Paper Info
Title
Mitigating Covid-19 Outbreaks In Workplaces And Schools By Hybrid Telecommuting
Abstract
Author summary The COVID-19 epidemics has forced most countries to impose prolonged contact-limiting restrictions at workplaces, universities, schools. Using simulation and taking into account the most salient epidemiological features of SARS-CoV-2, we analyze the risk of outbreak and the impact of contact-limiting strategies on three real-life contact networks stemming from a workplace, a primary school and a high school. The strategies investigated involve (1) Rotation, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off, where the whole group alternates periods of normal work interactions with complete telecommuting. Our study yields clear results, whatever the studied network (workplace, primary school and high school), we find that, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day can all help mitigate transmission below a certain epidemicity threshold. In the current context where institutions and companies have to quickly take local organizational decisions and review their planning or agendas, our results should help inform public health decisions.The COVID-19 epidemic has forced most countries to impose contact-limiting restrictions at workplaces, universities, schools, and more broadly in our societies. Yet, the effectiveness of these unprecedented interventions in containing the virus spread remain largely unquantified. Here, we develop a simulation study to analyze COVID-19 outbreaks on three real-life contact networks stemming from a workplace, a primary school and a high school in France. Our study provides a fine-grained analysis of the impact of contact-limiting strategies at workplaces, schools and high schools, including: (1) Rotating strategies, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off strategies, where the whole group alternates periods of normal work interactions with complete telecommuting. We model epidemics spread in these different setups using a stochastic discrete-time agent-based transmission model that includes the coronavirus most salient features: super-spreaders, infectious asymptomatic individuals, and pre-symptomatic infectious periods. Our study yields clear results: the ranking of the strategies, based on their ability to mitigate epidemic propagation in the network from a first index case, is the same for all network topologies (workplace, primary school and high school). Namely, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day. Moreover, our results show that below a certain threshold for the original local reproduction number R 0 l o c a l within the network (< 1.52 for primary schools, < 1.30 for the workplace, < 1.38 for the high school, and < 1.55 for the random graph), all four strategies efficiently control outbreak by decreasing effective local reproduction number to R 0 l o c a l < 1. These results can provide guidance for public health decisions related to telecommuting.
Year
DOI
Venue
2021
10.1371/journal.pcbi.1009264
PLOS COMPUTATIONAL BIOLOGY
DocType
Volume
Issue
Journal
17
8
ISSN
Citations 
PageRank 
1553-734X
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Simon Mauras100.34
Vincent Cohen-Addad28525.47
Guillaume Duboc300.34
Max Dupré la Tour400.34
Paolo Frasca540835.99
Claire Mathieu662.78
Opatowski Lulla721.12
Laurent Viennot849235.31