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Prioritizing vaccination based on analysis of community networks
Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision make...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9717573/ https://www.ncbi.nlm.nih.gov/pubmed/36505040 http://dx.doi.org/10.1007/s41109-022-00522-7 |
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author | Klise, Katherine Beyeler, Walt Acquesta, Erin Thelen, Haedi Makvandi, Monear Finley, Patrick |
author_facet | Klise, Katherine Beyeler, Walt Acquesta, Erin Thelen, Haedi Makvandi, Monear Finley, Patrick |
author_sort | Klise, Katherine |
collection | PubMed |
description | Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision makers to manage new variants, plan for future booster shots, or stage mass vaccinations. This paper explores the impact of vaccine prioritization strategies using networks that represent communities with different demographics and connectivity. The impact of vaccination is compared to non-medical intervention to reduce transmission. Several sources of uncertainty are considered, including vaccine willingness and mask effectiveness. This paper finds that while prioritization strategies can have a large impact on reducing deaths and peak hospitalization, selecting the best strategy depends on community characteristics and the desired objective. Additionally, in some cases random vaccination performs as well as more targeted prioritization strategies. Understanding these trade-offs is important when planning vaccine distribution. |
format | Online Article Text |
id | pubmed-9717573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-97175732022-12-05 Prioritizing vaccination based on analysis of community networks Klise, Katherine Beyeler, Walt Acquesta, Erin Thelen, Haedi Makvandi, Monear Finley, Patrick Appl Netw Sci Research Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision makers to manage new variants, plan for future booster shots, or stage mass vaccinations. This paper explores the impact of vaccine prioritization strategies using networks that represent communities with different demographics and connectivity. The impact of vaccination is compared to non-medical intervention to reduce transmission. Several sources of uncertainty are considered, including vaccine willingness and mask effectiveness. This paper finds that while prioritization strategies can have a large impact on reducing deaths and peak hospitalization, selecting the best strategy depends on community characteristics and the desired objective. Additionally, in some cases random vaccination performs as well as more targeted prioritization strategies. Understanding these trade-offs is important when planning vaccine distribution. Springer International Publishing 2022-12-02 2022 /pmc/articles/PMC9717573/ /pubmed/36505040 http://dx.doi.org/10.1007/s41109-022-00522-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Klise, Katherine Beyeler, Walt Acquesta, Erin Thelen, Haedi Makvandi, Monear Finley, Patrick Prioritizing vaccination based on analysis of community networks |
title | Prioritizing vaccination based on analysis of community networks |
title_full | Prioritizing vaccination based on analysis of community networks |
title_fullStr | Prioritizing vaccination based on analysis of community networks |
title_full_unstemmed | Prioritizing vaccination based on analysis of community networks |
title_short | Prioritizing vaccination based on analysis of community networks |
title_sort | prioritizing vaccination based on analysis of community networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9717573/ https://www.ncbi.nlm.nih.gov/pubmed/36505040 http://dx.doi.org/10.1007/s41109-022-00522-7 |
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