A network-based group testing strategy for colleges

Abstract Group testing has recently become a matter of vital importance for efficiently and rapidly identifying the spread of Covid-19. In particular, we focus on college towns due to their density, observability, and significance for school reopenings. We propose a novel group testing strategy whic...

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Autores principales: Alex Zhao, Kavin Kumaravel, Emanuele Massaro, Marta Gonzalez
Formato: article
Lenguaje:EN
Publicado: SpringerOpen 2021
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Acceso en línea:https://doaj.org/article/082d17451e6d4c97abd37f2edee78181
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Sumario:Abstract Group testing has recently become a matter of vital importance for efficiently and rapidly identifying the spread of Covid-19. In particular, we focus on college towns due to their density, observability, and significance for school reopenings. We propose a novel group testing strategy which requires only local information about the underlying transmission network. By using cellphone data from over 190,000 agents, we construct a mobility network and run extensive data-driven simulations to evaluate the efficacy of four different testing strategies. Our results demonstrate that our group testing method is more effective than three other baseline strategies for reducing disease spread with fewer tests.