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Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study
BACKGROUND: The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions. METHODS: We used an age-structured, expanded SEIR model wi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834611/ https://www.ncbi.nlm.nih.gov/pubmed/33388436 http://dx.doi.org/10.1016/j.ijid.2020.12.075 |
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author | Foy, Brody H. Wahl, Brian Mehta, Kayur Shet, Anita Menon, Gautam I. Britto, Carl |
author_facet | Foy, Brody H. Wahl, Brian Mehta, Kayur Shet, Anita Menon, Gautam I. Britto, Carl |
author_sort | Foy, Brody H. |
collection | PubMed |
description | BACKGROUND: The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions. METHODS: We used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations. RESULTS: Prioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination. CONCLUSIONS: Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals. |
format | Online Article Text |
id | pubmed-7834611 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78346112021-01-26 Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study Foy, Brody H. Wahl, Brian Mehta, Kayur Shet, Anita Menon, Gautam I. Britto, Carl Int J Infect Dis Article BACKGROUND: The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions. METHODS: We used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations. RESULTS: Prioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination. CONCLUSIONS: Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals. The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2021-02 2020-12-31 /pmc/articles/PMC7834611/ /pubmed/33388436 http://dx.doi.org/10.1016/j.ijid.2020.12.075 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Foy, Brody H. Wahl, Brian Mehta, Kayur Shet, Anita Menon, Gautam I. Britto, Carl Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title | Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title_full | Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title_fullStr | Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title_full_unstemmed | Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title_short | Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study |
title_sort | comparing covid-19 vaccine allocation strategies in india: a mathematical modelling study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834611/ https://www.ncbi.nlm.nih.gov/pubmed/33388436 http://dx.doi.org/10.1016/j.ijid.2020.12.075 |
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