Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication

Azizi, Asma; Montalvo, Cesar; Espinoza, Baltazar; Kang, Yun; Castillo-Chavez, Carlos

Proceed to quantify the sensitivity of the final size of the outbreak as a function of the prevalence threshold P Ã over the network structures G E , G W , and G S , Fig. 5 , for the simulated G E network that representing homogeneous random mixing and for the simulated G W network, we identify an optimal point for P Ã (the point that final size is minimized), that means awareness spread is most effective in reducing final size for these values of P Ã . For larger values of P Ã , the awareness policy is useless because it starts very late when many individuals got already infected, while for smaller values of P Ã is less effective because in this case, there is not enough infected cases in the population and therefore, individuals are not surrounded by infected contacts and consequently their social distancing for only one time and for a limited period wastes their protection, that is, they are protecting themselves when there is a small risk of catching infection, while later time when this risk increases they do not take any proper action, see subfigures (5a), and (5b). . 4 . Prevalence of infection versus time for three different network structure: the curves are the mean of 100 different stochastic simulations seeding the same initial condition. The diffusion of infection happens faster and more intense in more heterogeneous network G S , and awareness diffusion has less impact on reducing peak of infection for G S (by 6%). For other networks reduction of peak is by 19%.