Simulación en tiempos de pandemia

Autores:
Ceballos, Yony Fernando
Tipo de recurso:
Article of investigation
Fecha de publicación:
2021
Institución:
Universidad Autónoma de Bucaramanga - UNAB
Repositorio:
Repositorio UNAB
Idioma:
spa
OAI Identifier:
oai:repository.unab.edu.co:20.500.12749/26463
Acceso en línea:
http://hdl.handle.net/20.500.12749/26463
https://doi.org/10.29375/25392115.4154
Palabra clave:
Simulación
Pandemia
Computación
Tecnologías
Simulation
Pandemic
Computing
Technologies
Rights
License
http://purl.org/coar/access_right/c_abf2
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dc.title.spa.fl_str_mv Simulación en tiempos de pandemia
title Simulación en tiempos de pandemia
spellingShingle Simulación en tiempos de pandemia
Simulación
Pandemia
Computación
Tecnologías
Simulation
Pandemic
Computing
Technologies
title_short Simulación en tiempos de pandemia
title_full Simulación en tiempos de pandemia
title_fullStr Simulación en tiempos de pandemia
title_full_unstemmed Simulación en tiempos de pandemia
title_sort Simulación en tiempos de pandemia
dc.creator.fl_str_mv Ceballos, Yony Fernando
dc.contributor.author.none.fl_str_mv Ceballos, Yony Fernando
dc.subject.spa.fl_str_mv Simulación
Pandemia
Computación
Tecnologías
topic Simulación
Pandemia
Computación
Tecnologías
Simulation
Pandemic
Computing
Technologies
dc.subject.keywords.eng.fl_str_mv Simulation
Pandemic
Computing
Technologies
publishDate 2021
dc.date.issued.none.fl_str_mv 2021-06-01
dc.date.accessioned.none.fl_str_mv 2024-09-10T22:12:23Z
dc.date.available.none.fl_str_mv 2024-09-10T22:12:23Z
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dc.identifier.instname.spa.fl_str_mv instname:Universidad Autónoma de Bucaramanga UNAB
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identifier_str_mv ISSN: 1657-2831
e-ISSN: 2539-2115
instname:Universidad Autónoma de Bucaramanga UNAB
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url http://hdl.handle.net/20.500.12749/26463
https://doi.org/10.29375/25392115.4154
dc.language.iso.spa.fl_str_mv spa
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dc.relation.spa.fl_str_mv https://revistas.unab.edu.co/index.php/rcc/article/view/4154/3407
dc.relation.uri.spa.fl_str_mv https://revistas.unab.edu.co/index.php/rcc/issue/view/273
dc.relation.references.none.fl_str_mv Araya, F. (2021). Modeling the spread of COVID-19 on construction workers: An agent-based approach. Safety Science, 133, 105022. https://doi.org/10.1016/j.ssci.2020.105022
Bertoglio, N., Lamperti, G., Zanella, M., & Zhao, X. (2020). Temporal-Fault Diagnosis for Critical-Decision Making in Discrete-Event Systems. Procedia Computer Science, 176, 521–530. https://doi.org/10.1016/j.procs.2020.08.054
Cuadros, D. F., Branscum, A. J., Mukandavire, Z., Miller, F. D., & MacKinnon, N. (2021). Dynamics of the COVID- 19 epidemic in urban and rural areas in the United States. Annals of Epidemiology, 59, 16–20. https://doi.org/10.1016/j.annepidem.2021.04.007
Cuevas, E. (2020). An agent-based model to evaluate the COVID-19 transmission risks in facilities. Computers in Biology and Medicine, 121, 103827. https://doi.org/10.1016/j.compbiomed.2020.103827
Das, A. (2020). Impact of the COVID-19 pandemic on the workflow of an ambulatory endoscopy center: an assessment by discrete event simulation. Gastrointestinal Endoscopy, 92(4), 914–924. https://doi.org/10.1016/j.gie.2020.06.008
