A holistic approach for suppression of COVID-19 spread in workplaces and universities

Abstract

As society has moved past the initial phase of the COVID-19 crisis that relied on broad-spectrum shutdowns as a stopgap method, industries and institutions have faced the daunting question of how to return to a stabilized state of activities and more fully reopen the economy. A core problem is how to return people to their workplaces and educational institutions in a manner that is safe, ethical, grounded in science, and takes into account the unique factors and needs of each organization and community. In this paper, we introduce an epidemiological model (the “Community-Workplace” model) that accounts for SARS-CoV-2 transmission within the workplace, within the surrounding community, and between them. We use this multi-group deterministic compartmental model to consider various testing strategies that, together with symptom screening, exposure tracking, and nonpharmaceutical interventions (NPI) such as mask wearing and physical distancing, aim to reduce disease spread in the workplace. Our framework is designed to be adaptable to a variety of specific workplace environments to support planning efforts as reopenings continue. Using this model, we consider a number of case studies, including an office workplace, a factory floor, and a university campus. Analysis of these cases illustrates that continuous testing can help a workplace avoid an outbreak by reducing undetected infectiousness even in high-contact environments. We find that a university setting, where individuals spend more time on campus and have a higher contact load, requires more testing to remain safe, compared to a factory or office setting. Under the modeling assumptions, we find that maintaining a prevalence below 3% can be achieved in an office setting by testing its workforce every two weeks, whereas achieving this same goal for a university could require as much as fourfold more testing (i.e., testing the entire campus population twice a week). Our model also simulates the dynamics of reduced spread that result from the introduction of mitigation measures when test results reveal the early stages of a workplace outbreak. We use this to show that a vigilant university that has the ability to quickly react to outbreaks can be justified in implementing testing at the same rate as a lower-risk office workplace. Finally, we quantify the devastating impact that an outbreak in a small-town college could have on the surrounding community, which supports the notion that communities can be better protected by supporting their local places of business in preventing onsite spread of disease.

COVID-19 Infection among Elite Football Players: A Nationwide Prospective Cohort Study

“…Early diagnosis of the infections and appropriate clinical management are important for treating the infected athletes, minimize the risk of transmission, and helped Super League Greece to continue normally the schedule of football matches without any postponement. Another study from Poole et al supports our results and suggests that continuous testing can help a workplace avoid an outbreak by reducing undetected asymptomatic individuals [ 22 ]. Modelling studies estimated that weekly PCR testing to screen workers in health facilities and other high-risk groups, irrespective of symptoms, would reduce their contribution to SARS-CoV-2 transmission by 23% [ 19 ].…”

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

“…Because of this, the COVID-19 pandemic presented a particular challenge for IHEs during the Fall 2020 semester [16][17][18][19][20][21]. On the one hand, bringing students back for on-campus and in-person education introduced the risk that an IHE would contribute to or exacerbate large regional outbreaks [22][23][24][25][26][27][28][29][30]; on the other hand, postponing students' return to campus may bring economic or social hardship to the communities in which the IHEs are embedded [31][32][33][34], since IHEs are often large sources of employment for counties across the United States. As a result, IHEs instituted a variety of "reopening" strategies during the Fall 2020 semester [35][36][37][38][39][40][41][42][43][44].…”

Natural history and cycle threshold values analysis of COVID-19 in Xiamen City, China

“…The first case of this outbreak had a history of sojourn in a COVID-19 infected area (Putian City, Fujian Province) from September 5 to September 8, 2021, while the specificity of his occupation (factory worker) led to the outbreak of this aggregated outbreak ( Poole et al, 2021 ). The median incubation period calculated for confirmed patients in this study was 4 days, which is similar to the incubation period of the outbreaks of the Delta variant in other cities, but higher than the currently prevalent Omicron variant ( Del Aguila-Mejia et al, 2022 ; Wang et al, 2021 ), this may be due to that the incubation period of the virus variant decreases with the variation of the virus ( Liu et al, 2021 ).…”