Abstract
To enhance the prevention and control of pandemic respiratory infections, we constructed an infection risk prediction model for pathogen inhalation based on the dose-response relationship with reference to the long-distance transmission chain of the SARS-CoV-2 pathogen, applying it to the Fangcang Shelter Hospital (FSH). The model quantitatively describes key processes of pathogens shedding, airborne transmission, suspension, inhalation by susceptible individuals, and lung deposition, thus improving the resolution and accuracy of the results. This study considered four ventilation rates and quantitatively assessed their impact on inhalation infection risk. Results indicate that the infection risk within the multi-patient shelter unit is unevenly distributed, with the maximum probability (3.66 %) being more than 30 times higher than the minimum probability (0.10 %) at a ventilation rate of 8 ACH. Poor ventilation (6 ACH) significantly increases average infection probability, with a rise of 35.96 % compared to the average probability (1.14 %) at 8 ACH. However, excessive ventilation (12 ACH) led to diminishing returns on ventilation performance. Lastly, we also found that poor ventilation was a sufficient and non-essential condition for higher infection probability. Our findings can be extended to similar large-scale scenarios, offering positive support for the sustainable development of society.
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