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Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study

Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled f...

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Autores principales: Gozzi, Nicolò, Chinazzi, Matteo, Dean, Natalie E., Longini, Ira M., Halloran, M. Elizabeth, Perra, Nicola, Vespignani, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681050/
https://www.ncbi.nlm.nih.gov/pubmed/36415459
http://dx.doi.org/10.1101/2022.11.18.22282514
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author Gozzi, Nicolò
Chinazzi, Matteo
Dean, Natalie E.
Longini, Ira M.
Halloran, M. Elizabeth
Perra, Nicola
Vespignani, Alessandro
author_facet Gozzi, Nicolò
Chinazzi, Matteo
Dean, Natalie E.
Longini, Ira M.
Halloran, M. Elizabeth
Perra, Nicola
Vespignani, Alessandro
author_sort Gozzi, Nicolò
collection PubMed
description Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled from all WHO regions. We focus on the first critical months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that, in this high vaccine availability scenario, more than 50% of deaths (min-max range: [56% − 99%]) that occurred in the analyzed countries could have been averted. We further consider a scenario where LMIC had similarly early access to vaccine doses as high income countries; even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [7% − 73%]) could have been averted. In the absence of equitable allocation, the model suggests that considerable additional non-pharmaceutical interventions would have been required to offset the lack of vaccines (min-max range: [15% − 75%]). Overall, our results quantify the negative impacts of vaccines inequities and call for amplified global efforts to provide better access to vaccine programs in low and lower middle income countries.
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spelling pubmed-96810502022-11-23 Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study Gozzi, Nicolò Chinazzi, Matteo Dean, Natalie E. Longini, Ira M. Halloran, M. Elizabeth Perra, Nicola Vespignani, Alessandro medRxiv Article Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled from all WHO regions. We focus on the first critical months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that, in this high vaccine availability scenario, more than 50% of deaths (min-max range: [56% − 99%]) that occurred in the analyzed countries could have been averted. We further consider a scenario where LMIC had similarly early access to vaccine doses as high income countries; even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [7% − 73%]) could have been averted. In the absence of equitable allocation, the model suggests that considerable additional non-pharmaceutical interventions would have been required to offset the lack of vaccines (min-max range: [15% − 75%]). Overall, our results quantify the negative impacts of vaccines inequities and call for amplified global efforts to provide better access to vaccine programs in low and lower middle income countries. Cold Spring Harbor Laboratory 2022-11-18 /pmc/articles/PMC9681050/ /pubmed/36415459 http://dx.doi.org/10.1101/2022.11.18.22282514 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Gozzi, Nicolò
Chinazzi, Matteo
Dean, Natalie E.
Longini, Ira M.
Halloran, M. Elizabeth
Perra, Nicola
Vespignani, Alessandro
Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title_full Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title_fullStr Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title_full_unstemmed Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title_short Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study
title_sort estimating the impact of covid-19 vaccine allocation inequities: a modeling study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681050/
https://www.ncbi.nlm.nih.gov/pubmed/36415459
http://dx.doi.org/10.1101/2022.11.18.22282514
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