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\section*{Introduction}   Zoonoses represent an estimated 58\% of all human infectious diseases, and 73\% of emerging infectious diseases \cite{woolhouse}. Careful tracking of zoonotic disease 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 hundreds thousands  of deaths combined \cite{sars2}. \cite{sars2, }.  Early identification of new outbreaks is critical to successful containment of these diseases. The current toolkit for visualizing data from these emerging diseases is limited. Th epidemic curve, plotted as a histogram of new cases over time, is one popular option. Epidemic curves are limited in that they do not indicate how cases are related to one another, nor do they represent an animal source. Network diagrams are a useful though less popular option. These diagrams can depict individual human clusters, but often do not have a time component, and cannot represent constellation of unconnected clusters. Here we introduce case tree plots and checkerboard plots to address those weaknesses, while also allowing easy visualization of case attributes like patient sex or health status.