This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between laymans language used in disease outbreak reports and public health experts deep knowledge, and 2) making multi-lingual information available.