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COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies
BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922400/ https://www.ncbi.nlm.nih.gov/pubmed/35292054 http://dx.doi.org/10.1186/s12985-022-01771-9 |
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author | Li, Miaolei Zu, Jian Zhang, Yue Ma, Le Shen, Mingwang Li, Zongfang Ji, Fanpu |
author_facet | Li, Miaolei Zu, Jian Zhang, Yue Ma, Le Shen, Mingwang Li, Zongfang Ji, Fanpu |
author_sort | Li, Miaolei |
collection | PubMed |
description | BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. OBJECTIVE: Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. METHODS: We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. RESULTS: Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75–100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65–100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0–17 and 75–100 age groups as of June 1, 2021, then the allocation of 80% to the 0–17 age group and 20% to the 75–100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. CONCLUSIONS: The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12985-022-01771-9. |
format | Online Article Text |
id | pubmed-8922400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89224002022-03-15 COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies Li, Miaolei Zu, Jian Zhang, Yue Ma, Le Shen, Mingwang Li, Zongfang Ji, Fanpu Virol J Research BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. OBJECTIVE: Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. METHODS: We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. RESULTS: Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75–100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65–100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0–17 and 75–100 age groups as of June 1, 2021, then the allocation of 80% to the 0–17 age group and 20% to the 75–100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. CONCLUSIONS: The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12985-022-01771-9. BioMed Central 2022-03-15 /pmc/articles/PMC8922400/ /pubmed/35292054 http://dx.doi.org/10.1186/s12985-022-01771-9 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Li, Miaolei Zu, Jian Zhang, Yue Ma, Le Shen, Mingwang Li, Zongfang Ji, Fanpu COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title | COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title_full | COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title_fullStr | COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title_full_unstemmed | COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title_short | COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
title_sort | covid-19 epidemic in new york city: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922400/ https://www.ncbi.nlm.nih.gov/pubmed/35292054 http://dx.doi.org/10.1186/s12985-022-01771-9 |
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