In this lab, you will work to simulate a network-based epidemic model with demography (births and deaths, or another form of arrivals and departures). The specific learning objectives for this lab are to:
Once you are ready, start out by clearing your R object environment, to make sure that you do not have any objects lingering from the tutorial. This can be accomplished with:
rm(list = ls())In the tutorial, we used a risk attribute to define a
heterogeneous population that varied in terms of mean degree and
propensity for mixing. We then fit two models: one with homogeneity in
activity levels and proportional (random) mixing, and one with
heterogeneity in activity levels and preferential mixing by risk group.
In this lab, you will fit the other two possible models to understand
the unique contribution of assortative mixing and heterogeneity in
activity on epidemic outcomes.
Change the network parameterization so that you run a model with
the same assortative mixing as Model 2 in the tutorial, but no
heterogeneity in activity. Use the same epidemic parameters as the
tutorial. Run 5-10 simulations of this model, using the
tergmLite approach. Compare visually the outcomes from the
model to the two model outcomes in the tutorial.
Change the network parameterization so that you run a model with
the same heterogeneity in mean degree as Model 2 in the tutorial, but
proportional (random) mixing. Use the same epidemic parameters as the
tutorial. Run 10 simulations of this model, using the
tergmLite approach. Compare visually the outcomes from the
model to the two model outcomes in the tutorial.
If time permits, assume that there is disease-induced mortality
in your epidemic, by doubling the di.rate. What change
needs to be made to the dissolution_coefs inputs (use a
basic estimate for the d.rate)? Run one of the network
model paramterizations with heterogeneity in mean degree. Evaluate how
disease-induced mortality impacts the overall epidemic trajectory
overall, and by risk group. Try plotting some of the other overall
variables from the model (arrivals, departures, total population
size).
After you have completed running the models above, please answer the following questions and discuss in your work group.
What is the general relationship between assortative mixing on epidemic outcomes under different conditions of group heterogeneity?
How does disease-induced mortality impact the overall epidemic for the network model with heterogeneity in activity?
Last updated: 2022-07-07 with EpiModel v2.3.0