## 5 Conclusions  
The model developed in this study integrates a highly detailed 3D geometrical configuration of a room obtained using a LiDAR scanning device with a spatio-temporal pandemic spread model that is constructed from an _SEIR_-based epidemiological model with a CFD-based airflow model. The proposed model allows us to examine the influence of different room types on an airborne pandemic spread. In addition, the influence of mask-wearing and air ventilation at the room-level with relatively small populations and time duration on pathogen spread is analyzed.  
The proposed model is implemented for the COVID-19 outbreak. These spatio-temporal interactions allow one to explore the reciprocal effects of both spatial and temporal PIP on the spread of the pandemic during different social activities. An example is the effect of mask-wearing in a movie theater, as shown in Figure 5e. The inclusion of these interactions provides a highly detailed representation of how airborne pathogens move from one host (individual) to another. Thus, these improve the accuracy of the model's forecasts and allow for multidimensional analysis of the impact of PIPs.  
Our results indicate that policy makers need to consider the unique interactions of individuals in enclosed spaces population when considering optimal PIPs which involve different policies for different spaces such as restaurants and classrooms. We found that the population distribution in a space influences AAV primarily through the amount of breathing zone infections. Thus, given mask-wearing and AAV configurations, one can further control pathogen spread by controlling breathing zone infection using social distancing and other methods.  
The proposed model assumes that individuals are not moving, the AAV is affecting all air in the room at once, and the temperature is constant. In future work, we can relax these assumptions in order to obtain a more realistic representation of the airborne spread dynamics. Moreover, an investigation of a multi-strain and multi-mutation pandemic at the room-level is also a promising research direction, following recent studies on larger scales [29; 101; 102; 103; 104; 105].  
**Author Contributions:** Conceptualization, T.L. and A.A.; methodology, T.L.; software, T.L.; validation, T.L. and A.A.; formal analysis, T.L. and A.A.; investigation, T.L. and A.A.; resources, A.A.; data curation, A.A.; writing--original draft preparation, T.L.; writing--review and editing, A.A.; visualization, T.L.; supervision, T.L.; project administration, T.L.; funding acquisition, T.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The room's raw topological data is not available due to security reasons, according to Israeli law. In addition, the data used are provided in the manuscript with the relevant sources.  
**Acknowledgments:** The authors wish to thank [PERSON] for her statistical consulting and [PERSON] for the thought-provoking discussions.  
**Conflicts of Interest:** The authors declare no conflict of interest.