A child dies from malaria every two minutes worldwide, according to the World Health Organization. When prescribing antimalarial drugs, a challenging problem for physicians consists in estimating sequestered parasites Plasmodium fal-ciparum populations from noisy measurements of circulating parasite concentrations , while handling uncertainty. In this article, we design an interval state estimator for uncertain models of malaria patients. We consider the ubiquitous case in which only intervals of admissible values are available for all parameters in the model except for infection rates, whose bounding values are unavailable. Furthermore we compute optimal gains for the interval observer by using linear programming to minimize the estimated interval width. We test the observer's efficiency in simulation for a model and for real measured data collected by the US Public Health Service at the National Institutes of Health laboratories in Columbia, South Carolina and Milledgeville, Georgia.