Insights into the dynamics and control of COVID-19 infection rates

This work aims to model, simulate and provide insights into the dynamics and control of COVID-19 infection rates. Using an established epidemiological model augmented with a time-varying disease transmission rate allows daily model calibration using COVID-19 case data from countries around the world...

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Autores:
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/12076
Acceso en línea:
https://doi.org/10.1016/j.chaos.2020.109937
http://hdl.handle.net/20.500.12010/12076
Palabra clave:
COVID-19
Model calibration
Predictive modelling and simulation
Time varying disease transmission rate
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
Rights
License
Acceso restringido
id UTADEO2_2383b2d584b307e11ffe12037ce31c20
oai_identifier_str oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/12076
network_acronym_str UTADEO2
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repository_id_str
dc.title.spa.fl_str_mv Insights into the dynamics and control of COVID-19 infection rates
title Insights into the dynamics and control of COVID-19 infection rates
spellingShingle Insights into the dynamics and control of COVID-19 infection rates
COVID-19
Model calibration
Predictive modelling and simulation
Time varying disease transmission rate
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
title_short Insights into the dynamics and control of COVID-19 infection rates
title_full Insights into the dynamics and control of COVID-19 infection rates
title_fullStr Insights into the dynamics and control of COVID-19 infection rates
title_full_unstemmed Insights into the dynamics and control of COVID-19 infection rates
title_sort Insights into the dynamics and control of COVID-19 infection rates
dc.subject.spa.fl_str_mv COVID-19
Model calibration
Predictive modelling and simulation
Time varying disease transmission rate
topic COVID-19
Model calibration
Predictive modelling and simulation
Time varying disease transmission rate
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
dc.subject.lemb.spa.fl_str_mv Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
description This work aims to model, simulate and provide insights into the dynamics and control of COVID-19 infection rates. Using an established epidemiological model augmented with a time-varying disease transmission rate allows daily model calibration using COVID-19 case data from countries around the world. This hybrid model provides predictive forecasts of the cumulative number of infected cases. It also reveals the dynamics associated with disease suppression, demonstrating the time to reduce the effective, time-dependent, reproduction number. Model simulations provide insights into the outcomes of disease suppression measures and the predicted duration of the pandemic. Visualisation of reported data provides up-to-date condition monitoring, while daily model calibration allows for a continued and updated forecast of the current state of the pandemic.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-08-21T14:18:58Z
dc.date.available.none.fl_str_mv 2020-08-21T14:18:58Z
dc.date.created.none.fl_str_mv 2020
dc.type.local.spa.fl_str_mv Artículo
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
format http://purl.org/coar/resource_type/c_6501
dc.identifier.issn.spa.fl_str_mv 0960-0779
dc.identifier.other.spa.fl_str_mv https://doi.org/10.1016/j.chaos.2020.109937
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/12076
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1016/j.chaos.2020.109937
identifier_str_mv 0960-0779
url https://doi.org/10.1016/j.chaos.2020.109937
http://hdl.handle.net/20.500.12010/12076
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_f1cf
dc.rights.local.spa.fl_str_mv Acceso restringido
rights_invalid_str_mv Acceso restringido
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dc.format.extent.spa.fl_str_mv 7 páginas
dc.format.mimetype.spa.fl_str_mv image/jepg
dc.publisher.spa.fl_str_mv Chaos, Solitons and Fractals
dc.source.spa.fl_str_mv reponame:Expeditio Repositorio Institucional UJTL
instname:Universidad de Bogotá Jorge Tadeo Lozano
instname_str Universidad de Bogotá Jorge Tadeo Lozano
institution Universidad de Bogotá Jorge Tadeo Lozano
reponame_str Expeditio Repositorio Institucional UJTL
collection Expeditio Repositorio Institucional UJTL
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spelling 2020-08-21T14:18:58Z2020-08-21T14:18:58Z20200960-0779https://doi.org/10.1016/j.chaos.2020.109937http://hdl.handle.net/20.500.12010/12076https://doi.org/10.1016/j.chaos.2020.109937This work aims to model, simulate and provide insights into the dynamics and control of COVID-19 infection rates. Using an established epidemiological model augmented with a time-varying disease transmission rate allows daily model calibration using COVID-19 case data from countries around the world. This hybrid model provides predictive forecasts of the cumulative number of infected cases. It also reveals the dynamics associated with disease suppression, demonstrating the time to reduce the effective, time-dependent, reproduction number. Model simulations provide insights into the outcomes of disease suppression measures and the predicted duration of the pandemic. 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