In a pandemic situation, a large quantity of medical items are being consumed by citizens globally. If not properly processed, these items can be pollutant or even dangerous. Inspired by a real case study in the city of Barcelona, and assuming that data from container sensors are available in the city open repository, this work addresses a medical waste collection problem both with and without uncertainty. The waste collection process is modeled as a rich open vehicle routing problem, where the constraints are not in the loading dimension but in the maximum time each vehicle can circulate without having to perform a mandatory stop, with the goal of minimizing the time required to complete the collection process. To provide high-quality solutions to this complex problem, a biased-randomized heuristic is proposed. This heuristic is combined with simulation to provide effective collection plans in scenarios where travel and pickup times are uncertain.