High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions

Abstract

Controlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6–35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.

Impacts of vaccination and asymptomatic testing on SARS-CoV-2 transmission dynamics in a university setting

“…Our work suggests that asymptomatic testing is a useful supporting measure and can help to further reduce case numbers, having the most impact at low to medium levels of vaccination uptake. This corroborates previous findings reporting that asymptomatic testing is more impactful at higher reproduction numbers [8][9][10] . Reliably estimating uptake of asymptomatic testing is challenging.…”

“…Testing of asymptomatic individuals leads to increased case detection and may be particularly important in the university student population where, due to the younger age structure, cases are more likely to be asymptomatic 6,7 . Previous modelling of asymptomatic testing in a university found that adherence to testing and isolation was important for reducing transmission 8 , particularly at high values of the reproduction number [8][9][10] .…”

COVID-19 Pandemic Effect on Energy Consumption in State Universities: Michoacan, Mexico Case Study

“…In a complementary way, collateral effects are discussed, formulating a scenario of impacts generated by the reduction of student mobility during this pandemic. The objective of this research is to diagnose energy consumption patterns during the COVID-19 pandemic, as well as the environmental and economic effects that make it possible to determine possible routes for restructuring the university energy system, and to establish the basis for the construction of new scenarios on the management and efficient use of electricity during and after the pandemic, encouraging the construction of alternative proposals for self-sufficiency through sustainable electricity supply strategies, also promoting reflection regarding energy consumption linked to the new normal and distance education schemes that, in the coming years, will be abundantly reproducible in most universities [48]. It is also expected to encourage the establishment of realities of satisfaction of electrical energy needs economically and with low environmental impact.…”

Impact of routine asymptomatic screening on COVID-19 incidence in a highly vaccinated university population

“…In order for universities to plan a safe return to campus, several studies have analyzed the potential for mitigation strategies to control COVID-19 transmission in a university setting [4][5][6][7][8][9][10][11][12][13][14]. Most of these studies have focused on masks mandates, contact tracing, routine testing, and physical distancing.…”

“…Most of these studies have focused on masks mandates, contact tracing, routine testing, and physical distancing. Some utilized social mixing data from contact surveys [1,9,15,16], whereas others relied on simulations of daily behavioural contacts among students [17]. Only a few of these studies have considered scenarios that include a highly vaccinated university population [1,2,16,18,19].…”