Contacts and behaviours of university students during the COVID-19 pandemic at the start of the 2020/21 academic year

Nixon, Emily; Trickey, Adam; Christensen, Hannah; Finn, Adam; Thomas, Amy; Relton, Caroline; Montgomery, Clara; Hemani, Gibran; Metz, Jane; Walker, Josephine G.; Turner, Katy; Kwiatkowska, Rachel; Sauchelli, Sarah; Danon, León; Brooks-Pollock, Ellen

doi:10.1101/2020.12.09.20246421

Cited by 7 publications

(10 citation statements)

References 11 publications

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“…The total cases of infections and deaths over a 90-day semester if a fully unvaccinated population is on campus (contact rates of 16 to 24 per person per day as reported for regular face-to-face instructions [ 42 , 43 ]) suggest an exponential growth in infections in most testing scenarios, even if face mask and physical distancing are used at levels reported during the pandemic (transmission rates of 5% to 8%) ( S3 Table ). With contact rate of 6 to 8 per person per day (corresponding to reported numbers when several universities moved to partial or full remote instructions [ 35 , 36 ]) and use of facemask and physical distancing at levels reported during the pandemic, an exponential growth in infections was prevented with the following testing scenarios: 33% per day mass test only, at least 33% trace and test only, any of the combination tests, and any of the delayed combination tests ( Table 3 ). In these suitable scenarios, the peak number of trace and tests, per 10,000 persons, varied from 2 to 64 per day, and the peak number of quarantines, per 10,000 persons, varied from 3 to 26 per day ( Table 3 ).…”

Section: Resultsmentioning

confidence: 99%

“…Some of the surveys were specific to university students in the United States while others were either university students in other countries or general populations. Studies on surveys of university students, when partial shutdowns were enforced and universities resorted to varying levels of remote classes, reported 6 to 8 contacts per person per day [ 35 , 36 ]. However, students who self-reported as providing essential services or caring for non-household members (~23%) reported an average contact rate of about 14 per person per day [ 37 ].…”

Section: Methodsmentioning

confidence: 99%

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Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting

et al. 2021

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We simulated epidemic projections of a potential COVID-19 outbreak in a residential university population in the United States under varying combinations of asymptomatic tests (5% to 33% per day), transmission rates (2.5% to 14%), and contact rates (1 to 25), to identify the contact rate threshold that, if exceeded, would lead to exponential growth in infections. Using this, we extracted contact rate thresholds among non-essential workers, population size thresholds in the absence of vaccines, and vaccine coverage thresholds. We further stream-lined our analyses to transmission rates of 5 to 8%, to correspond to the reported levels of face-mask-use/physical-distancing during the 2020 pandemic. Our results suggest that, in the absence of vaccines, testing alone without reducing population size would not be sufficient to control an outbreak. If the population size is lowered to 34% (or 44%) of the actual population size to maintain contact rates at 4 (or 7) among non-essential workers, mass tests at 25% (or 33%) per day would help control an outbreak. With the availability of vaccines, the campus can be kept at full population provided at least 95% are vaccinated. If vaccines are partially available such that the coverage is lower than 95%, keeping at full population would require asymptomatic testing, either mass tests at 25% per day if vaccine coverage is at 63–79%, or mass tests at 33% per day if vaccine coverage is at 53–68%. If vaccine coverage is below 53%, to control an outbreak, in addition to mass tests at 33% per day, it would also require lowering the population size to 90%, 75%, and 60%, if vaccine coverage is at 38–53%, 23–38%, and below 23%, respectively. Threshold estimates from this study, interpolated over the range of transmission rates, can collectively help inform campus level preparedness plans for adoption of face mask/physical-distancing, testing, remote instructions, and personnel scheduling, during non-availability or partial-availability of vaccines, in the event of SARS-Cov2-type disease outbreaks.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting

et al. 2021

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“…We assume a diagnostic specificity of 99.5% for a single RT-qPCR test, and therefore the pool+followup results will have a false positive rate of 0.005 2 .…”

Section: Methodsmentioning

confidence: 99%

“…In the midst of the COVID-19 pandemic, university students represent a demographic in the population who are likely to experience low rates of symptomatic infection 1 while being in a high contact social setting 2,3 . Extensive testing is required to monitor and manage potentially high rates of SARS-CoV-2 infection within a student population, particularly to minimise transmission to vulnerable individuals and groups, both within and outside of the student population 4 .…”

Section: Introductionmentioning

confidence: 99%

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

Hemani

Thomas

Walker

et al. 2021

Preprint

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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.

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“…In the midst of the coronavirus disease 2019 (COVID-19) pandemic, university students represent a demographic in the population who are likely to experience low rates of symptomatic infection 1 while being in a high contact social setting 2,3 . Extensive testing is required to monitor and manage potentially high rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection within a student population, particularly to minimise transmission to vulnerable individuals and groups, both within and outside of the student population 4 .…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

Self Cite

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Background: Pre-symptomatic and asymptomatic transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important elements in the coronavirus disease 2019 (COVID-19) pandemic, and there remains a reliance on testing to manage the spread of the disease. 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. Methods: In this study we present a simulation framework to evaluate the effectiveness of different mass testing strategies within a university setting, across a range of transmission scenarios. Results: The sensitivity of 5x pooled RT-qPCR tests appears to be higher than testing using the lateral flow device with relatively little loss compared to single RT-qPCR tests, and is improved by pooling by social cluster. The range of strategies that we evaluated give comparable results for estimating prevalence. Conclusions: Pooling tests by known social structures, such as student households can substantially improve the cost effectiveness of RT-qPCR tests. We also note that routine recording of quantitative RT-qPCR results would facilitate future modelling studies.

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Contacts and behaviours of university students during the COVID-19 pandemic at the start of the 2020/21 academic year

Cited by 7 publications

References 11 publications

Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting

Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting

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

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

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