Optimal Testing and Containment Strategies for Universities in Mexico amid COVID-19

TL;DR

This paper develops a testing and containment framework for Mexican universities to safely reopen during COVID-19, optimizing limited testing resources through a novel allocation mechanism and practical web tool.

Contribution

It introduces a resource allocation model and web application for testing strategies, along with real-world pilot implementation and policy insights in the Mexican university context.

Findings

Effective testing allocation improves containment efforts.

Pilot implementation demonstrates practical utility.

Policy recommendations support safe reopening strategies.

Abstract

This work sets out a testing and containment framework developed for reopening universities in Mexico following the lockdown due to COVID-19. We treat diagnostic testing as a resource allocation problem and develop a testing allocation mechanism and practical web application to assist educational institutions in making the most of limited testing resources. In addition to the technical results and tools, we also provide a reflection on our current experience of running a pilot of our framework within the Instituto Tecnol\'ogico y de Estudios Superiores de Monterrey (ITESM), a leading private university in Mexico, as well as on our broader experience bridging research with academic policy in the Mexican context.