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Zoonoses represent an estimated 64\% of all human infectious diseases, and 75\% of emerging infectious diseases. Careful tracking of zoonoses is a major focus of global public health protection strategy. Recent examples of zoonotic outbreaks include Severe Acute Respiratory Syndrome, H1N1, and Middle East Respiratory Syndrome, which have caused thousands of deaths combined. Early identification of new outbreaks is critical to successful containment of these diseases, because outbreaks can sometimes be controlled through interventions like limiting human exposure to the source, or isolating victims.  The current toolkit for visualizing data from these emerging diseases is limited. Epidemic curves, plotted as a histogram of new cases over time, is one popular option. These curves, however, do not indicate how cases are related to one another, or to an animal source. Network diagrams are a useful though less popular option. These diagrams can depict individual human clusters, but do not have a time component, and cannot represent constellation of unconnected clusters.    Case tree plots assist epidemiologists with visualizing and analyzing zoonoses with human to human potential. Case tree plots provide valuable insight in the following ways:   \begin{itemize}   \item see how epidemiology, esp $R0$, is changing over time   \item estimating spillover frequency, which in turn is useful for identifying animal host. Frequent spillovers -> domesticated or agricultural animals, rare spillovers -> wild animals   \item estimating $R0$ (human to human transmissibility)   \item identifying superspreaders   \item analyzing case outcomes by generation and by cluster   \end{itemize}