The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy

Detalhes bibliográficos
Autor(a) principal: Cobre, Alexandre de Fátima
Data de Publicação: 2022
Outros Autores: Stremel, Dile Pontarolo, Böger, Beatriz, Fachi, Mariana Millan, Borba , Helena Hiemisch Lobo, Tonin, Fernanda Stumpf, Pontarolo, Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/33435
Resumo: Objective. To predict when different countries will reach 70% of fully vaccinated population against COVID-19 and to assess the effects of vaccine rejection on the number of patients admitted to ICU and on rates of omicron and other SARS-Cov-2 variants infections. Methods.  Data on the ‘number of patients with COVID-19 admitted to ICU’, ‘share of people who received at least one dose of COVID-19 vaccine’ and ‘percentage of unvaccinated population (USA, Brazil, Europe, Africa, Asia) that refuses to receive the first dose of COVID-19 vaccine’ were collected from a public database from December 2020-January 2022. Time series-based models were used to predict when countries will reach 70% rate of fully vaccinated population. Results. ARIMA model was robust for predicting COVID-19 vaccination in different countries. In the USA, Brazil, the European Union and Asia 70% of the population was vaccinated against COVID-19 between September 2021-April 2022. In the Africa, the forecast is only in the beginning of 2024. The percentage of the unvaccinated population had a significant effect on the increase in ICU admissions and on the increase of omicron, alpha, delta, and gamma variant cases. Conclusion.  Although the ARIMA model showed the best performance to predict vaccination patterns, its accuracy may decrease over time especially due the vaccination rejection rate. In this scenario, strategies to improve vaccination should be implemented.
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spelling The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policyEl impacto del rechazo a la vacuna COVID-19 en el ingreso hospitalario y la propagación de variantes en todo el mundo: implicaciones para la política de saludO impacto da rejeição da vacina COVID-19 na admissão hospitalar e a disseminação das variantes pelo mundo: implicações para a política de saúdeCoronavirusVaccineARIMA modelRejectionHospitalization.CoronavírusVacinaModelo ARIMARejeiçãoHospitalização.Coronavirus VacunaModelo ARIMARechazoHospitalización.Objective. To predict when different countries will reach 70% of fully vaccinated population against COVID-19 and to assess the effects of vaccine rejection on the number of patients admitted to ICU and on rates of omicron and other SARS-Cov-2 variants infections. Methods.  Data on the ‘number of patients with COVID-19 admitted to ICU’, ‘share of people who received at least one dose of COVID-19 vaccine’ and ‘percentage of unvaccinated population (USA, Brazil, Europe, Africa, Asia) that refuses to receive the first dose of COVID-19 vaccine’ were collected from a public database from December 2020-January 2022. Time series-based models were used to predict when countries will reach 70% rate of fully vaccinated population. Results. ARIMA model was robust for predicting COVID-19 vaccination in different countries. In the USA, Brazil, the European Union and Asia 70% of the population was vaccinated against COVID-19 between September 2021-April 2022. In the Africa, the forecast is only in the beginning of 2024. The percentage of the unvaccinated population had a significant effect on the increase in ICU admissions and on the increase of omicron, alpha, delta, and gamma variant cases. Conclusion.  Although the ARIMA model showed the best performance to predict vaccination patterns, its accuracy may decrease over time especially due the vaccination rejection rate. In this scenario, strategies to improve vaccination should be implemented.Objetivo. Predecir cuándo los diferentes países alcanzarán el 70 % de la población completamente vacunada contra el COVID-19 y evaluar los efectos del rechazo de la vacuna en el número de pacientes ingresados ​​en la UCI y en las tasas de infecciones por omicron y otras variantes del SARS-Cov-2. Métodos. Datos sobre el 'número de pacientes con COVID-19 ingresados ​​en UCI', 'proporción de personas que recibieron al menos una dosis de la vacuna COVID-19' y 'porcentaje de población no vacunada (EE. UU., Brasil, Europa, África, Asia) que se niega a recibir la primera dosis de la vacuna COVID-19' se recopilaron de una base de datos pública desde diciembre de 2020 hasta enero de 2022. Se utilizaron modelos basados ​​en series temporales para predecir cuándo alcanzarán los países una tasa del 70 % de población completamente vacunada. Resultados. El modelo ARIMA fue sólido para predecir la vacunación contra la COVID-19 en diferentes países. En EE. UU., Brasil, la Unión Europea y Asia, el 70% de la población se vacunó contra el COVID-19 entre septiembre de 2021 y abril de 2022. En África, la previsión es solo a principios de 2024. El porcentaje de la población no vacunada había un efecto significativo en el aumento de las admisiones en la UCI y en el aumento de los casos variantes omicron, alfa, delta y gamma. Conclusión. Aunque el modelo ARIMA mostró el mejor rendimiento para predecir los patrones de vacunación, su precisión puede disminuir con el tiempo, especialmente debido a la tasa de rechazo a la vacunación. En este escenario, se deben implementar estrategias para mejorar la vacunación.Objetivo. Prever quando diferentes países atingirão 70% da população totalmente vacinada contra o COVID-19 e avaliar os efeitos da rejeição da vacina no número de pacientes internados na UTI e nas taxas de infecções por omicron e outras variantes do SARS-Cov-2. Métodos. Dados sobre o 'número de pacientes com COVID-19 admitidos na UTI', 'taxa de pessoas que receberam pelo menos uma dose da vacina COVID-19' e 'porcentagem da população não vacinada (EUA, Brasil, Europa, África, Ásia) que se recusa a receber a primeira dose da vacina