Controlling COVID-19 outbreaks in the correctional setting: A mathematical modelling study
Correctional centres (termed here 'prisons') are at high risk of COVID-19 and have featured major outbreaks worldwide. Inevitable close contacts, frequent inmate movements, and a disproportionate burden of co-morbidities mean these environments need to be prioritised in any public health r...
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description | Correctional centres (termed here 'prisons') are at high risk of COVID-19 and have featured major outbreaks worldwide. Inevitable close contacts, frequent inmate movements, and a disproportionate burden of co-morbidities mean these environments need to be prioritised in any public health response to respiratory pathogens such as COVID-19. We developed an individual-based SARS-CoV-2 transmission model for the prison system in New South Wales, Australia - incorporating all 33 correctional centres, 13,458 inmates, 578 healthcare and 6,909 custodial staff. Potential COVID-19 disease outbreaks were assessed under various mitigation strategies, including quarantine on entry, isolation of cases, rapid antigen testing of staff, as well as immunisation.Without control measures, the model projected a peak of 472 new infections daily by day 35 across the prison system, with all inmates infected by day 120. The most effective individual mitigation strategies were high immunisation coverage and prompt lockdown of centres with infected inmates which reduced outbreak size by 62-73%. Other than immunisation, the combination of quarantine of inmates at entry, isolation of proven or suspected cases, and widespread use of personal protective equipment by staff and inmates was the most effective strategy. High immunisation coverage mitigates the spread of COVID-19 within and between correctional settings but is insufficient alone. Maintaining quarantine and isolation, along with high immunisation levels, will allow correctional systems to function with a low risk of outbreaks. These results have informed public health policy for respiratory pathogens in Australian correctional systems. |
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Inevitable close contacts, frequent inmate movements, and a disproportionate burden of co-morbidities mean these environments need to be prioritised in any public health response to respiratory pathogens such as COVID-19. We developed an individual-based SARS-CoV-2 transmission model for the prison system in New South Wales, Australia - incorporating all 33 correctional centres, 13,458 inmates, 578 healthcare and 6,909 custodial staff. Potential COVID-19 disease outbreaks were assessed under various mitigation strategies, including quarantine on entry, isolation of cases, rapid antigen testing of staff, as well as immunisation.Without control measures, the model projected a peak of 472 new infections daily by day 35 across the prison system, with all inmates infected by day 120. The most effective individual mitigation strategies were high immunisation coverage and prompt lockdown of centres with infected inmates which reduced outbreak size by 62-73%. Other than immunisation, the combination of quarantine of inmates at entry, isolation of proven or suspected cases, and widespread use of personal protective equipment by staff and inmates was the most effective strategy. High immunisation coverage mitigates the spread of COVID-19 within and between correctional settings but is insufficient alone. Maintaining quarantine and isolation, along with high immunisation levels, will allow correctional systems to function with a low risk of outbreaks. These results have informed public health policy for respiratory pathogens in Australian correctional systems.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0303062</identifier><identifier>PMID: 38758971</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Australia ; Biology and Life Sciences ; Correctional institutions ; Correctional personnel ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - prevention & control ; COVID-19 - transmission ; Disease Outbreaks - prevention & control ; Disease transmission ; Engineering and Technology ; Epidemics ; Health policy ; Humans ; Immunization ; Imprisonment ; Infections ; Mathematical models ; Medical research ; Medicine and Health Sciences ; Medicine, Experimental ; Models, Theoretical ; New South Wales - epidemiology ; Outbreaks ; Pandemics ; Pathogens ; Personal Protective Equipment ; Prison overcrowding ; Prisoners ; Prisons ; Prisons - statistics & numerical data ; Probability ; Protective equipment ; Public health ; Quarantine ; Respiratory diseases ; SARS-CoV-2 - isolation & purification ; Severe acute respiratory syndrome coronavirus 2 ; Simulation ; Social Sciences ; Viral diseases</subject><ispartof>PloS one, 2024-05, Vol.19 (5), p.e0303062-e0303062</ispartof><rights>Copyright: © 2024 Bretaña et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Bretaña et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Bretaña et al 2024 Bretaña et al</rights><rights>2024 Bretaña et al. 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Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c642t-8c9d08152b8fb334761e11adfd7b1f37bebc8b1ba73a92d64b44d4ac97ae1c003</cites><orcidid>0000-0002-7517-0413 ; 0000-0003-2829-6694 ; 0000-0003-4743-348X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11101071/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11101071/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38758971$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bretaña, Neil Arvin</creatorcontrib><creatorcontrib>Kwon, Jisoo A</creatorcontrib><creatorcontrib>Grant, Luke</creatorcontrib><creatorcontrib>Galouzis, Jennifer</creatorcontrib><creatorcontrib>McGrath, Colette</creatorcontrib><creatorcontrib>Hoey, Wendy</creatorcontrib><creatorcontrib>Blogg, James</creatorcontrib><creatorcontrib>Lloyd, Andrew R</creatorcontrib><creatorcontrib>Gray, Richard T</creatorcontrib><title>Controlling COVID-19 outbreaks in the correctional setting: A mathematical modelling study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Correctional centres (termed here 'prisons') are at high risk of COVID-19 and have featured major outbreaks worldwide. 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These results have informed public health policy for respiratory pathogens in Australian correctional systems.</description><subject>Australia</subject><subject>Biology and Life Sciences</subject><subject>Correctional institutions</subject><subject>Correctional personnel</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - prevention & control</subject><subject>COVID-19 - transmission</subject><subject>Disease Outbreaks - prevention & control</subject><subject>Disease transmission</subject><subject>Engineering and Technology</subject><subject>Epidemics</subject><subject>Health policy</subject><subject>Humans</subject><subject>Immunization</subject><subject>Imprisonment</subject><subject>Infections</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Medicine, Experimental</subject><subject>Models, Theoretical</subject><subject>New South Wales - epidemiology</subject><subject>Outbreaks</subject><subject>Pandemics</subject><subject>Pathogens</subject><subject>Personal Protective Equipment</subject><subject>Prison overcrowding</subject><subject>Prisoners</subject><subject>Prisons</subject><subject>Prisons - 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subjects | Australia Biology and Life Sciences Correctional institutions Correctional personnel COVID-19 COVID-19 - epidemiology COVID-19 - prevention & control COVID-19 - transmission Disease Outbreaks - prevention & control Disease transmission Engineering and Technology Epidemics Health policy Humans Immunization Imprisonment Infections Mathematical models Medical research Medicine and Health Sciences Medicine, Experimental Models, Theoretical New South Wales - epidemiology Outbreaks Pandemics Pathogens Personal Protective Equipment Prison overcrowding Prisoners Prisons Prisons - statistics & numerical data Probability Protective equipment Public health Quarantine Respiratory diseases SARS-CoV-2 - isolation & purification Severe acute respiratory syndrome coronavirus 2 Simulation Social Sciences Viral diseases |
title | Controlling COVID-19 outbreaks in the correctional setting: A mathematical modelling study |
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