From a life spent on count statistics, one thing I think is interesting is how definitively you can reject perfect randomness from a very small sample like this.

The expected event count from 17,000 people exposed to a month of constant uniform event risk with an annual hazard rate of 20 per 100,000 per year is 0.28. The p-value for observing a count of 5 from a (Poissonian) mean of 0.28 is 1 in 100,000. So it's pretty unlikely by perfect random chance.

The other thing you see in a life spent in count statistics is a lot of statistically extreme events that turn out to have no deep or predictive significance.