Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries

Autores
Santoro, Adrián Gabriel; López Osornio, Alejandro; Williams, Iván; Wachs, Martín; Cejas, Cintia; Havela, Maisa; Bardach, Ariel Esteban; López, Analía; Augustovski, Federico Ariel; Pichón Riviere, Andrés; Rubinstein, Adolfo Luis
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The global impact of COVID-19 has challenged health systems across the world. This situation highlighted the need to develop policies based on scientific evidence to prepare the health systems and mitigate the pandemic. In this scenario, governments were urged to predict the impact of the measures they were implementing, how they related to the population’s behavior, and the capacity of health systems to respond to the pandemic. The overarching aim of this research was to develop a customizable and open-source tool to predict the impact of the expansion of COVID-19 on the level of preparedness of the health systems of different Latin American and the Caribbean countries, with two main objectives. Firstly, to estimate the transmission dynamics of COVID-19 and the preparedness and response capacity of health systems in those countries, based on different scenarios and public policies implemented to control, mitigate, or suppress the spread of the epidemic. Secondly, to facilitate policy makers’ decisions by allowing the model to adjust its parameters according to the specific pandemic trajectory and policy context. How many infections and deaths are estimated per day?; When are the peaks of cases and deaths expected, according to the different scenarios?; Which occupancy rate will ICU services have along the epidemiological curve?; When is the optimal time increase restrictions in order to prevent saturation of ICU beds?, are some of the key questions that the model can respond, and is publicly accessible through the following link: http://shinyapps.iecs.org.ar/modelo-covid19/. This open-access and open code tool is based on a SEIR model (Susceptible, Exposed, Infected and Recovered). Using a deterministic epidemiological model, it allows to frame potential scenarios for long periods, providing valuable information on the dynamics of transmission and how it could impact on health systems through multiple customized configurations adapted to specific characteristics of each country.
Fil: Santoro, Adrián Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: López Osornio, Alejandro. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Williams, Iván. Universidad de Buenos Aires. Facultad de Ciencias Económicas; Argentina
Fil: Wachs, Martín. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Cejas, Cintia. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Havela, Maisa. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: López, Analía. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: Pichón Riviere, Andrés. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Rubinstein, Adolfo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Materia
COVID-19
PANDEMICS
PUBLIC POLICY
HEALTH CARE POLICY
EPIDEMIOLOGY
INTENSIVE CARE UNITS
CARIBBEAN
PUBLIC AND OCCUPATIONAL HEALTH
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/215334
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/215334
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countriesSantoro, Adrián GabrielLópez Osornio, AlejandroWilliams, IvánWachs, MartínCejas, CintiaHavela, MaisaBardach, Ariel EstebanLópez, AnalíaAugustovski, Federico ArielPichón Riviere, AndrésRubinstein, Adolfo LuisCOVID-19PANDEMICSPUBLIC POLICYHEALTH CARE POLICYEPIDEMIOLOGYINTENSIVE CARE UNITSCARIBBEANPUBLIC AND OCCUPATIONAL HEALTHhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3The global impact of COVID-19 has challenged health systems across the world. This situation highlighted the need to develop policies based on scientific evidence to prepare the health systems and mitigate the pandemic. In this scenario, governments were urged to predict the impact of the measures they were implementing, how they related to the population’s behavior, and the capacity of health systems to respond to the pandemic. The overarching aim of this research was to develop a customizable and open-source tool to predict the impact of the expansion of COVID-19 on the level of preparedness of the health systems of different Latin American and the Caribbean countries, with two main objectives. Firstly, to estimate the transmission dynamics of COVID-19 and the preparedness and response capacity of health systems in those countries, based on different scenarios and public policies implemented to control, mitigate, or suppress the spread of the epidemic. Secondly, to facilitate policy makers’ decisions by allowing the model to adjust its parameters according to the specific pandemic trajectory and policy context. How many infections and deaths are estimated per day?; When are the peaks of cases and deaths expected, according to the different scenarios?; Which occupancy rate will ICU services have along the epidemiological curve?; When is the optimal time increase restrictions in order to prevent saturation of ICU beds?, are some of the key questions that the model can respond, and is publicly accessible through the following link: http://shinyapps.iecs.org.ar/modelo-covid19/. This open-access and open code tool is based on a SEIR model (Susceptible, Exposed, Infected and Recovered). Using a deterministic epidemiological model, it allows to frame potential scenarios for long periods, providing valuable information on the dynamics of transmission and how it could impact on health systems through multiple customized configurations adapted to specific characteristics of each country.Fil: Santoro, Adrián Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: López Osornio, Alejandro. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Williams, Iván. Universidad de Buenos Aires. Facultad de Ciencias Económicas; ArgentinaFil: Wachs, Martín. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Cejas, Cintia. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Havela, Maisa. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: López, Analía. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Pichón Riviere, Andrés. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Rubinstein, Adolfo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaPublic Library of Science2022-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/215334Santoro, Adrián Gabriel; López Osornio, Alejandro; Williams, Iván; Wachs, Martín; Cejas, Cintia; et al.; Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries; Public Library of Science; PLOS Global Public Health; 2; 3; 3-2022; 1-132767-3375CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pgph.0000186info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pgph.0000186info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:52Zoai:ri.conicet.gov.ar:11336/215334instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:38:52.905CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
title Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
spellingShingle Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
Santoro, Adrián Gabriel
COVID-19
PANDEMICS
PUBLIC POLICY
