ArticleEpidemics2021
Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach.
Article in Epidemics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Agent-based modeling to estimate the impact of lockdown scenarios and events on a pandemic exemplified on SARS-CoV-2.Scientific reports · 2024Article
- Efficacy of facemasks in preventing transmission of COVID-19 in non-healthcare settings: A scoping review.Journal of infection prevention · 2024Article
- Assessing the impact of architectural and behavioral interventions for controlling indoor COVID-19 infection risk: An agent-based approach.Journal of building engineering · 2023Article
- Combined Infection Control Interventions Protect Essential Food Workers from Occupational Exposures to SARS-CoV-2 in the Agricultural Environment.Applied and environmental microbiology · 2023Article
- Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.Progress in planning · 2023Article
- The Skagit County choir COVID-19 outbreak - have we got it wrong?Public health · 2023Review
- The impact of crowd gatherings on the spread of COVID-19.Environmental research · 2022Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Risk Stratification of SARS-CoV-2 Breakthrough Infections Based on an Outbreak at a Student Festive Event.Vaccines · 2022Article
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- A Vaccination Simulator for COVID-19: Effective and Sterilizing Immunization Cases.IEEE journal of biomedical and health informatics · 2021Article
- When can we stop wearing masks? Agent-based modeling to identify when vaccine coverage makes nonpharmaceutical interventions for reducing SARS-CoV-2 infections redundant in indoor gatherings.medRxiv : the preprint server for health sciences · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Nonpharmaceutical interventions for minimizing indoor SARS-CoV-2 transmission continue to be critical tools for protecting susceptible individuals from infection, even as effective vaccines are produced and distributed globally. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission during discrete events taking place in a single room within a sub-day time frame, and used it to compare effects of four interventions on reducing secondary SARS-CoV-2 attack rates during a superspreading event by simulating a well-known case study. We found that preventing people from moving within the simulated room and efficacious mask usage appear to have the greatest effects on reducing infection risk, but multiple concurrent interventions are required to minimize the proportion of susceptible individuals infected. Social distancing had little effect on reducing transmission if individuals were randomly relocated within the room to simulate activity-related movements during the gathering. Furthermore, our results suggest that there is potential for ventilation airflow to expose susceptible people to aerosolized pathogens even if they are relatively far from infectious individuals. Maximizing the vertical aerosol removal rate is paramount to successful transmission-risk reduction when using ventilation systems as intervention tools.
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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.