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A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2
As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208574/ https://www.ncbi.nlm.nih.gov/pubmed/34133427 http://dx.doi.org/10.1371/journal.pcbi.1009058 |
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author | Hill, Edward M. Atkins, Benjamin D. Keeling, Matt J. Dyson, Louise Tildesley, Michael J. |
author_facet | Hill, Edward M. Atkins, Benjamin D. Keeling, Matt J. Dyson, Louise Tildesley, Michael J. |
author_sort | Hill, Edward M. |
collection | PubMed |
description | As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create ‘COVID-secure’ workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. |
format | Online Article Text |
id | pubmed-8208574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-82085742021-06-29 A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 Hill, Edward M. Atkins, Benjamin D. Keeling, Matt J. Dyson, Louise Tildesley, Michael J. PLoS Comput Biol Research Article As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create ‘COVID-secure’ workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. Public Library of Science 2021-06-16 /pmc/articles/PMC8208574/ /pubmed/34133427 http://dx.doi.org/10.1371/journal.pcbi.1009058 Text en © 2021 Hill 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, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hill, Edward M. Atkins, Benjamin D. Keeling, Matt J. Dyson, Louise Tildesley, Michael J. A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title_full | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title_fullStr | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title_full_unstemmed | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title_short | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 |
title_sort | network modelling approach to assess non-pharmaceutical disease controls in a worker population: an application to sars-cov-2 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208574/ https://www.ncbi.nlm.nih.gov/pubmed/34133427 http://dx.doi.org/10.1371/journal.pcbi.1009058 |
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