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 falciparum 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.

根据世界卫生组织的数据，全世界每两分钟就有一名儿童死于疟疾。处方抗疟药时，医师面临的挑战性问题在于估计被隔离的寄生虫恶性疟原虫噪声的循环寄生虫浓度测量，同时处理不确定性。在本文中，我们为疟疾患者的不确定模型设计了一种区间状态估计量。我们考虑一种普遍存在的情况，其中除了感染率（其边界值不可用）之外，模型中的所有参数都只能使用允许值的间隔。此外，我们通过使用线性编程来最小化估计的间隔宽度来为间隔观察器计算最佳增益。我们测试观察员在模型中的效率，以及在南卡罗来纳州哥伦比亚市和佐治亚州Milledgeville的美国国立卫生研究院实验室由美国公共卫生服务局收集的实际测量数据的真实性。