COVID-19 Modeling Pt. 3

In my last post, I mentioned the SIR (susceptibility, infected, and recovery) model that incorporates the interaction effect between variables. SIR models can range from simple models, such as the following:

To complex models, such as the SEIR (susceptibility, exposure, infected, recovered) Vensim simulation model. derived by Tom Fiddaman of Ventana, the SEIR is an example of a complex system dynamics approach to modeling. The benefit of advanced SIR or, in this case, SEIR models are that they allow policymakers to simulate the impact of various policy actions. For example, it is possible to simulate how social distancing might move the curve of infected individuals to a later period, and better understand how social distancing might impact the number of deaths resulting from overwhelmed healthcare systems.


While all the models described to this point can help policymakers or community leaders forecast and consider “what-if” scenarios, they do not do an excellent job of helping to determine if variables of interest, such as if the number of cases or number of deaths is beginning to decline. In this situation, what is needed is a tool which will make it easy to determine if contiguous areas should receive extra assistance or if a community is ready to reopen. In the next post, I will describe some industrial methods which can help with these types of issues. Until next time, remember to protect yourself which also helps protect your neighbors and community.

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