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Sci Rep ; 12(1): 726, 2022 01 26.
Article in English | MEDLINE | ID: covidwho-1655612


Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.

Air Pollution/analysis , Air Pollutants/analysis , Bayes Theorem , COVID-19/epidemiology , COVID-19/virology , Environmental Monitoring , Europe/epidemiology , Humans , Nitrogen Oxides/analysis , Pandemics , Particulate Matter/analysis , Quarantine , SARS-CoV-2/isolation & purification
Nat Commun ; 12(1): 5968, 2021 10 13.
Article in English | MEDLINE | ID: covidwho-1467102


There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission.

COVID-19/transmission , Meteorological Concepts , SARS-CoV-2/pathogenicity , Basic Reproduction Number , COVID-19/epidemiology , Cities , Cross-Sectional Studies , Humans , Meta-Analysis as Topic , Pandemics , Regression Analysis , Seasons , Temperature , Weather