Analysis

Congratulations! You have sucessfully created a model in Vensim PLE. You should now have the tools necessary to go on and create other models. You can also expand your Vensim PLE skills by looking into more advanced input (sliders!) and output (permanent graphs), as well as the full range of options in SyntheSim. But rather than forget the model you just worked to build, take a critical look at it and follow the discussion below.

Based on the custom graphs you generated, what can you conclude? Around the start of the third day of the simulation, there is an even number of susceptible and infected people. In addition, this is the point at which the disease peaks in terms of the number of people getting sick.

To see this fact illustrated, bring up a quick graph of Get Sick. Select Get Sick with the selection button , and then click on the Quick Graph button to see the value of Get Sick over time.

In the long term, what happens in this model? Everyone gets sick and stays that way. This may not be entirely realistic, but is in fact what we told the computer to model. We assumed that no one would get well. Take some time and list other assumptions made by this model.

It is worth noting that even the most sophisticated models involve assumptions and simplifications. The real question is whether or not the assumptions are reasonable and yield useful information. We could have made our model more accurate (for example, by including a box variable for recovered people), but that would necessitate making the model more complex. Scientific modeling requires a constant give-and-take between accuracy and complexity.

As a final word on this model, note that the assumptions made in it should be viewed as opportunities for exploration rather than limitations. Challenge yourself and/or your students to expand the model. What if infected people eventually get well? What if people who get well can get sick again? What if some people who get well develop an immunity to the disease? Visit the Center for Disease Control web site and search for real world data. Part of the appeal of interactive tools is that models you build, even simple ones, can help pose and answer numerous questions. Expanding and refining models builds pattern recognition and offers insight into the ways systsems and numbers behave.