Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW

With the arrival of the pandemic in Argentina in March 2020, a working group of scientists from two institutes belonging to the Faculty of Exact and Natural Sciences of the University of Buenos Aires and CONICET, together with colleagues from different...

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Detalles Bibliográficos
Autores principales: Arrar, Mehrnoosh, Belloli, Laouen Mayal Louan, Bianco, Ana María, Boechi, Leonardo, Castro, Rodrigo Daniel, Duran, Guillermo Alfredo, Etchenique, Roberto Argentino, Fernández, Natalia Brenda, Ferrer, Luciana, Garbervetsky, Diego David, Goldsmit, Rodrigo, Grillo, Carolina, Kamienkowsk, Juan E., Laciana, Pablo, Lanzarotti, Esteban, Lozano, Mario Enrique, Maidana, Rodrigo, Mendiluce, Mauricio, Minoldo, Sol, Daniel Pecker Marcosig, Ezequiel Puerta, Ezequiel Quiroga, Rodrigo Solovey, Guillermo Valdora, Marina Silvia Zapatero, Mariano, Pepino, Leonardo Daniel, Pecker Marcosig, Ezequiel, Puerta, Ezequiel, Quiroga, Rodrigo, Solovey, Guillermo, Valdora, Marina Silvia, Zapatero, Mariano
Formato: article
Lenguaje:Español
Publicado: 2021
Materias:
Covid 19
Data-driven
Response
Agent-based simulations
Effective reproductive number
Prognosis models
Buenos Aires
Pandemic
Acceso en línea:http://hdl.handle.net/11086/19833
http://www.scirevfew.net/index.php/sciencereviews/article/view/38
Aporte de:
Repositorio Digital Universitario (UNC) de Universidad Nacional de Córdoba
id I10-R14111086-19833
record_format dspace
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-141
collection Repositorio Digital Universitario (UNC)
language Español
topic Covid 19
Data-driven
Response
Agent-based simulations
Effective reproductive number
Prognosis models
Buenos Aires
Pandemic
spellingShingle Covid 19
Data-driven
Response
Agent-based simulations
Effective reproductive number
Prognosis models
Buenos Aires
Pandemic
Arrar, Mehrnoosh
Belloli, Laouen Mayal Louan
Bianco, Ana María
Boechi, Leonardo
Castro, Rodrigo Daniel
Duran, Guillermo Alfredo
Etchenique, Roberto Argentino
Fernández, Natalia Brenda
Ferrer, Luciana
Garbervetsky, Diego David
Goldsmit, Rodrigo
Grillo, Carolina
Kamienkowsk, Juan E.
Laciana, Pablo
Lanzarotti, Esteban
Lozano, Mario Enrique
Maidana, Rodrigo
Mendiluce, Mauricio
Minoldo, Sol
Daniel Pecker Marcosig, Ezequiel Puerta, Ezequiel Quiroga, Rodrigo Solovey, Guillermo Valdora, Marina Silvia Zapatero, Mariano
Pepino, Leonardo Daniel
Pecker Marcosig, Ezequiel
Puerta, Ezequiel
Quiroga, Rodrigo
Solovey, Guillermo
Valdora, Marina Silvia
Zapatero, Mariano
Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
topic_facet Covid 19
Data-driven
Response
Agent-based simulations
Effective reproductive number
Prognosis models
Buenos Aires
Pandemic
description With the arrival of the pandemic in Argentina in March 2020, a working group of scientists from two institutes belonging to the Faculty of Exact and Natural Sciences of the University of Buenos Aires and CONICET, together with colleagues from different academic institutions in the country, decided to put forth our experience and knowledge in data science and associated disciplines, towards helping with decision-making in the context of COVID-19. Data analysis within Argentina and other countries, scenario simulation, as well as rapid response projects- mainly in the province of Buenos Aires- were all within the scope of our aim. This review article outlines some of the activities carried out by our team throughout these pandemic months.
format article
author Arrar, Mehrnoosh
Belloli, Laouen Mayal Louan
Bianco, Ana María
Boechi, Leonardo
Castro, Rodrigo Daniel
Duran, Guillermo Alfredo
Etchenique, Roberto Argentino
Fernández, Natalia Brenda
Ferrer, Luciana
Garbervetsky, Diego David
Goldsmit, Rodrigo
Grillo, Carolina
Kamienkowsk, Juan E.
Laciana, Pablo
Lanzarotti, Esteban
Lozano, Mario Enrique
Maidana, Rodrigo
Mendiluce, Mauricio
Minoldo, Sol
Daniel Pecker Marcosig, Ezequiel Puerta, Ezequiel Quiroga, Rodrigo Solovey, Guillermo Valdora, Marina Silvia Zapatero, Mariano
Pepino, Leonardo Daniel
Pecker Marcosig, Ezequiel
Puerta, Ezequiel
Quiroga, Rodrigo
Solovey, Guillermo
Valdora, Marina Silvia
Zapatero, Mariano
author_facet Arrar, Mehrnoosh
Belloli, Laouen Mayal Louan
Bianco, Ana María
Boechi, Leonardo
Castro, Rodrigo Daniel
Duran, Guillermo Alfredo
Etchenique, Roberto Argentino
Fernández, Natalia Brenda
Ferrer, Luciana
Garbervetsky, Diego David
Goldsmit, Rodrigo
Grillo, Carolina
Kamienkowsk, Juan E.
Laciana, Pablo
Lanzarotti, Esteban
Lozano, Mario Enrique
Maidana, Rodrigo
Mendiluce, Mauricio
Minoldo, Sol
Daniel Pecker Marcosig, Ezequiel Puerta, Ezequiel Quiroga, Rodrigo Solovey, Guillermo Valdora, Marina Silvia Zapatero, Mariano
Pepino, Leonardo Daniel
Pecker Marcosig, Ezequiel
Puerta, Ezequiel
Quiroga, Rodrigo
Solovey, Guillermo
Valdora, Marina Silvia
Zapatero, Mariano
author_sort Arrar, Mehrnoosh
title Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
title_short Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
title_full Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
title_fullStr Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
title_full_unstemmed Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW
title_sort mathematical and computational initiatives from the university of buenos aires to contribute to decision-making in the context of covid-19 in argentina. review
publishDate 2021
url http://hdl.handle.net/11086/19833
http://www.scirevfew.net/index.php/sciencereviews/article/view/38
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