Fair, J. M., LeClaire, R. J., Dauelsberg, L. R., Ewers, M., Pasqualini, D., Cleland, T., & Rosenberger, W. (2021). Systems dynamics and the uncertainties of diagnostics, testing and contact tracing for COVID-19. Methods. https://doi.org/10.1016/j.ymeth.2021.03.008
Ibarra-Vega, D. (2020). Lockdown, one, two, none, or smart. Modeling containing covid-19 infection. A conceptual model. Science of The Total Environment, 730, 138917. https://doi.org/10.1016/j.scitotenv.2020.138917
Kierzkowski, A., & Kisiel, T. (2020). Simulation model of security control lane operation in the state of the COVID- 19 epidemic. Journal of Air Transport Management, 88, 101868. https://doi.org/10.1016/j.jairtraman.2020.101868
Kontogiannis, T. (2021). A qualitative model of patterns of resilience and vulnerability in responding to a pandemic outbreak with system dynamics. Safety Science, 134, 105077. https://doi.org/10.1016/j.ssci.2020.105077
Lim, C. Y., Bohn, M. K., Lippi, G., Ferrari, M., Loh, T. P., Yuen, K.-Y., Adeli, K., & Horvath, A. R. (2020). Staff rostering, split team arrangement, social distancing (physical distancing) and use of personal protective equipment to minimize risk of workplace transmission during the COVID-19 pandemic: A simulation study. Clinical Biochemistry, 86, 15–22. https://doi.org/10.1016/j.clinbiochem.2020.09.003
Silva, P. C. L., Batista, P. V. C., Lima, H. S., Alves, M. A., Guimarães, F. G., & Silva, R. C. P. (2020). COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos, Solitons & Fractals, 139, 110088. https://doi.org/10.1016/j.chaos.2020.110088
Tatapudi, H., Das, R., & Das, T. K. (2020). Impact assessment of full and partial stay-at-home orders, face mask usage, and contact tracing: An agent-based simulation study of COVID-19 for an urban region. Global Epidemiology, 2, 100036. https://doi.org/10.1016/j.gloepi.2020.100036
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spelling Ceballos, Yony Fernando6b26b936-303a-4ae2-a73c-13354bd22f922024-09-10T22:12:23Z2024-09-10T22:12:23Z2021-06-01ISSN: 1657-2831e-ISSN: 2539-2115http://hdl.handle.net/20.500.12749/26463instname:Universidad Autónoma de Bucaramanga UNABrepourl:https://repository.unab.edu.cohttps://doi.org/10.29375/25392115.4154application/pdfspaUniversidad Autónoma de Bucaramanga UNABhttps://revistas.unab.edu.co/index.php/rcc/article/view/4154/3407https://revistas.unab.edu.co/index.php/rcc/issue/view/273Araya, F. (2021). Modeling the spread of COVID-19 on construction workers: An agent-based approach. Safety Science, 133, 105022. https://doi.org/10.1016/j.ssci.2020.105022Bertoglio, N., Lamperti, G., Zanella, M., & Zhao, X. (2020). Temporal-Fault Diagnosis for Critical-Decision Making in Discrete-Event Systems. Procedia Computer Science, 176, 521–530. https://doi.org/10.1016/j.procs.2020.08.054Cuadros, D. F., Branscum, A. J., Mukandavire, Z., Miller, F. D., & MacKinnon, N. (2021). Dynamics of the COVID- 19 epidemic in urban and rural areas in the United States. Annals of Epidemiology, 59, 16–20. https://doi.org/10.1016/j.annepidem.2021.04.007Cuevas, E. (2020). An agent-based model to evaluate the COVID-19 transmission risks in facilities. Computers in Biology and Medicine, 121, 103827. https://doi.org/10.1016/j.compbiomed.2020.103827Das, A. (2020). Impact of the COVID-19 pandemic on the workflow of an ambulatory endoscopy center: an assessment by discrete event simulation. Gastrointestinal Endoscopy, 92(4), 