The role of environmental factors in the COVID-19 pandemic: research from the MCC Network

Abstract

Background and Aim. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread across the globe, traversing diverse climatic and environmental conditions. From the early phase of the pandemic, there has been speculation that weather conditions could modulate SARS-CoV-2 transmission patterns. Methods. In this talk, I will present the current evidence and methodological challenges in evaluating potential drivers of COVID-19 seasonality. I will also present the results of two global studies based on an extensive city-level dataset, collected by the Multi-Country Multi-City MCC Collaborative Research Network, where we studied the relationship between weather conditions and COVID-19 spread using ecological and time-series designs. Finally, I will discuss planned future studies based on data collected until March 2022. Results. We collected data from 455 cities across 20 countries around the globe over an observation period ranging from 3 February to 31 October 2020. For each location, daily COVID-19 cases were linked with meteorological (mean temperature, relative and absolute humidity and UV radiation) variables derived from the Copernicus ERA5 dataset, and with the Oxford Governmental Stringency Index to account for the effect of lockdown measures. These data were analysed using ecological designs (spatial and time-series approaches) giving evidence of effects of mean temperature and absolute humidity on COVID-19 transmission. However, these studies underline regional heterogeneity of weather-related effects on COVID-19 transmission and the dominant role of non-pharmaceutical interventions. We are extending the data collection until March 2022 to investigate the interdependent role of seasonality, meteorological factors, environmental stressors (air pollution), non-pharmaceutical interventions and vaccination. Conclusion. This research activity is an example of the flexibility of the MCC Network in adapting and using its collaborative platform and data collection to address urgent and challenging research questions. Key words: Temperature, Humidity, UV Radiation, COVID-19, DLNM, Global Analysis, Meta-Regression