Abstract
During the Covid-19 pandemic, location of the SARS-CoV-2 infected patients inside the hospital is a major issue to prevent viral cross-transmission. The objective of this study was to evaluate the risk of contamination through aerosol by using a global approach of the multiple environmental parameters to simulate, including seasonal context. A computational fluid dynamic (CFD) simulation based on the Lattice Boltzmann Method approach was used to predict airflow on the entire floor of a private hospital in Paris. The risk of contamination outside the rooms was evaluated by using a water vapor mass fraction tracker. Finally, the air contamination was estimated by a "cough model" producing several punctual emissions of contaminated air from potentially infected patients. In a winter configuration, the simulation showed a well-balanced ventilation on the floor and especially inside the rooms. After cough emissions from COVID-positive rooms, no significant contamination was observed in the circulation area, public waiting space and nurse office. On the contrary, in a summer configuration, the temperature difference due to the impact of the sun radiation between both sides of the building created additional air transport increasing the contamination risk in neighboring rooms and public spaces. Airborne spread was limited to rooms during winter conditions. On the contrary, during summer conditions, market airflow with potentially contaminated air coming from rooms located on the side of the building exposed to solar radiation was evidenced. These observations have implications to locate infected patients inside the building and for the conception of future health care structures.