CCS Testing

One of the primary emergent behaviors we want to see in our model is Critical Community Size. Perhaps the best discussion of that phenomenon is Kurt Frey's PPT. (Link coming.)

In short, for a measles-like disease, we expect nodes with populations above, say, 250k to experience endemicity, while populations below that we expect to eliminate. This is all based on non-intervention immunity (for now).

We propose initially testing this using a Simplified Synthetic Spatial Scenario. Such a model will consist of ~100 nodes with varying population sizes. They will be isolated from each other. They will have vital dynamics (births and deaths). Each will be initially seeded.

We expect the discovered CCS threshold to vary with R0/Base Infectivity and Birth Rates.

Here's a screenshot of a sparklines UI of 100 nodes after almost 1000 timesteps. The left-most node has a population of just under 400k. The right-most node has a population of about 4000. Base Infectivity was 50 and CBR was 30 (high). The height of the bars represents prevalence. Going from left to right, larger population to smaller, we infer that the probability of elimination starts off at essentially 0, and then starts to decline, and is at 0 for the right third of the populations.

Manually testing -- manually varying BI and CBR and observing outputs -- shows expected behavior, broadly speaking. But this needs to be turned into a turnkey automated test, which requires some thought since we need to vary 2-3 inputs and look at results stastically.