A new study is being conducted to better understand the transmission of COVID- 19 – this time, through University of California, Irvine (UCI) students. The project’s principal investigators include UCI’s Infectious Disease Science Initiative’s co-directors Sanghyuk Shin and Vladimir Minin along with Ilhem Messaoudi (UCI Dept. of Molecular Biology), Bernadette Boden-Albala (Founding Dean of UCI Program in Public Health) and Dominik Wodarz (UCI Dept. of Population Health and Disease Prevention). The 1.5 year-long study will examine undetected viral transmission among people with mild or asymptomatic COVID-19 disease. Mathematical modeling suggests that 18-30-year-old young people are more likely to carry COVID-19 in this way. This is an area of study that is not well-understood, as little is known regarding the epidemiology of COVID-19 among university students. According to Adams et al., “Recent estimates suggest that up to 20% of college-aged adults 18 – 29 years old in the U.S. have one or more underlying conditions that increase their risk of severe COVID-19 disease” (2020).
Specific aims of this project are:
1) to determine the prevalence of prior SARS-CoV-2 infection among UCI students;
2) to estimate the risk of acquiring SARS-CoV-2 infection over time;
3) to refine existing mathematical models of COVID-19 transmission with age-specific estimates of asymptomatic infections among young adults.
A random sample of UCI students will be recruited to submit saliva and blood specimens at the time of enrollment and at months 3, 6, and 12 after enrollment. Saliva is a non-invasive specimen that has been shown to provide highly sensitive for detecting the presence of SARS-CoV-2 RNA via qRT-PCR. Completion of the proposed study will provide critical information for developing and refining interventions to prevent COVID-19 among university students, inform mathematical models for the transmission of SARS-CoV2, and assess the effect of easing current social distancing measures. Moreover, the proposed research could serve as a model for establishing COVID-19 surveillance systems in universities across the country.
References
Adams ML, Katz DL, Grandpre J. 2020. Population-Based Estimates of Chronic Conditions Affecting Risk for Complications from Coronavirus Disease, United States. Emerg Infect Dis.
