Modelling pooling strategies for SARS-CoV-2 testing in a university setting

Hemani, G.; Thomas, A. C.; Walker, J. G.; Trickey, A.; Nixon, E.; Ellis, D.; Kwiatkowska, R.; Relton, C.; Danon, L.; Christensen, H.; Brooks-Pollock, E.

Pre-symptomatic and asymptomatic transmission of SARS-CoV-2 are important elements in the Covid-19 pandemic, and until vaccines are made widely available there remains a reliance on testing to manage the spread of the disease, alongside non-pharmaceutical interventions such as measures to reduce close social interactions. In the UK, many universities opened for blended learning for the 2020-2021 academic year, with a mixture of face to face and online teaching. In this study we present a simulation framework to evaluate the effectiveness of different asymptomatic testing strategies within a university setting, across a range of transmission scenarios. We show that when positive cases are clustered by known social structures, such as student households, the pooling of samples by these social structures can substantially reduce the total cost of conducting RT-qPCR tests. We also note that routine recording of quantitative RT-qPCR results would facilitate future modelling studies.