Logistics estimation of the COVID-19 vaccination process in Peru
Descripción del Articulo
While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination proce...
Autores: | , , , , , , |
---|---|
Formato: | artículo |
Fecha de Publicación: | 2023 |
Institución: | Universidad Ricardo Palma |
Repositorio: | Revistas - Universidad Ricardo Palma |
Lenguaje: | español |
OAI Identifier: | oai:oai.revistas.urp.edu.pe:article/5675 |
Enlace del recurso: | http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675 |
Nivel de acceso: | acceso abierto |
Materia: | COVID-19 critical time logistics estimation Peru vaccination velocity estimación logística Perú tiempo crítico vacunación velocidad |
id |
REVURP_fe82c31ff1866b827210cfacd233d2b8 |
---|---|
oai_identifier_str |
oai:oai.revistas.urp.edu.pe:article/5675 |
network_acronym_str |
REVURP |
network_name_str |
Revistas - Universidad Ricardo Palma |
repository_id_str |
|
dc.title.none.fl_str_mv |
Logistics estimation of the COVID-19 vaccination process in Peru Estimación logística del proceso de vacunación contra la COVID-19 en el Perú |
title |
Logistics estimation of the COVID-19 vaccination process in Peru |
spellingShingle |
Logistics estimation of the COVID-19 vaccination process in Peru Marín-Machuca , Olegario COVID-19 critical time logistics estimation Peru vaccination velocity COVID-19 estimación logística Perú tiempo crítico vacunación velocidad |
title_short |
Logistics estimation of the COVID-19 vaccination process in Peru |
title_full |
Logistics estimation of the COVID-19 vaccination process in Peru |
title_fullStr |
Logistics estimation of the COVID-19 vaccination process in Peru |
title_full_unstemmed |
Logistics estimation of the COVID-19 vaccination process in Peru |
title_sort |
Logistics estimation of the COVID-19 vaccination process in Peru |
dc.creator.none.fl_str_mv |
Marín-Machuca , Olegario Dávila-Solar, Luis Alberto Blas-Ramos, Walter Eduardo López-Ráez, Luz Eufemia Alvarado-Zambrano, Fredy Aníbal Alvarado-Zambrano, Ricardo Arnaldo Marín-Sánchez, Obert |
author |
Marín-Machuca , Olegario |
author_facet |
Marín-Machuca , Olegario Dávila-Solar, Luis Alberto Blas-Ramos, Walter Eduardo López-Ráez, Luz Eufemia Alvarado-Zambrano, Fredy Aníbal Alvarado-Zambrano, Ricardo Arnaldo Marín-Sánchez, Obert |
author_role |
author |
author2 |
Dávila-Solar, Luis Alberto Blas-Ramos, Walter Eduardo López-Ráez, Luz Eufemia Alvarado-Zambrano, Fredy Aníbal Alvarado-Zambrano, Ricardo Arnaldo Marín-Sánchez, Obert |
author2_role |
author author author author author author |
dc.subject.none.fl_str_mv |
COVID-19 critical time logistics estimation Peru vaccination velocity COVID-19 estimación logística Perú tiempo crítico vacunación velocidad |
topic |
COVID-19 critical time logistics estimation Peru vaccination velocity COVID-19 estimación logística Perú tiempo crítico vacunación velocidad |
description |
While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination process in Peru, to estimate the number of people vaccinated, the critical time for which the estimated rate of vaccinated people has been the highest value, and to specify the date on which the highest number of people vaccinated has occurred. The methodology was based on determining the form of dispersion of the vaccination process, this being a logistic distribution and considering that a mathematical model is a mathematical description, by means of a function of a real-world phenomenon, such as the number of people vaccinated against the COVID-19 disease. The model presented a correlation coefficient r=-0.95, the critical time (tc) was 286 days and the maximum rate of vaccinated persons 143071 persons/day, dated December thirteenth, 2022: between March second, 2021, and March ninth, 2022. The estimated number of people vaccinated against COVID-19 disease was determined by the equation N ̂=28601461/(1+89.0602×e^(-0, 0157×t) ) and the rate of change or rate of estimated persons vaccinated against COVID-19 in Peru was calculated by the equation (dN ̂)/dt=(39949527,1600×e^(-0,0157×t))/〖(1+89,0602×e^(-0,0157×t))〗^2; the correlation coefficient between the elapsed time t (days) and the number of people vaccinated (N), based on twenty-five cases, was r=-0.95, representing a "very strong correlation" between the elapsed time (t) and the number of people vaccinated (N), and the coefficient of determination indicates that 89.47 % of the variance in N is explained by t; for the vaccination process against COVID-19 in the country; concluding that the theory of Bronshtein & Semendiaev and the logistic models can be adequately applied to pandemic and epidemiological phenomena, that the critical time (tc), for the contagions was two hundred eighty-six days, reaching its maximum speed of contagion estimated at 112142 persons/day. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-29 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo evaluado por pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675 10.31381/paideia.v13i1.5675 |
url |
http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675 |
identifier_str_mv |
10.31381/paideia.v13i1.5675 |
dc.language.none.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/7784 http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/8419 |
dc.rights.none.fl_str_mv |
Derechos de autor 2023 Paideia XXI info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Derechos de autor 2023 Paideia XXI |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/html |
dc.publisher.none.fl_str_mv |
Universidad Ricardo Palma |
publisher.none.fl_str_mv |
Universidad Ricardo Palma |
dc.source.none.fl_str_mv |
