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...
- 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
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oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/12076 |
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| 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 http://purl.org/coar/access_right/c_f1cf |
| 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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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. 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.7 páginasimage/jepgengChaos, Solitons and Fractalsreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoCOVID-19Model calibrationPredictive modelling and simulationTime varying disease transmission rateSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusInsights into the dynamics and control of COVID-19 infection ratesArtículohttp://purl.org/coar/resource_type/c_6501Acceso restringidohttp://purl.org/coar/access_right/c_f1cfWillis, Mark J.Grisales Díaz, Victor HugoPrado-Rubio, Oscar AndrésStosch, Moritz vonLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12076/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessTHUMBNAILCaptura.PNGCaptura.PNGPortadaimage/png166048https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12076/4/Captura.PNG045704131e68c08ff22e65b34e09e963MD54open accessInsights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdf.jpgInsights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdf.jpgIM Thumbnailimage/jpeg15479https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12076/5/Insights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdf.jpg683d854d694f893158c74e6675f53654MD55open accessORIGINALCaptura.PNGCaptura.PNGVer portadaimage/png166048https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12076/1/Captura.PNG045704131e68c08ff22e65b34e09e963MD51open accessInsights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdfInsights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdfArtículo reservadoapplication/pdf1120824https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12076/3/Insights-into-the-dynamics-and-control-of-COVID-19-_2020_Chaos--Solitons---F.pdfd6de3dea3565eb09168e1e8dcae50324MD53embargoed access|||2200-08-2120.500.12010/12076oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/120762020-08-21 09:18:58.927open accessRepositorio Institucional - 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