COVID-19 vaccine program eliminates law enforcement workforce infections: a Bayesian structural time series analysis
No. Panggil : | eja-21-0033 |
Nama Orang : | Mourtgos, Scott M. Adams, Ian T. |
Penerbitan : | [Place of publication not identified] : Taylor and Francis - Criminology and Law, 2021 |
Abstrak | COVID-19 has created tremendous operational difficulties for law enforcement agencies, with substantial portions of their staff quarantined for either exposure or infection. With the rollout of a vaccine beginning in early 2021, there is hoped for relief on the horizon. However, to date, no study has reported the vaccines effect on infection rates within the law enforcement workforce. We address that gap with a report on a single large agencys experience, using data on officer positivity rates gathered over 341 days. During the immunization period, employees accepted vaccination at over 70% uptake. Results show the vaccine eliminated new cases of COVID-19 among the agencys nearly 700 employees within weeks. As other agencies consider their vaccination programs, they should consider communicating early and often about the impact of the pandemic on operations and the efficacy of vaccination, including the results reported here. |
Entri Tambahan Nama Orang | |
001 Hak Akses (open/membership) | membership |
Kata Kunci | COVID-19; vaccination; police; Bayesian structural time series |
ISSN | |
Tahun Terbit | 2021 |
No. Induk | eja-21-0033 |
Entri Sumber Data | Taylor and Francis - Criminology and Law |
Entri Utama Nama orang | Mourtgos, Scott M.; Adams, Ian T. |
Volume, Nomor, Tahun dan Hlm. | vol. 22, no. 5, p. 1557-1565 |
Subjek Topik | |
Barcode | eja-21-0033 |
Judul Utama | COVID-19 vaccine program eliminates law enforcement workforce infections: a Bayesian structural time series analysis |
Kode Bahasa | eng |
Sumber Koleksi | Perpustakaan Nasional |
No. Panggil | No. Barkod | Ketersediaan |
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eja-21-0033 | eja-21-0033 | TERSEDIA |
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