914–924. https://doi.org/10.1016/j.gie.2020.06.008Fair, J. M., LeClaire, R. J., Dauelsberg, L. R., Ewers, M., Pasqualini, D., Cleland, T., & Rosenberger, W. (2021). Systems dynamics and the uncertainties of diagnostics, testing and contact tracing for COVID-19. Methods. https://doi.org/10.1016/j.ymeth.2021.03.008Ibarra-Vega, D. (2020). Lockdown, one, two, none, or smart. Modeling containing covid-19 infection. A conceptual model. Science of The Total Environment, 730, 138917. https://doi.org/10.1016/j.scitotenv.2020.138917Kierzkowski, A., & Kisiel, T. (2020). Simulation model of security control lane operation in the state of the COVID- 19 epidemic. Journal of Air Transport Management, 88, 101868. https://doi.org/10.1016/j.jairtraman.2020.101868Kontogiannis, T. (2021). A qualitative model of patterns of resilience and vulnerability in responding to a pandemic outbreak with system dynamics. Safety Science, 134, 105077. https://doi.org/10.1016/j.ssci.2020.105077Lim, C. Y., Bohn, M. K., Lippi, G., Ferrari, M., Loh, T. P., Yuen, K.-Y., Adeli, K., & Horvath, A. R. (2020). Staff rostering, split team arrangement, social distancing (physical distancing) and use of personal protective equipment to minimize risk of workplace transmission during the COVID-19 pandemic: A simulation study. Clinical Biochemistry, 86, 15–22. https://doi.org/10.1016/j.clinbiochem.2020.09.003Silva, P. C. L., Batista, P. V. C., Lima, H. S., Alves, M. A., Guimarães, F. G., & Silva, R. C. P. (2020). COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos, Solitons & Fractals, 139, 110088. https://doi.org/10.1016/j.chaos.2020.110088Tatapudi, H., Das, R., & Das, T. K. (2020). Impact assessment of full and partial stay-at-home orders, face mask usage, and contact tracing: An agent-based simulation study of COVID-19 for an urban region. Global Epidemiology, 2, 100036. https://doi.org/10.1016/j.gloepi.2020.100036Vol. 22 Núm. 1 (2021): Revista Colombiana de Computación (Enero-Junio); 56-57SimulaciónPandemiaComputaciónTecnologíasSimulationPandemicComputingTechnologiesSimulación en tiempos de pandemiainfo:eu-repo/semantics/articleArtículohttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/access_right/c_abf2ORIGINALArtículo.pdfArtículo.pdfArtículoapplication/pdf137439https://repository.unab.edu.co/bitstream/20.500.12749/26463/1/Art%c3%adculo.pdfc385230c33a8207d0d9bd88fbe3e8aa6MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-8347https://repository.unab.edu.co/bitstream/20.500.12749/26463/2/license.txt855f7d18ea80f5df821f7004dff2f316MD52open accessTHUMBNAILArtículo.pdf.jpgArtículo.pdf.jpgIM Thumbnailimage/jpeg10258https://repository.unab.edu.co/bitstream/20.500.12749/26463/3/Art%c3%adculo.pdf.jpg78e6f6e648b01a2cf6cda6d8f927210dMD53open access20.500.12749/26463oai:repository.unab.edu.co:20.500.12749/264632024-09-10 22:01:27.151open accessRepositorio Institucional | Universidad Autónoma de Bucaramanga - UNABrepositorio@unab.edu.coTGEgUmV2aXN0YSBDb2xvbWJpYW5hIGRlIENvbXB1dGFjacOzbiBlcyBmaW5hbmNpYWRhIHBvciBsYSBVbml2ZXJzaWRhZCBBdXTDs25vbWEgZGUgQnVjYXJhbWFuZ2EuIEVzdGEgUmV2aXN0YSBubyBjb2JyYSB0YXNhIGRlIHN1bWlzacOzbiB5IHB1YmxpY2FjacOzbiBkZSBhcnTDrWN1bG9zLiBQcm92ZWUgYWNjZXNvIGxpYnJlIGlubWVkaWF0byBhIHN1IGNvbnRlbmlkbyBiYWpvIGVsIHByaW5jaXBpbyBkZSBxdWUgaGFjZXIgZGlzcG9uaWJsZSBncmF0dWl0YW1lbnRlIGludmVzdGlnYWNpw7NuIGFsIHDDumJsaWNvIGFwb3lhIGEgdW4gbWF5b3IgaW50ZXJjYW1iaW8gZGUgY29ub2NpbWllbnRvIGdsb2JhbC4=

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