The model will stop running once the virus has completely died out. The INITIAL-OUTBREAK-SIZE slider determines how many of the nodes will start the simulation infected with the virus. This process is repeated until the network has the correct number of links to give the specified average node degree. A node is randomly chosen and connected to the nearest node that it is not already connected to. The network that is created is based on proximity (Euclidean distance) between nodes.

Using the sliders, choose the NUMBER-OF-NODES and the AVERAGE-NODE-DEGREE (average number of links coming out of each node). When a node becomes resistant, the links between it and its neighbors are darkened, since they are no longer possible vectors for spreading the virus. If a node does recover, there is some probability that it will become resistant to this virus in the future (given by the GAIN-RESISTANCE-CHANCE slider).

When the virus has been detected, there is a probability that the virus will be removed (determined by the RECOVERY-CHANCE slider). This might correspond to a regularly scheduled virus-scan procedure, or simply a human noticing something fishy about how the computer is behaving. Only every so often (determined by the VIRUS-CHECK-FREQUENCY slider) do the nodes check whether they are infected by a virus. Infected nodes are not immediately aware that they are infected. This might correspond to up-to-date antivirus software and security patches that make a computer immune to this particular virus. Resistant nodes (colored gray) cannot be infected. This might correspond to the probability that someone on the susceptible system actually executes the infected email attachment. Susceptible neighbors (colored green) will be infected with a probability given by the VIRUS-SPREAD-CHANCE slider. HOW IT WORKSĮach time step (tick), each infected node (colored red) attempts to infect all of its neighbors. In the academic literature such a model is sometimes referred to as an SIR model for epidemics. Each node may be in one of three states: susceptible, infected, or resistant. Although the model is somewhat abstract, one interpretation is that each node represents a computer, and we are modeling the progress of a computer virus (or worm) through this network. This model demonstrates the spread of a virus through a network. You can also Try running it in NetLogo Web If you download the NetLogo application, this model is included. NetLogo Models Library: Virus on a Network

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