The VC/RC/US model was used to illustrate how quickly the calculation method of assessing V and R can become very complex. The VC/RS/UL model eliminates the difficult of calculating probabilities, but will only work well if you can handle the level of complexity you need for modeling variability.
Since we are using the simulation for the Randomness (RS) component, it is no longer available to us to model the Uncertainty component if we want to keep them separate. We have to construct a model that runs as follows:
Draw values from each uncertainty distribution for all uncertain parameters and place in risk model (start loop);
Simulate model and save results;
Repeat steps 1 and 2 until to get a 2nd order distribution for the selected individual (end loop);
This sounds pretty tedious, but the simulation software package provides a Two-Dimensional Simulation Tool that will allow you to automate the process. This Tool allows one to nominate uncertainty and variability distributions within a model separately and then completely automates the process.
Despite the automation provided by the facilities of the simulation software package's Two-dimensional Simulation Tool and the speed of modern computers, the simulations can take some time. However, in most non-trivial models that time is easily balanced by the reduction in complexity of the model (compared with an RC model) and therefore the time it takes to construct, as well as the more intuitive manner in which the models can be constructed which greatly helps avoiding errors.
The model VC_RS_UL converts the multiple disease, multiple area outbreak model into a VC/RS/UL model. The links to the software specific models are provided here:
Here is the screenshot of the model:
Here is a screenshot of the model:
@Risk users are also able to export the results into a model of just the variability and randomness (VC/RS) and make it into a table so that the RiskSimtable functions can use the values from these tables:
The spreadsheet of this @Risk model is provided here: VC_RS_UL_-_2
Running 50 simulations each of (say) 500 iterations allow us to review a second order model of the outputs. For example, the second-order probability distribution of the sum of total outbreaks over all diseases looks like this:
[In fact, only 10 of the distributions are shown here so that the figure is not too busy. However, the simulation software package offers you the option to plot all 50]