Table 1.
Time (days) used as model parameters.
Fig 1.
Dynamics of the model: An infected individual can be symptomatic or asymptomatic.
Symptomatic individuals can go to the infirmary and, eventually, to the ICU.
Fig 2.
Percentage of infected agents for different values of mobility restriction.
Fig 3.
Percentage of infected agents for different values of mobility restriction for 70% of individuals wearing masks.
Fig 4.
(a) Number of new infections per day divided by the actual number of individuals responsible for those infections for different values of mobility restriction (R0). (b) Number of new infections per day by the total number of infected on that day for different values of mobility restriction ().
Table 2.
Maximum infected and number of ICU beds required every 10000 individuals for each percentage of mobility restriction.
Simulations without PPE.
Fig 5.
Example of transmission networks generated at the time step corresponding to the maximum of infected agents in each mobility restriction scenario, without PPE, colored according to out-degree value, betweenness and closeness centrality: (a) Out-degree and 0% of mobility restriction; (b) Betweenness centrality and 0% of mobility restriction; (c) Closeness centrality and 0% of mobility restriction; (d) Out-degree and 40% of mobility restriction; (e) Betweenness centrality and 40% of mobility restriction 40%; (f) Closeness centrality and 40% of mobility restriction; (g) Out-degree and 90% of mobility restriction; (h) Betweenness centrality and 90% of mobility restriction; (i) Closeness centrality and 90% of mobility restriction.
Fig 6.
Out-degree distribution for each mobility restriction percentage considered.
Lines corresponds to exponential fitting. Inset of the fitting parameters versus the percentage of restriction mobility. Data registred at the end of the simulation.
Fig 7.
Betweenness centrality distribution of each mobility restriction value.
Lines are just guides for the eyes. Data registred at the end of the simulation.
Fig 8.
Closeness centrality distribution for each mobility restriction value.
Lines are just guides for the eyes. Data registred at the end of the simulation.
Fig 9.
(a) infection period; (b) travelled distance during simulation; (c) number of contacts during whole simulation and (d) number of contacts during infection period.
All distributions in function of degree.
Fig 10.
Out-degree measured for simulations: No masks and no mobility restriction; no masks and 40% mobility restriction; individuals wearing masks and for all individuals.
Data registred at the end of the simulation.
Fig 11.
Betweenness centrality measured for simulation: No masks and no mobility restriction; no masks and 40% mobility restriction; 70% wearing masks and no mobility restriction.
Data registred at the end of the simulation.
Fig 12.
Closeness centrality measured for simulation: No masks and no mobility restriction; no masks and 40% mobility restriction; 70% wearing masks and no mobility restriction.
Data registred at the end of the simulation.