HEALTH CARE POLICY
EPIDEMIOLOGY
INTENSIVE CARE UNITS
CARIBBEAN
PUBLIC AND OCCUPATIONAL HEALTH
title_short Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
title_full Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
title_fullStr Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
title_full_unstemmed Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
title_sort Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries
dc.creator.none.fl_str_mv Santoro, Adrián Gabriel
López Osornio, Alejandro
Williams, Iván
Wachs, Martín
Cejas, Cintia
Havela, Maisa
Bardach, Ariel Esteban
López, Analía
Augustovski, Federico Ariel
Pichón Riviere, Andrés
Rubinstein, Adolfo Luis
author Santoro, Adrián Gabriel
author_facet Santoro, Adrián Gabriel
López Osornio, Alejandro
Williams, Iván
Wachs, Martín
Cejas, Cintia
Havela, Maisa
Bardach, Ariel Esteban
López, Analía
Augustovski, Federico Ariel
Pichón Riviere, Andrés
Rubinstein, Adolfo Luis
author_role author
author2 López Osornio, Alejandro
Williams, Iván
Wachs, Martín
Cejas, Cintia
Havela, Maisa
Bardach, Ariel Esteban
López, Analía
Augustovski, Federico Ariel
Pichón Riviere, Andrés
Rubinstein, Adolfo Luis
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv COVID-19
PANDEMICS
PUBLIC POLICY
HEALTH CARE POLICY
EPIDEMIOLOGY
INTENSIVE CARE UNITS
CARIBBEAN
PUBLIC AND OCCUPATIONAL HEALTH
topic COVID-19
PANDEMICS
PUBLIC POLICY
HEALTH CARE POLICY
EPIDEMIOLOGY
INTENSIVE CARE UNITS
CARIBBEAN
PUBLIC AND OCCUPATIONAL HEALTH
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv The global impact of COVID-19 has challenged health systems across the world. This situation highlighted the need to develop policies based on scientific evidence to prepare the health systems and mitigate the pandemic. In this scenario, governments were urged to predict the impact of the measures they were implementing, how they related to the population’s behavior, and the capacity of health systems to respond to the pandemic. The overarching aim of this research was to develop a customizable and open-source tool to predict the impact of the expansion of COVID-19 on the level of preparedness of the health systems of different Latin American and the Caribbean countries, with two main objectives. Firstly, to estimate the transmission dynamics of COVID-19 and the preparedness and response capacity of health systems in those countries, based on different scenarios and public policies implemented to control, mitigate, or suppress the spread of the epidemic. Secondly, to facilitate policy makers’ decisions by allowing the model to adjust its parameters according to the specific pandemic trajectory and policy context. How many infections and deaths are estimated per day?; When are the peaks of cases and deaths expected, according to the different scenarios?; Which occupancy rate will ICU services have along the epidemiological curve?; When is the optimal time increase restrictions in order to prevent saturation of ICU beds?, are some of the key questions that the model can respond, and is publicly accessible through the following link: http://shinyapps.iecs.org.ar/modelo-covid19/. This open-access and open code tool is based on a SEIR model (Susceptible, Exposed, Infected and Recovered). Using a deterministic epidemiological model, it allows to frame potential scenarios for long periods, providing valuable information on the dynamics of transmission and how it could impact on health systems through multiple customized configurations adapted to specific characteristics of each country.
Fil: Santoro, Adrián Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: López Osornio, Alejandro. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Williams, Iván. Universidad de Buenos Aires. Facultad de Ciencias Económicas; Argentina
Fil: Wachs, Martín. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Cejas, Cintia. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Havela, Maisa. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: López, Analía. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: Pichón Riviere, Andrés. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Rubinstein, Adolfo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
description The global impact of COVID-19 has challenged health systems across the world. This situation highlighted the need to develop policies based on scientific evidence to prepare the health systems and mitigate the pandemic. In this scenario, governments were urged to predict the impact of the measures they were implementing, how they related to the population’s behavior, and the capacity of health systems to respond to the pandemic. The overarching aim of this research was to develop a customizable and open-source tool to predict the impact of the expansion of COVID-19 on the level of preparedness of the health systems of different Latin American and the Caribbean countries, with two main objectives. Firstly, to estimate the transmission dynamics of COVID-19 and the preparedness and response capacity of health systems in those countries, based on different scenarios and public policies implemented to control, mitigate, or suppress the spread of the epidemic. Secondly, to facilitate policy makers’ decisions by allowing the model to adjust its parameters according to the specific pandemic trajectory and policy context. How many infections and deaths are estimated per day?; When are the peaks of cases and deaths expected, according to the different scenarios?; Which occupancy rate will ICU services have along the epidemiological curve?; When is the optimal time increase restrictions in order to prevent saturation of ICU beds?, are some of the key questions that the model can respond, and is publicly accessible through the following link: http://shinyapps.iecs.org.ar/modelo-covid19/. This open-access and open code tool is based on a SEIR model (Susceptible, Exposed, Infected and Recovered). Using a deterministic epidemiological model, it allows to frame potential scenarios for long periods, providing valuable information on the dynamics of transmission and how it could impact on health systems through multiple customized configurations adapted to specific characteristics of each country.
publishDate 2022
dc.date.none.fl_str_mv 2022-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/215334
Santoro, Adrián Gabriel; López Osornio, Alejandro; Williams, Iván; Wachs, Martín; Cejas, Cintia; et al.; Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries; Public Library of Science; PLOS Global Public Health; 2; 3; 3-2022; 1-13
2767-3375
CONICET Digital
CONICET
url http://hdl.handle.net/11336/215334
identifier_str_mv Santoro, Adrián Gabriel; López Osornio, Alejandro; Williams, Iván; Wachs, Martín; Cejas, Cintia; et al.; Development and application of a dynamic transmission model of health systems’ preparedness and response to COVID-19 in twenty-six Latin American and Caribbean countries; Public Library of Science; PLOS Global Public Health; 2; 3; 3-2022; 1-13
2767-3375
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pgph.0000186
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pgph.0000186
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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