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Effects of temperature, humidity, and air saturation state on the transmission risk prediction of COVID-19 in typical scenarios
Summary
Researchers introduced a dynamic virus deposition ratio concept to model how temperature, humidity, and air saturation state influence respiratory particle size and viral deposition in the airway, incorporating it into a modified non-steady-state Wells-Riley model for COVID-19 infection risk prediction. The model estimated transmission risk across typical indoor scenarios under varying ambient environmental conditions.
Abstract Environmental parameters have a significant impact on the spread of respiratory viral diseases. Temperature and relative humidity are correlated with viral inactivation in the air, whereas supersaturated air can promote viral deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in particle size and viral deposition under varying ambient environments. Moreover, a non-steady-state modified Wells-Riley model is established to predict the infection risk of shared air space under varying environmental parameters, including temperature, relative humidity, and air saturation state. The quanta emission rate of an asymptomatic infector during different respiratory activities (breath, voice, and cough) are explored, and the differences in the infection risk under saturated and unsaturated air conditions are also compared. Finally, six typical exposure scenarios from daily life are also explored, highlighting scenarios of higher risk. The results show that the highest infection risk (Rmax=5.2%) and the longest risk duration (Tterminal=6.8h) are both reached in cold and damp conditions. This study quantitatively reflects how environmental parameters are linked to viral inactivation and particle deposition, affecting transmission risk.
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