COVID-19 dynamics in an Ohio prison
Incarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding communities is a crucial component of pandemic prep...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1087698/full |
| _version_ | 1797856297985507328 |
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| author | Wasiur R. KhudaBukhsh Sat Kartar Khalsa Eben Kenah Gregorz A. Rempała Joseph H. Tien |
| author_facet | Wasiur R. KhudaBukhsh Sat Kartar Khalsa Eben Kenah Gregorz A. Rempała Joseph H. Tien |
| author_sort | Wasiur R. KhudaBukhsh |
| collection | DOAJ |
| description | Incarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding communities is a crucial component of pandemic preparedness and response. Here, we use mathematical and statistical models to analyze publicly available data on the spread of SARS-CoV-2 reported by the Ohio Department of Rehabilitation and Corrections (ODRC). Results from mass testing conducted on April 16, 2020 were analyzed together with time of first reported SARS-CoV-2 infection among Marion Correctional Institution (MCI) inmates. Extremely rapid, widespread infection of MCI inmates was reported, with nearly 80% of inmates infected within 3 weeks of the first reported inmate case. The dynamical survival analysis (DSA) framework that we use allows the derivation of explicit likelihoods based on mathematical models of transmission. We find that these data are consistent with three non-exclusive possibilities: (i) a basic reproduction number >14 with a single initially infected inmate, (ii) an initial superspreading event resulting in several hundred initially infected inmates with a reproduction number of approximately three, or (iii) earlier undetected circulation of virus among inmates prior to April. All three scenarios attest to the vulnerabilities of prisoners to COVID-19, and the inability to distinguish among these possibilities highlights the need for improved infection surveillance and reporting in prisons. |
| first_indexed | 2024-04-09T20:38:11Z |
| format | Article |
| id | doaj.art-a75b3a538fa9451c97eff097cfe5ccf1 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-09T20:38:11Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-a75b3a538fa9451c97eff097cfe5ccf12023-03-30T06:55:02ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-03-011110.3389/fpubh.2023.10876981087698COVID-19 dynamics in an Ohio prisonWasiur R. KhudaBukhsh0Sat Kartar Khalsa1Eben Kenah2Gregorz A. Rempała3Joseph H. Tien4School of Mathematical Sciences, The University of Nottingham, Nottingham, United KingdomWexner Medical Center, The Ohio State University, Columbus, OH, United StatesDivision of Biostatistics, The Ohio State University, Columbus, OH, United StatesDivision of Biostatistics, Department of Mathematics, The Ohio State University, Columbus, OH, United StatesDivision of Epidemiology, Department of Mathematics, The Ohio State University, Columbus, OH, United StatesIncarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding communities is a crucial component of pandemic preparedness and response. Here, we use mathematical and statistical models to analyze publicly available data on the spread of SARS-CoV-2 reported by the Ohio Department of Rehabilitation and Corrections (ODRC). Results from mass testing conducted on April 16, 2020 were analyzed together with time of first reported SARS-CoV-2 infection among Marion Correctional Institution (MCI) inmates. Extremely rapid, widespread infection of MCI inmates was reported, with nearly 80% of inmates infected within 3 weeks of the first reported inmate case. The dynamical survival analysis (DSA) framework that we use allows the derivation of explicit likelihoods based on mathematical models of transmission. We find that these data are consistent with three non-exclusive possibilities: (i) a basic reproduction number >14 with a single initially infected inmate, (ii) an initial superspreading event resulting in several hundred initially infected inmates with a reproduction number of approximately three, or (iii) earlier undetected circulation of virus among inmates prior to April. All three scenarios attest to the vulnerabilities of prisoners to COVID-19, and the inability to distinguish among these possibilities highlights the need for improved infection surveillance and reporting in prisons.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1087698/fullSARS-CoV-2correctional facilitiesmathematical modelingmass testingreproduction number |
| spellingShingle | Wasiur R. KhudaBukhsh Sat Kartar Khalsa Eben Kenah Gregorz A. Rempała Joseph H. Tien COVID-19 dynamics in an Ohio prison Frontiers in Public Health SARS-CoV-2 correctional facilities mathematical modeling mass testing reproduction number |
| title | COVID-19 dynamics in an Ohio prison |
| title_full | COVID-19 dynamics in an Ohio prison |
| title_fullStr | COVID-19 dynamics in an Ohio prison |
| title_full_unstemmed | COVID-19 dynamics in an Ohio prison |
| title_short | COVID-19 dynamics in an Ohio prison |
| title_sort | covid 19 dynamics in an ohio prison |
| topic | SARS-CoV-2 correctional facilities mathematical modeling mass testing reproduction number |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1087698/full |
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