanatory variables' non-linear effects as well as the non-linear effects across lags. Results: This study found a non-linear association of COVID-19 cases with temperature. At 11.9 degrees C there was 1.62-times (95%-CI: 1.44; 1.81) the risk of cases compared to the temperature-level with the smallest risk (21.8 degrees C). Absolute humidity exhibited a 1.61-times (95%-CI: 1.41; 1.83) elevated risk at 6.6 g/m(3) compared to the centering at 15.1 g/m(3). When adjusting for temperature RH shows a 1.41-fold increase in risk of COVID-19 incidence (95%-CI: 1.09; 1.81) at 60.7% in respect to 87.6%. Conclusion: The analysis suggests that in England meteorological variables likely influence COVID-19 case development. These results reinforce the importance of non-pharmaceutical interventions (e.g., social distancing and mask use) during all seasons, especially with cold and dry weather conditions.
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