Based on previous observations that the 2b protein is also a movement protein (19, 63) , that the presence of the 2b protein was necessary for the cell-to-cell movement of pseudorecombinants viruses (21) , and that the 2b protein is a viral RNA-binding protein (Figure 4) , it seems likely that the 2b binds to and selects specific recombinant viral RNAs for cell-to-cell movement. The different forms of recombinant RNAs generated may have different affinities for the various 2b proteins, leading to selection of one recombinant form over another by a particular 2b protein, which leads eventually to selection of the recombinant RNA over the parental RNA. Since selection to reach detectable levels was only observed after several weeks, the recombinant viral RNAs do not appear to be under strong selection pressure, although there is clearly a gradual selection for the recombinant RNAs over the parental RNA 3. This was seen in the slow appearance of the recombinant RNAs in both sets of time course experiments ( Figure 6 and Supplementary Figure 1 ). The rate of selection could be tested further by direct competition experiments. The Q-CMV 2b protein did not select for any recombinants, while the TAV and WAII-CMV 2b proteins selected for different recombinants, possibly reflecting differences in their RNA-binding properties. It would also be interesting to determine whether various 2b mutants would show differences in their selection of different recombinants. Epigrass: a tool to study disease spread in complex networks BACKGROUND: The construction of complex spatial simulation models such as those used in network epidemiology, is a daunting task due to the large amount of data involved in their parameterization. Such data, which frequently resides on large geo-referenced databases, has to be processed and assigned to the various components of the model. All this just to construct the model, then it still has to be simulated and analyzed under different epidemiological scenarios. This workflow can only be achieved efficiently by computational tools that can automate most, if not all, these time-consuming tasks. In this paper, we present a simulation software, Epigrass, aimed to help designing and simulating network-epidemic models with any kind of node behavior. RESULTS: A Network epidemiological model representing the spread of a directly transmitted disease through a bus-transportation network connecting mid-size cities in Brazil. Results show that the topological context of the starting point of the epidemic is of great importance from both control and preventive perspectives. CONCLUSION: Epigrass is shown to facilitate greatly the construction, simulation and analysis of complex network models. The output of model results in standard GIS file formats facilitate the post-processing and analysis of results by means of sophisticated GIS software. Epidemic models describe the spread of infectious diseases in populations. More and more, these models are being used for predicting, understanding and developing control strategies. To be used in specific contexts, modeling approaches have shifted from "strategic models" (where a caricature of real processes is modeled in order to emphasize first principles) to "tactical models" (detailed representations of real situations). Tactical models are useful for cost-benefit and scenario analyses. Good examples are the foot-and-mouth epidemic models for UK, triggered by the need of a response to the 2001 epidemic [1, 2] and the simulation of pandemic flu in differ-ent scenarios helping authorities to choose among alternative intervention strategies [3, 4] .