Paideia XXI; Vol. 13 Núm. 1 (2023): Paideia XXI; 51-63 Paideia XXI; Vol. 13 No. 1 (2023): Paideia XXI: Advance publication; 51-63 2519-5700 2221-7770 10.31381/paideia.v13i1 reponame:Revistas - Universidad Ricardo Palma instname:Universidad Ricardo Palma instacron:URP |
instname_str |
Universidad Ricardo Palma |
instacron_str |
URP |
institution |
URP |
reponame_str |
Revistas - Universidad Ricardo Palma |
collection |
Revistas - Universidad Ricardo Palma |
repository.name.fl_str_mv |
|
repository.mail.fl_str_mv |
|
_version_ |
1789625154683273216 |
spelling |
Logistics estimation of the COVID-19 vaccination process in PeruEstimación logística del proceso de vacunación contra la COVID-19 en el Perú Marín-Machuca , Olegario Dávila-Solar, Luis Alberto Blas-Ramos, Walter Eduardo López-Ráez, Luz Eufemia Alvarado-Zambrano, Fredy Aníbal Alvarado-Zambrano, Ricardo Arnaldo Marín-Sánchez, Obert COVID-19 critical time logistics estimation Peru vaccination velocity COVID-19 estimación logística Perú tiempo crítico vacunación velocidad While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination process in Peru, to estimate the number of people vaccinated, the critical time for which the estimated rate of vaccinated people has been the highest value, and to specify the date on which the highest number of people vaccinated has occurred. The methodology was based on determining the form of dispersion of the vaccination process, this being a logistic distribution and considering that a mathematical model is a mathematical description, by means of a function of a real-world phenomenon, such as the number of people vaccinated against the COVID-19 disease. The model presented a correlation coefficient r=-0.95, the critical time (tc) was 286 days and the maximum rate of vaccinated persons 143071 persons/day, dated December thirteenth, 2022: between March second, 2021, and March ninth, 2022. The estimated number of people vaccinated against COVID-19 disease was determined by the equation N ̂=28601461/(1+89.0602×e^(-0, 0157×t) ) and the rate of change or rate of estimated persons vaccinated against COVID-19 in Peru was calculated by the equation (dN ̂)/dt=(39949527,1600×e^(-0,0157×t))/〖(1+89,0602×e^(-0,0157×t))〗^2; the correlation coefficient between the elapsed time t (days) and the number of people vaccinated (N), based on twenty-five cases, was r=-0.95, representing a "very strong correlation" between the elapsed time (t) and the number of people vaccinated (N), and the coefficient of determination indicates that 89.47 % of the variance in N is explained by t; for the vaccination process against COVID-19 in the country; concluding that the theory of Bronshtein & Semendiaev and the logistic models can be adequately applied to pandemic and epidemiological phenomena, that the critical time (tc), for the contagions was two hundred eighty-six days, reaching its maximum speed of contagion estimated at 112142 persons/day.Si bien es cierto que las vacunas generan inmunidad con alto grado de efectividad y que en el Perú se realizó cierto tiempo iniciada enfermedad COVID-19; proceso de vacunación que se desarrolló logísticamente; cuyo propósito fue obtener un modelo matemático del proceso de vacunación contra la enfermedad de la COVID-19 en el Perú, para estimar el número de personas vacunadas, el tiempo crítico para el cual la velocidad estimada de personas vacunadas ha sido la de mayor valor, y precisar la fecha en que se ha producido la mayor cantidad de personas vacunadas. La metodología se basó en determinar la forma de dispersión del proceso de vacunación, siendo esta una distribución logística y teniendo en cuenta que un modelo matemático es una descripción matemática, mediante una función de un fenómeno del mundo real, como el número de vacunados contra la enfermedad COVID-19. El modelo presentó un coeficiente de correlación , el tiempo crítico ( y la velocidad máxima de personas vacunadas , de fecha trece de diciembre del 2022; entre el dos de marzo del 2021 y el nueve de marzo del 2022. El número estimado de personas vacunadas contra la enfermedad COVID-19 fue determinado por la ecuación y la razón de cambio o velocidad de personas estimadas vacunadas contra la COVID-19 en el Perú, se calculó por la ecuación ; el coeficiente de correlación entre el tiempo transcurrido t (días) y el número de personas vacunadas ( ), basado en veinticinco casos, fue de , representando una “correlacion muy fuerte” entre el tiempo transcurrido ( ) y el número de personas vacunadas ( ), y el coeficiente de determinación indica que el 89,47 % de la variancia en es explicada por ; para el proceso de vacunación contra la COVID-19 en el país; concluyendo que la teoría de Bronshtein & Semendiaev y los modelos logísticos se pueden aplicar adecuadamente a fenómenos pandémicos y epidemiológicos, que el tiempo crítico ( ), para los contagios fue de doscientos ochenta y seis días, llegando a su velocidad máxima de contagio estimados de .Universidad Ricardo Palma2023-04-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulo evaluado por paresapplication/pdftext/htmlhttp://revistas.urp.edu.pe/index.php/Paideia/article/view/567510.31381/paideia.v13i1.5675Paideia XXI; Vol. 13 Núm. 1 (2023): Paideia XXI; 51-63Paideia XXI; Vol. 13 No. 1 (2023): Paideia XXI: Advance publication; 51-632519-57002221-777010.31381/paideia.v13i1reponame:Revistas - Universidad Ricardo Palmainstname:Universidad Ricardo Palmainstacron:URPspahttp://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/7784http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/8419Derechos de autor 2023 Paideia XXIinfo:eu-repo/semantics/openAccessoai:oai.revistas.urp.edu.pe:article/56752023-12-16T02:50:55Z |
score |
13.982926 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).