The simplified diffusion and agent-based modeling approaches employed in this study present several limitations that could impact the accuracy and applicability of the findings:
Assumptions of Homogeneity: The simplified diffusion model assumes a uniform distribution of droplets and does not account for variations in droplet size, which can affect their behavior in the air. This limitation can be addressed by incorporating a more complex model that differentiates between various droplet sizes and their respective settling velocities.
Static Environmental Conditions: The models do not account for dynamic changes in environmental conditions, such as varying ventilation rates or changes in occupancy. To overcome this, more detailed simulations that incorporate time-varying parameters and real-time data from environmental sensors could be developed.
Simplified Agent Interactions: The agent-based model simplifies interactions between agents, potentially overlooking complex social behaviors and movement patterns that can influence infection transmission. Enhancing the model to include more realistic movement patterns and social interactions, such as clustering or avoidance behaviors, could provide a more accurate representation of infection dynamics.
Lack of Experimental Validation: While the models are validated through simulations, there is a need for empirical validation in real-world settings. Conducting controlled experiments in industrial environments to measure droplet dispersion and infection rates would provide critical data to refine the models.
Computational Complexity: More detailed simulations, such as those using CFD, can be computationally intensive and may require significant resources. Developing hybrid models that combine simplified analytical approaches with more complex simulations could balance computational efficiency with accuracy.
By addressing these limitations through more detailed simulations and experimental validation, the models can be improved to provide more reliable predictions of infection risks in industrial settings.