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Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study

BACKGROUND: Evidence from COVID-19 outbreak shows that individuals with specific chronic diseases are at higher risk of severe prognosis after infection. Public health authorities are developing vaccination programmes with priorities that minimize the risk of mortality and severe events in individua...

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Autores principales: Russo, Antonio Giampiero, Decarli, Adriano, Valsecchi, Maria Grazia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997303/
https://www.ncbi.nlm.nih.gov/pubmed/33824037
http://dx.doi.org/10.1016/j.vaccine.2021.03.076
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author Russo, Antonio Giampiero
Decarli, Adriano
Valsecchi, Maria Grazia
author_facet Russo, Antonio Giampiero
Decarli, Adriano
Valsecchi, Maria Grazia
author_sort Russo, Antonio Giampiero
collection PubMed
description BACKGROUND: Evidence from COVID-19 outbreak shows that individuals with specific chronic diseases are at higher risk of severe prognosis after infection. Public health authorities are developing vaccination programmes with priorities that minimize the risk of mortality and severe events in individuals and communities. We propose an evidence-based strategy that targets the frailest subjects whose timely vaccination is likely to minimize future deaths and preserve the resilience of the health service by preventing infections. METHODS: The cohort includes 146,087 cases with COVID-19 diagnosed in 2020 in Milan (3.49 million inhabitants). Individual level data on 42 chronic diseases and vital status updated as of January 21, 2021, were available in administrative data. Analyses were performed in three sub-cohorts of age (16–64, 65–79 and 80+ years) and comorbidities affecting mortality were selected by means of LASSO cross-validated conditional logistic regression. Simplified models based on previous results identified high-risk categories worth targeting with highest priority. Results adjusted by age and gender, were reported in terms of odds ratios and 95%CI. RESULTS: The final models include as predictors of mortality (7,667 deaths, 5.2%) 10, 12, and 5 chronic diseases, respectively. The older age categories shared, as risk factors, chronic renal failure, chronic heart failure, cerebrovascular disease, Parkinson disease and psychiatric diseases. In the younger age category, predictors included neoplasm, organ transplantation and psychiatric conditions. Results were consistent with those obtained on mortality at 60 days from diagnosis (6,968 deaths). CONCLUSION: This approach defines a two-level stratification for priorities in the vaccination that can easily be applied by health authorities, eventually adapted to local results in terms of number and types of comorbidities, and rapidly updated with current data. After the early phase of vaccination, data on effectiveness and safety will give the opportunity to revise prioritization and discuss the future approach in the remaining population.
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spelling pubmed-79973032021-03-29 Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study Russo, Antonio Giampiero Decarli, Adriano Valsecchi, Maria Grazia Vaccine Article BACKGROUND: Evidence from COVID-19 outbreak shows that individuals with specific chronic diseases are at higher risk of severe prognosis after infection. Public health authorities are developing vaccination programmes with priorities that minimize the risk of mortality and severe events in individuals and communities. We propose an evidence-based strategy that targets the frailest subjects whose timely vaccination is likely to minimize future deaths and preserve the resilience of the health service by preventing infections. METHODS: The cohort includes 146,087 cases with COVID-19 diagnosed in 2020 in Milan (3.49 million inhabitants). Individual level data on 42 chronic diseases and vital status updated as of January 21, 2021, were available in administrative data. Analyses were performed in three sub-cohorts of age (16–64, 65–79 and 80+ years) and comorbidities affecting mortality were selected by means of LASSO cross-validated conditional logistic regression. Simplified models based on previous results identified high-risk categories worth targeting with highest priority. Results adjusted by age and gender, were reported in terms of odds ratios and 95%CI. RESULTS: The final models include as predictors of mortality (7,667 deaths, 5.2%) 10, 12, and 5 chronic diseases, respectively. The older age categories shared, as risk factors, chronic renal failure, chronic heart failure, cerebrovascular disease, Parkinson disease and psychiatric diseases. In the younger age category, predictors included neoplasm, organ transplantation and psychiatric conditions. Results were consistent with those obtained on mortality at 60 days from diagnosis (6,968 deaths). CONCLUSION: This approach defines a two-level stratification for priorities in the vaccination that can easily be applied by health authorities, eventually adapted to local results in terms of number and types of comorbidities, and rapidly updated with current data. After the early phase of vaccination, data on effectiveness and safety will give the opportunity to revise prioritization and discuss the future approach in the remaining population. The Authors. Published by Elsevier Ltd. 2021-04-28 2021-03-26 /pmc/articles/PMC7997303/ /pubmed/33824037 http://dx.doi.org/10.1016/j.vaccine.2021.03.076 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
Russo, Antonio Giampiero
Decarli, Adriano
Valsecchi, Maria Grazia
Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title_full Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title_fullStr Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title_full_unstemmed Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title_short Strategy to identify priority groups for COVID-19 vaccination: A population based cohort study
title_sort strategy to identify priority groups for covid-19 vaccination: a population based cohort study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997303/
https://www.ncbi.nlm.nih.gov/pubmed/33824037
http://dx.doi.org/10.1016/j.vaccine.2021.03.076
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