Efficiency of preventing epidemic spreads of contact infections via reduction in transmission rate and change in network structure
Abstract
Epidemiological models have been used recently to explain the process of infection spread in a given population. Reduction of transmission probability as a method to prevent the spread of infection typically assumes that the network remains unchanged during its implementation. In this work, we investigate the extent of spread of infection in a static random geometric network with free boundary conditions for different transmission probabilities. The infection process is investigated after 106 iterations upon the assumption of one-at-a-time contact per iteration. The behavior with varying network structure and transmission probability is examined. We find that a “breaking point” is dependent on the network structure that is a function of the average number of contact possibilities per node. Hence, the network structure besides simply reducing transmission rate must be considered if infection spread over the whole population is to be totally stopped.
