Designing Mechanisms for Social Good:

The seminar focuses on designing mechanisms to maximize the efficient use of limited resources, such as COVID testing, by applying optimization methods aimed at minimizing the impact of isolation and improving public health decision-making. One of the main approaches is group testing, a technique that combines samples from multiple individuals to detect infections in a single analysis, allowing for resource savings and a higher number of tests. However, this method presents challenges related to sensitivity and accuracy, especially in cases of asymptomatic infections with low viral loads. These techniques are already being implemented in educational institutions in Mexico, such as Tecnológico de Monterrey, where they are used to manage the health safety of students and faculty through a strategic allocation of tests. Throughout the seminar, different strategies for efficiently assigning tests are presented, considering population heterogeneity and infection risk levels in each segment to optimize the limited number of available tests. Additionally, the project fosters close collaboration between researchers and public decision-makers to address challenges related to data collection and the practical implementation of these solutions in various institutions, seeking a balance between research and real-world application.