Cargando…

Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons

PURPOSE: In this work, the authors present some of the key results found during early efforts to model the COVID-19 outbreak inside a UK prison. In particular, this study describes outputs from an idealised disease model that simulates the dynamics of a COVID-19 outbreak in a prison setting when var...

Descripción completa

Detalles Bibliográficos
Autores principales: Bays, Declan, Williams, Hannah, Pellis, Lorenzo, Curran-Sebastian, Jacob, O'Mara, Oscar, Team, PHE Joint Modelling, Finnie, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Emerald Publishing Limited 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753626/
https://www.ncbi.nlm.nih.gov/pubmed/34339114
http://dx.doi.org/10.1108/IJPH-09-2020-0075
_version_ 1784632130647621632
author Bays, Declan
Williams, Hannah
Pellis, Lorenzo
Curran-Sebastian, Jacob
O'Mara, Oscar
Team, PHE Joint Modelling
Finnie, Thomas
author_facet Bays, Declan
Williams, Hannah
Pellis, Lorenzo
Curran-Sebastian, Jacob
O'Mara, Oscar
Team, PHE Joint Modelling
Finnie, Thomas
author_sort Bays, Declan
collection PubMed
description PURPOSE: In this work, the authors present some of the key results found during early efforts to model the COVID-19 outbreak inside a UK prison. In particular, this study describes outputs from an idealised disease model that simulates the dynamics of a COVID-19 outbreak in a prison setting when varying levels of social interventions are in place, and a Monte Carlo-based model that assesses the reduction in risk of case importation, resulting from a process that requires incoming prisoners to undergo a period of self-isolation prior to admission into the general prison population. DESIGN/METHODOLOGY/APPROACH: Prisons, typically containing large populations confined in a small space with high degrees of mixing, have long been known to be especially susceptible to disease outbreaks. In an attempt to meet rising pressures from the emerging COVID-19 situation in early 2020, modellers for Public Health England’s Joint Modelling Cell were asked to produce some rapid response work that sought to inform the approaches that Her Majesty’s Prison and Probation Service (HMPPS) might take to reduce the risk of case importation and sustained transmission in prison environments. FINDINGS: Key results show that deploying social interventions has the potential to considerably reduce the total number of infections, while such actions could also reduce the probability that an initial infection will propagate into a prison-wide outbreak. For example, modelling showed that a 50% reduction in the risk of transmission (compared to an unmitigated outbreak) could deliver a 98% decrease in total number of cases, while this reduction could also result in 86.8% of outbreaks subsiding before more than five persons have become infected. Furthermore, this study also found that requiring new arrivals to self-isolate for 10 and 14 days prior to admission could detect up to 98% and 99% of incoming infections, respectively. RESEARCH LIMITATIONS/IMPLICATIONS: In this paper we have presented models which allow for the studying of COVID-19 in a prison scenario, while also allowing for the assessment of proposed social interventions. By publishing these works, the authors hope these methods might aid in the management of prisoners across additional scenarios and even during subsequent disease outbreaks. Such methods as described may also be readily applied use in other closed community settings. ORIGINALITY/VALUE: These works went towards informing HMPPS on the impacts that the described strategies might have during COVID-19 outbreaks inside UK prisons. The works described herein are readily amendable to the study of a range of addition outbreak scenarios. There is also room for these methods to be further developed and built upon which the timeliness of the original project did not permit.
format Online
Article
Text
id pubmed-8753626
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Emerald Publishing Limited
record_format MEDLINE/PubMed
spelling pubmed-87536262022-01-26 Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons Bays, Declan Williams, Hannah Pellis, Lorenzo Curran-Sebastian, Jacob O'Mara, Oscar Team, PHE Joint Modelling Finnie, Thomas Int J Prison Health Research Paper PURPOSE: In this work, the authors present some of the key results found during early efforts to model the COVID-19 outbreak inside a UK prison. In particular, this study describes outputs from an idealised disease model that simulates the dynamics of a COVID-19 outbreak in a prison setting when varying levels of social interventions are in place, and a Monte Carlo-based model that assesses the reduction in risk of case importation, resulting from a process that requires incoming prisoners to undergo a period of self-isolation prior to admission into the general prison population. DESIGN/METHODOLOGY/APPROACH: Prisons, typically containing large populations confined in a small space with high degrees of mixing, have long been known to be especially susceptible to disease outbreaks. In an attempt to meet rising pressures from the emerging COVID-19 situation in early 2020, modellers for Public Health England’s Joint Modelling Cell were asked to produce some rapid response work that sought to inform the approaches that Her Majesty’s Prison and Probation Service (HMPPS) might take to reduce the risk of case importation and sustained transmission in prison environments. FINDINGS: Key results show that deploying social interventions has the potential to considerably reduce the total number of infections, while such actions could also reduce the probability that an initial infection will propagate into a prison-wide outbreak. For example, modelling showed that a 50% reduction in the risk of transmission (compared to an unmitigated outbreak) could deliver a 98% decrease in total number of cases, while this reduction could also result in 86.8% of outbreaks subsiding before more than five persons have become infected. Furthermore, this study also found that requiring new arrivals to self-isolate for 10 and 14 days prior to admission could detect up to 98% and 99% of incoming infections, respectively. RESEARCH LIMITATIONS/IMPLICATIONS: In this paper we have presented models which allow for the studying of COVID-19 in a prison scenario, while also allowing for the assessment of proposed social interventions. By publishing these works, the authors hope these methods might aid in the management of prisoners across additional scenarios and even during subsequent disease outbreaks. Such methods as described may also be readily applied use in other closed community settings. ORIGINALITY/VALUE: These works went towards informing HMPPS on the impacts that the described strategies might have during COVID-19 outbreaks inside UK prisons. The works described herein are readily amendable to the study of a range of addition outbreak scenarios. There is also room for these methods to be further developed and built upon which the timeliness of the original project did not permit. Emerald Publishing Limited 2021-08-03 2021 /pmc/articles/PMC8753626/ /pubmed/34339114 http://dx.doi.org/10.1108/IJPH-09-2020-0075 Text en © Declan Bays, Hannah Williams, Lorenzo Pellis, Jacob Curran-Sebastian, Oscar O'Mara, PHE Joint Modelling Team and Thomas Finnie. https://creativecommons.org/licenses/by/4.0/Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at https://creativecommons.org/licenses/by/4.0/
spellingShingle Research Paper
Bays, Declan
Williams, Hannah
Pellis, Lorenzo
Curran-Sebastian, Jacob
O'Mara, Oscar
Team, PHE Joint Modelling
Finnie, Thomas
Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title_full Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title_fullStr Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title_full_unstemmed Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title_short Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons
title_sort insights gained from early modelling of covid-19 to inform the management of outbreaks in uk prisons
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753626/
https://www.ncbi.nlm.nih.gov/pubmed/34339114
http://dx.doi.org/10.1108/IJPH-09-2020-0075
work_keys_str_mv AT baysdeclan insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT williamshannah insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT pellislorenzo insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT curransebastianjacob insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT omaraoscar insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT teamphejointmodelling insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons
AT finniethomas insightsgainedfromearlymodellingofcovid19toinformthemanagementofoutbreaksinukprisons