 Seasonal malaria epidemics are strongly linked with temperature and rainfall, and advance warning from seasonal climate models can potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. The study presents validation of a process-based, dynamic malaria model driven by hind casts from a state-of-the-art seasonal climate model from the European Center for Medium Range Weather Forecasts Against Observed Meteorological and Incidence Data for Botswana over the period 1982 to 2006. The study demonstrates forecast skill for upper teresol malaria incidents for the Botswana malaria season, January-May, using forecasts issued at the start of November, anticipating six out of the seven upper teresol malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change. This article was authored by Davey McLeod and Jones, Francesca DiGiseppe and others. We are article.tv, links in the description below.