‘Being able to accurately forecast which populations are most at risk of viral diseases … would allow for the more efficient use of resources, while improving health.’ Where is forecasting in the prevention of infectious diseases? An ounce of prevention, so the approbation goes, is worth a pound (in the nonmetric world) of cure. In a more official sense, public health has as an article of faith that prevention is a cheaper, more efficient and ‘better’ approach to maintaining human health than interventions and treatments. The cornerstone of the prevention of chronic and environmental diseases, such as heart disease, stroke and some cancers, as well as infectious diseases such as smallpox, measles and sexually transmitted infections (including HIV and human papillomavirus), is the identification and communication of risk factors to individuals at risk, with a hoped-for change in behavior. Furthermore, vaccines are developed to prevent disease and therapies are designed to mitigate the effects for those who do suffer from disease. However, prevention on a global scale is still an incredibly expensive endeavor, and the need to ensure the prevention message is made clear risks creating listener fatigue, with people eventually ignoring the message. The potential consequence of this is that people’s risk increases as they fail to believe the accuracy of the information provided. Thus, targeted approaches are considered critical, both in terms of the frequency and type of message, vaccines or therapeutics provided. The issue of accurately targeting interventions is also of practical concern as many infectious diseases are reported to have potential populations in the billions at risk, whereas the annual incident number of disease cases may be in the hundreds of thousands. This difference indicates that we currently either identify who is at risk based on terms that are too broadly defined or that other, unidentified factors determine who develops disease. Regardless, human scales are much too large for most technologies to deliver interventions in an efficient manner. Thus, being able to accurately forecast which populations are most at risk of viral diseases and when infection will occur would allow for the more efficient use of resources, while improving health. Another major challenge arises when forecasting focuses on characterizing the emergence of episodic and ‘new’ diseases. In these situations, the challenge is that outbreaks of apparently new diseases (e.g., severe acute respiratory syndrome or highly pathogenic avian influenza) have undefined biologies and appear as almost point-source outbreaks.