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Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses
This study aims to inform SARS-CoV-2 vaccine development/licensure/decision-making/implementation, using mathematical modeling, by determining key preferred vaccine product characteristics and associated population-level impacts of a vaccine eliciting long-term protection. A prophylactic vaccine wit...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712303/ https://www.ncbi.nlm.nih.gov/pubmed/33182403 http://dx.doi.org/10.3390/vaccines8040668 |
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author | Makhoul, Monia Ayoub, Houssein H. Chemaitelly, Hiam Seedat, Shaheen Mumtaz, Ghina R. Al-Omari, Sarah Abu-Raddad, Laith J. |
author_facet | Makhoul, Monia Ayoub, Houssein H. Chemaitelly, Hiam Seedat, Shaheen Mumtaz, Ghina R. Al-Omari, Sarah Abu-Raddad, Laith J. |
author_sort | Makhoul, Monia |
collection | PubMed |
description | This study aims to inform SARS-CoV-2 vaccine development/licensure/decision-making/implementation, using mathematical modeling, by determining key preferred vaccine product characteristics and associated population-level impacts of a vaccine eliciting long-term protection. A prophylactic vaccine with efficacy against acquisition (VE(S)) ≥70% can eliminate the infection. A vaccine with VE(S) <70% may still control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, if it is supplemented with <20% reduction in contact rate, or if it is complemented with herd-immunity. At VE(S) of 50%, the number of vaccinated persons needed to avert one infection is 2.4, and the number is 25.5 to avert one severe disease case, 33.2 to avert one critical disease case, and 65.1 to avert one death. The probability of a major outbreak is zero at VE(S) ≥70% regardless of the number of virus introductions. However, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact. In addition to the reduction in infection acquisition, developers should assess the natural history and disease progression outcomes when evaluating vaccine impact. |
format | Online Article Text |
id | pubmed-7712303 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77123032020-12-04 Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses Makhoul, Monia Ayoub, Houssein H. Chemaitelly, Hiam Seedat, Shaheen Mumtaz, Ghina R. Al-Omari, Sarah Abu-Raddad, Laith J. Vaccines (Basel) Article This study aims to inform SARS-CoV-2 vaccine development/licensure/decision-making/implementation, using mathematical modeling, by determining key preferred vaccine product characteristics and associated population-level impacts of a vaccine eliciting long-term protection. A prophylactic vaccine with efficacy against acquisition (VE(S)) ≥70% can eliminate the infection. A vaccine with VE(S) <70% may still control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, if it is supplemented with <20% reduction in contact rate, or if it is complemented with herd-immunity. At VE(S) of 50%, the number of vaccinated persons needed to avert one infection is 2.4, and the number is 25.5 to avert one severe disease case, 33.2 to avert one critical disease case, and 65.1 to avert one death. The probability of a major outbreak is zero at VE(S) ≥70% regardless of the number of virus introductions. However, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact. In addition to the reduction in infection acquisition, developers should assess the natural history and disease progression outcomes when evaluating vaccine impact. MDPI 2020-11-09 /pmc/articles/PMC7712303/ /pubmed/33182403 http://dx.doi.org/10.3390/vaccines8040668 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Makhoul, Monia Ayoub, Houssein H. Chemaitelly, Hiam Seedat, Shaheen Mumtaz, Ghina R. Al-Omari, Sarah Abu-Raddad, Laith J. Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title | Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title_full | Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title_fullStr | Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title_full_unstemmed | Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title_short | Epidemiological Impact of SARS-CoV-2 Vaccination: Mathematical Modeling Analyses |
title_sort | epidemiological impact of sars-cov-2 vaccination: mathematical modeling analyses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712303/ https://www.ncbi.nlm.nih.gov/pubmed/33182403 http://dx.doi.org/10.3390/vaccines8040668 |
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