In 2015, almost half of the world population lived in areas at risk of malaria transmission. There were around 214 million malaria cases and 438,000 associated deaths. One of the major paths to prevent and reduce malaria transmission is through vector control, especially with the use of insecticide-treated nets (ITN). In this context, ITN distribution campaigns face several challenges, such as uncertainties related to funding, transportation, market and price volatility, which might be effectively tackled through long-term agreements and proper planning. However, that might not be an option for all humanitarian organizations and governments. Besides, considering uncertainties during budgetary planning is particular relevant. In this sense, a robust optimization model, based on Bertsimas and Sim (2004) and Fernandes et al. (2016) frameworks, is proposed to minimize the involved costs or, given a budget constraint, maximize the coverage of priority areas. A literature review on robust optimization applied to humanitarian logistics is conducted, in which aspects with less academic research attention are revealed and considered in the model, such as the simultaneous account of the aforementioned uncertainties and demand prioritization. A United Nations Children s Fund campaign in Ivory Coast is studied, and reveals that, as expected, as the robustness level increases so does the total costs. In return, the robust model generally provides a solution with improved supply chain flexibility, that might minimize efforts, in case it is necessary to adjust procurement and transportation plans when uncertainty is revealed. In addition, robust solutions were assessed through Monte Carlo simulations against several realizations of uncertain parameters values, pointing that, as desired, solution feasibility increases alongside the specified level of conservatism.