Talib Dbouk and Dimitris Drikakis
University of Nicosia, Nicosia, Cyprus
Epidemic models do not account for the effects of climate conditions on the transmission dynamics of viruses. This study presents the vital relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks over a whole year.
Using the data obtained from high-fidelity multi-phase, fluid dynamics simulations, we calculate the concentration rate of Coronavirus particles in contaminated saliva droplets and use it to derive a new Airborne Infection Rate (AIR) index.
Then, combining the simplest form of an epidemiological model, the susceptible–infected–recovered, and the AIR index, we show through data evidence how weather seasonality induces two outbreaks per year, as it is observed with the COVID-19 pandemic worldwide.
This study explains how pandemic outbreaks are associated with temperature, relative humidity, and wind speed changes independently of the particular season. For that reason, we propose that epidemiological models must incorporate climate effects to predict the pandemic curves behavior on a long-term basis.