Malaria also presents a challenge. This disease continues to devastate sub-Saharan Africa and other parts of the developing world. Substantial resources over the past several decades have gone toward eradication, vaccination, treatment, and, more recently, prediction of malaria outbreaks. Satellite imaging has been used to predict the distribution of 5 of the 6 Anopheles gambiae complex species that are responsible for much of the malaria transmission in Africa (13) . However, human factors again make accurate prediction of disease events complex. Prediction of a disease event is complicated by host immunity effects, which can result in cycles of infection that would appear to bear no relationship to environmental variables. To predict malaria outbreaks, remote sensing technologies need to be coupled with a better understanding of how specific populations are effected by host immunity, which could allow population susceptibility at any given time to be estimated.