Abstract
The key to strengthening the inherent safety of large public spaces and implementing precise preventive measures lies in clarifying the transmission risks of respiratory infectious diseases based on multiple factors. This work innovatively improves a pathogen inhalation infection risk prediction model and attempts to apply it to a Fangcang Shelter Hospital to investigate the effect of pathogen release location on risk distribution and the role of airflow distribution in risk control mechanisms. The model used in the study improved in resolution and accuracy, shedding light on the airflow distribution mechanisms involved in pathogen transport and risk control, thus providing a quantitatively realistic landscape of the spread of respiratory infectious diseases in large indoor environments. Predictions reveal a significant unevenness in the spatial distribution of infection probabilities within the multi-patient shelter unit, which is further exacerbated by different release locations, and that extreme infection risks can reach 4 to 14 times the average. Additionally, the study noted that the infection probability in the medical staff area due to the long-distance transmission of contaminants can reach as high as 1.72 % and that patients from ward 6# could potentially infect a healthcare worker every four days.
Published Version
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