COVID-19: Reopening universities requires rapid testing, mask wearing and contact reduction
Scientific Reports
March 17, 2021
Rapid testing that is cost-effective and easy to administer in high volumes, together with preventative measures such as mask wearing, physical distancing and contact reduction, is needed if universities are to consider reopening during the COVID-19 pandemic. The findings from a modelling study using data from 86 universities in the United States are published in Scientific Reports.
Ujjal Mukherjee and colleagues used analytical modelling to simulate the spread of COVID-19 within universities. The authors found that due to the particular challenges associated with asymptomatic transmission, contact tracing was not enough to contain infection spread, whereas rapid bulk testing was associated with a reduced number of infections.
The model also showed that efficacy of testing dropped if results were delayed either due to the nature of the test or limited testing capacity, as infected individuals continued to interact with people while awaiting test results. Testing efficacy also decreased if isolation measures were not 100% effective. Simulating the effect of adopting preventative measures such as mask wearing and sanitization, the authors found that even at higher testing rates infections spread quickly if these measures were not stringent enough.
The findings suggest that bulk testing in combination with stringent preventative measures such as mask wearing, physical distancing and contact reduction are necessary to safely reopen education institutions. The analytical model provided in this study could be used by institutions to evaluate the effect of different strategies for reopening based on their own COVID-19 data, according to the authors.
The findings suggest that bulk testing in combination with stringent preventative measures such as mask wearing, physical distancing and contact reduction are necessary to safely reopen education institutions. The analytical model provided in this study could be used by institutions to evaluate the effect of different strategies for reopening based on their own COVID-19 data, according to the authors.
doi:10.1038/s41598-021-84192-y
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