The Lusic Lab in collaboration with Genewerk GmbH provided an insight into spatial and temporal trends of SARS-CoV‑2 infection outbreak linked to ambient air pollution, and specifically particulate matter and ozone. Daily pollution parameters and positive SARS-CoV‑2 cases from Italy, France, Spain and Germany were used to build a binary classifier based on artificial neural network. The model shows that particulate matter is positively correlated with SARS-CoV‑2 outbreak severity, while ozone is protective against the virus at higher particulate concentrations. The findings offer a base for generating a tool to predict the future pace of coronavirus outbreaks by monitoring atmospheric parameters that are continuously recorded worldwide. Their implication may be particularly important for the post COVID-19 era, as strong global economical and industrial re-start is expected.
Link to full article: https://www.mdpi.com/1999–4915/12/6/588