Lesson 5: Epidemic Model REMIX + graph

While my original simulation simulates the effect of the transmission rate and / or recovery rate, where one observes the relative number of blue ("healthy") and red ("sick") "people" during the simulation, the introduction of a graph facilitates the ability of students to observe the effects of varying these parameters. That is, I believe that students could more easily acquire the concepts from the simulation from observing the graph rather than visually estimating the relative changes in the color of the turtles, which correspond to the number of sick and healthy people.

Changes in the transmission rate and recovery rate could correspond to changes in public health measures and disease treatment, respectively. Such changes can be positive (e.g. discovery of new drug or quarantine of sick people) or negative (e.g. development of antibiotic resistance or slashing public health budget).

The effect of changes in either the transmission rate and / or recovery rate could be examined by either examining the relative number of sick and healthy individuals in the population under different simulation conditions, i.e. run multiple simulations under different conditions.

Alternatively, a potentially more efficient method would be to examine the change in the relative steady-state number of sick and healthy individuals as these parameters are changed during the simulation. It's analogous to obtaining a culumative dose-response curve versus individual dose-response curve, where one should be aware of potential confounding factors; e.g. positive or negative cooperativity - don't know the validity of such an analysis / analogy in this case, since did not investigate the issue using this simulation. As such, recommend such an investigation.

There are flaws in the simulation due to its assumptions, e.g. a constant infection rate during the epidemic is invalid, since the population should change during the epidemic - recovered people should be more resistant to re-infection, so the infection rate should decrease during an epidemic, not remain a constant.

As such, while simulations are potentially a powerful teaching tool, a teacher should be aware of potential misconception(s) that a simulation might impart on a student.

The line graph feature is based on the work of:
http://www.slnova.org/RMalones/projects/5503/play/

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