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The rate at which new trees pop up is useful for estimating spillover frequency, which in turn is useful for identifiying animal hosts. Numerous trees over a short period of time may suggest a domesticated or agricultural animal host rather than a wild animal. As case tree plots become more common, patterns will likely emerge that indicate certain emergence scenarios, similar to how the shape of epidemic curves can differentiate a point source outbreak from a continuous sort outbreak.  Finally, case tree plots visually represent case outcomes by generation and by cluster, which can reveal new insights. For example, a disproportionate number of male index nodes could suggest that expsoure to the disease occurs in a male-dominated setting like hunting. A high mortality rate case fatality risk  among index nodes compared to non-index nodes suggests that the infection is less virulent when transmitted from person to person than when acquired from an animal source. Revealing this patterns is useful for understanding the epidemiology of the disease, and for identifying effective interventions.