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Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics

BACKGROUND: Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of...

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Detalles Bibliográficos
Autores principales: Nashebi, Ramin, Sari, Murat, Kotil, Seyfullah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760027/
https://www.ncbi.nlm.nih.gov/pubmed/36540805
http://dx.doi.org/10.7717/peerj.14353
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author Nashebi, Ramin
Sari, Murat
Kotil, Seyfullah
author_facet Nashebi, Ramin
Sari, Murat
Kotil, Seyfullah
author_sort Nashebi, Ramin
collection PubMed
description BACKGROUND: Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of pandemics such as COVID-19. METHODS: To achieve this, we have developed an agent based model based on a time-dynamic graph with stochastic transmission events. The graph is constructed from a real-world social network. The edges of graph have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type COVID-19 and the delta variant have been analyzed. Our purposeful agent based model has carefully executed tens of thousands of individual-based simulations. We propose simple relationships for the trade-offs between effective reproduction number (R(e)), transmission rate, working hours, vaccination, and stay-at-home restrictions. RESULTS: We have found that the effect of a 13.6% increase in vaccination for wild-type (WT) COVID-19 is equivalent to reducing four hours of work or a one-day stay-at-home restriction. For the delta, 20.2% vaccination has the same effect. Also, since we can keep track of household and non-household infections, we observed that the change in household transmission rate does not significantly alter the R(e). Household infections are not limited by transmission rate due to the high frequency of connections. For the specifications of COVID-19, the R(e) depends on the non-household transmissions rate. CONCLUSIONS: Our findings highlight that decreasing working hours is the least effective among the non-pharmaceutical interventions. Our results suggest that policymakers decrease work-related activities as a last resort and should probably not do so when the effects are minimal, as shown. Furthermore, the enforcement of stay-at-home restrictions is moderately effective and can be used in conjunction with other measures if absolutely necessary.
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spelling pubmed-97600272022-12-19 Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics Nashebi, Ramin Sari, Murat Kotil, Seyfullah PeerJ Computational Biology BACKGROUND: Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of pandemics such as COVID-19. METHODS: To achieve this, we have developed an agent based model based on a time-dynamic graph with stochastic transmission events. The graph is constructed from a real-world social network. The edges of graph have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type COVID-19 and the delta variant have been analyzed. Our purposeful agent based model has carefully executed tens of thousands of individual-based simulations. We propose simple relationships for the trade-offs between effective reproduction number (R(e)), transmission rate, working hours, vaccination, and stay-at-home restrictions. RESULTS: We have found that the effect of a 13.6% increase in vaccination for wild-type (WT) COVID-19 is equivalent to reducing four hours of work or a one-day stay-at-home restriction. For the delta, 20.2% vaccination has the same effect. Also, since we can keep track of household and non-household infections, we observed that the change in household transmission rate does not significantly alter the R(e). Household infections are not limited by transmission rate due to the high frequency of connections. For the specifications of COVID-19, the R(e) depends on the non-household transmissions rate. CONCLUSIONS: Our findings highlight that decreasing working hours is the least effective among the non-pharmaceutical interventions. Our results suggest that policymakers decrease work-related activities as a last resort and should probably not do so when the effects are minimal, as shown. Furthermore, the enforcement of stay-at-home restrictions is moderately effective and can be used in conjunction with other measures if absolutely necessary. PeerJ Inc. 2022-12-15 /pmc/articles/PMC9760027/ /pubmed/36540805 http://dx.doi.org/10.7717/peerj.14353 Text en ©2022 Nashebi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Computational Biology
Nashebi, Ramin
Sari, Murat
Kotil, Seyfullah
Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title_full Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title_fullStr Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title_full_unstemmed Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title_short Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
title_sort using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on covid-19 dynamics
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760027/
https://www.ncbi.nlm.nih.gov/pubmed/36540805
http://dx.doi.org/10.7717/peerj.14353
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