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Zechariah Lau

Publications and source records attributed to Zechariah Lau.

2 recordsLinked to original sources

The effect of local ventilation on a spatiotemporal model of airborne disease transmission in indoor spaces

We incorporate local ventilation effects into a spatially dependent generalisation of the Wells--Riley model for airborne disease transmission. Aerosol production and removal through ventilation, biological deactivation, and gravitational settling as well as transport around a recirculating air-conditioning flow and turbulent mixing are modelled using an advection--diffusion--reaction equation. The local ventilation model, motivated by air purifiers, is compared with the global ventilation model for a weak purifier (CADR = 140 m$^3$h$^{-1}$) and a strong purifier (CADR = 1,000 m$^3$h$^{-1}$). We find that, as expected, increasing the distance of the infectious person from the purifier reduces the aerosol concentration. Moreover, the concentration is generally lowest when the infectious person is upstream of the purifier, located in regions where the airflow streamlines are directed into the purifier inlet. For these infectious source locations, the global ventilation model significantly overestimates the concentration throughout the room. For infectious sources outside of these regions, there is generally good agreement between the models, particularly for the weak purifier. We also studied, for fixed distance from the purifier, how the infection risk to a susceptible person varies as the infectious person changes location. The infection risk is greatest when the susceptible person is directly downstream of the infectious person. There is better agreement between local and global ventilation models for the weak purifier than the strong purifier.

q-bio.QM

Predicting the Spatially Varying Infection Risk in Indoor Spaces Using an Efficient Airborne Transmission Model

We develop a spatially dependent generalisation to the Wells-Riley model and its extensions applied to COVID-19, that determines the infection risk due to airborne transmission of viruses. We assume that the concentration of infectious particles is governed by an advection-diffusion-reaction equation with the particles advected by airflow, diffused due to turbulence, emitted by infected people and removed due to the room ventilation, inactivation of the virus and gravitational settling. We consider one asymptomatic or presymptomatic infectious person who breathes or talks, with or without a mask and model a quasi-3D setup that incorporates a recirculating air-conditioning flow. A semi-analytic solution is available and this enables fast simulations. We quantify the effect of ventilation and particle emission rate on the particle concentration, infection risk and the `time to probable infection' (TTPI). Good agreement with CFD models is achieved. Furthermore, we derive power laws that quantify the effect of ventilation, emission rate and infectiousness of the virus on the TTPI. The model can be easily updated to take into account modified parameter values. This work paves the way for establishing `safe occupancy times' at any location and has direct applicability in mitigating the spread of the COVID-19 pandemic.

q-bio.QM