Meteorological factors, population immunity, and COVID-19 incidence A global multi-city analysis
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Authors
Feurer, Denise
Riffe, Tim
Kniffka, Maxi Stella
Acosta, Enrique
Armstrong, Ben
Mistry, Malcolm
Lowe, Rachel
Royé, Dominic
Hashizume, Masahiro
Madaniyazi, Lina
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Abstract
Description
<p>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.</p>
Keywords
COVID-19, Distributed lag nonlinear models, Humidity, Multi-Country Multi-City Collaborative Research Network, Precipitation, Solar radiation, Temperature, Time-series design, SDG 3 - Good Health and Well-being, SDG 11 - Sustainable Cities and Communities