ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2021
Examining SARS-CoV-2 Interventions in Residential Colleges Using an Empirical Network.
Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
- Connecting mass-action models and network models for infectious diseases.PLoS computational biology · 2025Article
- Accounting for contact network uncertainty in epidemic inferences with Approximate Bayesian Computation.Applied network science · 2025Article
- Flexible Bayesian inference on partially observed epidemics.Journal of complex networks · 2024Article
- Framework for converting mechanistic network models to probabilistic models.Journal of complex networks · 2023Article
- Mask Adherence and the Relationship Between Masking and Weather-Related Metrics.Journal of community health · 2023Article
- Assessing individual risk and the latent transmission of COVID-19 in a population with an interaction-driven temporal model.Scientific reports · 2023Article
- Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses.Frontiers in digital health · 2023Article
- Monitoring and responding to emerging infectious diseases in a university setting: A case study using COVID-19.PloS one · 2023Article
- Assessment of the Effectiveness of Omicron Transmission Mitigation Strategies for European Universities Using an Agent-Based Network Model.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022Article
- Effect of a two-dose vs three-dose vaccine strategy in residential colleges using an empirical proximity network.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
- Quantifying the dynamic transmission of COVID-19 asymptomatic and symptomatic infections: Evidence from four Chinese regions.Frontiers in public health · 2022Article
- SARS-CoV-2 infection in UK university students: lessons from September-December 2020 and modelling insights for future student return.Royal Society open science · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Objectives Universities have turned to SARS-CoV-2 models to examine campus reopening strategies. While these studies have explored a variety of modeling techniques, none have used empirical data. Methods In this study, we use an empirical proximity network of college freshmen obtained using smartphone Bluetooth to simulate the spread of the virus. We investigate the role of immunization, testing, isolation, mask wearing, and social distancing in the presence of implementation challenges and imperfect compliance. Results We show that frequent testing could drastically reduce the spread of the virus if levels of immunity are low, but its effects are limited if immunity is more ubiquitous. Furthermore, moderate levels of mask wearing and social distancing could lead to additional reductions in cumulative incidence, but their benefit decreases rapidly as immunity and testing frequency increase. However, if immunity from vaccination is imperfect or declines over time, scenarios not studied here, frequent testing and other interventions may play more central roles. Conclusions Our findings suggest that although regular testing and isolation are powerful tools, they have limited benefit if immunity is high or other interventions are widely adopted. If universities can attain even moderate levels of vaccination, masking, and social distancing, they may be able to relax the frequency of testing to once every four weeks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.