The SWIR model was introduced in 2017 by Lee et al. In this model, during the epidemics, a node is allowed to change its status from Susceptible (S) to Weakened (W) or Infected (I), then to Removed (R). The model is instantiated on a graph having a non-empty set of infected nodes. At time t a node in the state I is selected randomly and the states of all neighbors are checked one by one. If the state of a neighbor is S then this state changes either i) to I with probability kappa or ii) to W with probability mu. If the state of a neighbor is W then the state W changes to I with probability nu. We repeat the above process for all nodes in state I and then changes to R for each associated node.