Attack rates are one of the most common tools in outbreak epidemiology. They seem to offer a quick answer to a simple question: how many exposed people got sick? But what if the exposed group was never truly sharing the same exposure in the first place? 

In this episode, we break down why attack rates often fail when exposure is uneven, how denominator assumptions distort outbreak interpretation, and why summary measures can hide the real structure of transmission.

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