COVID-19' foram coletados de um banco de dados público de dezembro de 2020 a janeiro de 2022. Modelos baseados em séries temporais foram usados ​​para prever quando os países atingirão a taxa de 70% da população totalmente vacinada. Resultados. O modelo ARIMA foi robusto para prever a vacinação COVID-19 em diferentes países. Nos EUA, Brasil, União Europeia e Ásia 70% da população foi vacinada contra a COVID-19 entre setembro de 2021 a abril de 2022. Na África, a previsão é apenas no início de 2024. O percentual da população não vacinada teve um efeito significativo no aumento de internações em UTI e no aumento de casos de variantes ômicron, alfa, delta e gama. Conclusão. Embora o modelo ARIMA tenha apresentado o melhor desempenho para prever os padrões de vacinação, sua acurácia pode diminuir com o tempo, principalmente devido à taxa de rejeição da vacinação. Nesse cenário, estratégias para melhorar a vacinação devem ser implementadas.Research, Society and Development2022-08-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/3343510.33448/rsd-v11i11.33435Research, Society and Development; Vol. 11 No. 11; e189111133435Research, Society and Development; Vol. 11 Núm. 11; e189111133435Research, Society and Development; v. 11 n. 11; e1891111334352525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/33435/28331Copyright (c) 2022 Alexandre de Fátima Cobre; Dile Pontarolo Stremel; Beatriz Böger; Mariana Millan Fachi; Helena Hiemisch Lobo Borba ; Fernanda Stumpf Tonin; Roberto Pontarolohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCobre, Alexandre de Fátima Stremel, Dile PontaroloBöger, Beatriz Fachi, Mariana Millan Borba , Helena Hiemisch LoboTonin, Fernanda Stumpf Pontarolo, Roberto2022-09-05T13:24:46Zoai:ojs.pkp.sfu.ca:article/33435Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:49:05.032898Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
El impacto del rechazo a la vacuna COVID-19 en el ingreso hospitalario y la propagación de variantes en todo el mundo: implicaciones para la política de salud
O impacto da rejeição da vacina COVID-19 na admissão hospitalar e a disseminação das variantes pelo mundo: implicações para a política de saúde
title The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
spellingShingle The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
Cobre, Alexandre de Fátima
Coronavirus
Vaccine
ARIMA model
Rejection
Hospitalization.
Coronavírus
Vacina
Modelo ARIMA
Rejeição
Hospitalização.
Coronavirus
Vacuna
Modelo ARIMA
Rechazo
Hospitalización.
title_short The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
title_full The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
title_fullStr The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
title_full_unstemmed The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
title_sort The impact of COVID-19 vaccine rejection on hospital admission and variants spread worldwide: implications for healthcare policy
author Cobre, Alexandre de Fátima
author_facet Cobre, Alexandre de Fátima
Stremel, Dile Pontarolo
Böger, Beatriz
Fachi, Mariana Millan
Borba , Helena Hiemisch Lobo
Tonin, Fernanda Stumpf
Pontarolo, Roberto
author_role author
author2 Stremel, Dile Pontarolo
Böger, Beatriz
Fachi, Mariana Millan
Borba , Helena Hiemisch Lobo
Tonin, Fernanda Stumpf
Pontarolo, Roberto
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Cobre, Alexandre de Fátima
Stremel, Dile Pontarolo
Böger, Beatriz
Fachi, Mariana Millan
Borba , Helena Hiemisch Lobo
Tonin, Fernanda Stumpf
Pontarolo, Roberto
dc.subject.por.fl_str_mv Coronavirus
Vaccine
ARIMA model
Rejection
Hospitalization.
Coronavírus
Vacina
Modelo ARIMA
Rejeição
Hospitalização.
Coronavirus
Vacuna
Modelo ARIMA
Rechazo
Hospitalización.
topic Coronavirus
Vaccine
ARIMA model
Rejection
Hospitalization.
Coronavírus
Vacina
Modelo ARIMA
Rejeição
Hospitalização.
Coronavirus
Vacuna
Modelo ARIMA
Rechazo
Hospitalización.
description Objective. To predict when different countries will reach 70% of fully vaccinated population against COVID-19 and to assess the effects of vaccine rejection on the number of patients admitted to ICU and on rates of omicron and other SARS-Cov-2 variants infections. Methods.  Data on the ‘number of patients with COVID-19 admitted to ICU’, ‘share of people who received at least one dose of COVID-19 vaccine’ and ‘percentage of unvaccinated population (USA, Brazil, Europe, Africa, Asia) that refuses to receive the first dose of COVID-19 vaccine’ were collected from a public database from December 2020-January 2022. Time series-based models were used to predict when countries will reach 70% rate of fully vaccinated population. Results. ARIMA model was robust for predicting COVID-19 vaccination in different countries. In the USA, Brazil, the European Union and Asia 70% of the population was vaccinated against COVID-19 between September 2021-April 2022. In the Africa, the forecast is only in the beginning of 2024. The percentage of the unvaccinated population had a significant effect on the increase in ICU admissions and on the increase of omicron, alpha, delta, and gamma variant cases. Conclusion.  Although the ARIMA model showed the best performance to predict vaccination patterns, its accuracy may decrease over time especially due the vaccination rejection rate. In this scenario, strategies to improve vaccination should be implemented.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-19
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/33435
10.33448/rsd-v11i11.33435
url https://rsdjournal.org/index.php/rsd/article/view/33435
identifier_str_mv 10.33448/rsd-v11i11.33435
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/33435/28331
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 11 No. 11; e189111133435
Research, Society and Development; Vol. 11 Núm. 11; e189111133435
Research, Society and Development; v. 11 n. 11; e189111133435
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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