# How Human Mobility Models Can Help to Deal with COVID-19
## 7 Evaluation of the Infection Risk
### ERQ Evaluation  
The previous experiments only considered the impact of distance and time. Nevertheless, it is essential to evaluate the impact of the environment on the risk. For example, there is strong evidence that indoor airborne transmission of the COVID-19 is much higher than in outdoor spaces, particularly in crowded environments such as a station. Thus, we repeated the previous experiments using Expression (4) for evaluating the spatial and temporal risk exposure. Unlike the previous ERV evaluation, we do not consider explicitly contacts between pairs. Instead, we obtain the risk of each pair of individuals that are in the scenario. The procedure is the following: every second and for each pair individuals in the scenario, we calculate their ERQ, considering an elapsed time of \(t=1\) s. This ERQ, measured in equivalent MEMs, is added to the cells where the individuals were in that moment, in order to obtain a measure of the exposure risk in each cell. Figure 8: Temporal evolution of the exposure risk measured in MEMs for the ERV evaluation. (**a**) Plaza scenario; (**b**) Station scenario. Figure 7: Heat maps of the Exposure Risk Value (ERV) measured in Meaningful Exposure Minutes (MEMs) unit per cell (cell size 1 m\({}^{2}\)). Higher MEMs value imply higher exposure risk. (**a**) RWP; (**b**) SWIM: (**c**) RWPa; (**d**) Plaza; (**e**) Station. Regarding the quality of the medium (\(Qm\)), since the three synthetic scenarios do not correspond to a real scenario, we set a value of \(Q_{m}=0.5\) (we cannot use Table 3. Regarding the other two real scenarios, as detailed in Section 6, we consider \(Q_{m}=1/3\) for the Plaza scenario, which corresponds to an open space with high solar radiation, and \(Q_{m}=2/3\) for the Station scenario, which corresponds to an indoor space with high ceilings and with poor ventilation. The results of the spatial exposure risk are shown in Figure 9. For the synthetic scenarios, we can see that the patterns are similar to the results obtained for the ERV. Nevertheless, the obtained MEMs are in general greater than using ERV, showing a higher exposure risk. This is mainly due to the way the exposure risk of a cell is obtained: in ERQ, each second of exposure is added up while for ERV only contacts with duration longer than 1 minute is considered. For the Plaza scenario (Figure 9d) we can see, as expected being an open space, that the exposure risk has been reduced considerably when compared to the previous ERV results. Only in some small spots, there is a small exposure risk, which corresponds to the locations where people stay. On the contrary, the Station scenario (Figure 9b displays a high exposure risk, particularly on the centre of the platforms and turnstiles, which are in general much higher than in the ERV evaluation. These results do not only depend on the value of \(Q_{m}\) but also on the number of contacts and their short proximity, not accounted for when using the previous ERV model. As in the ERV evaluation, we study the temporal evolution of the risk, obtaining for each second the aggregated equivalent MEMs between all pair of individuals in the scenario. We only show in Figure 10 the results for the Plaza and Station scenarios. Firstly, we can see that the ERQ is now a continuous plot (compared to the discrete plot of Figure 8). For the Plaza scenario, we can see that the exposition risk is very low. In the Station scenario,  
Figure 9: Heat maps of the ERQ measured in equivalent MEMs unit per cell (cell size 1 m\({}^{2}\)). Higher MEMs value imply higher risks. (**a**) RWP; (**b**) SWIM; (**c**) RWPa; (**d**) Plaza; (**e**) Station. we can clearly see a higher exposure risk and observe graphically how this risk increases when people crowd the platform waiting for the trains. Finally, we evaluate the impact of social distancing on the exposure risk. Along with the use of face masks, social distancing has been seen as one of the most effective measures that people can take. So, it is important to evaluate its impact to reduce the COVID-19 disease.