Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia
Objective To establish a new predictive methodology to determine the proportion of severe dengue with respect to the annual total of dengue infections per department based on the probability theory. Materials and Methods Based on annual data on the number of infected persons by department in the per...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/23157
- Acceso en línea:
- https://doi.org/10.15446/rsap.v20n3.42701
https://repository.urosario.edu.co/handle/10336/23157
- Palabra clave:
- Biological model
Colombia
Epidemic
Human
Probability
Severe dengue
Spatiotemporal analysis
Colombia
Epidemics
Humans
Probability
Severe dengue
Spatio-temporal analysis
Dengue
Epidemics
Probability
biological
Models
Severe dengue
- Rights
- License
- Abierto (Texto Completo)
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6d4e551c-1e14-498b-80ad-b8641293072d826418fc-c4ae-4c2b-a4f2-953016d66edb26ffa6c7-de1e-4be4-9d05-37b9932cad5d80423861600cbc28566-283f-4a3c-b6d6-de9be2810195107fd603-ed0c-4b44-8bd4-28976c6c882e1e5e9da2-0123-4253-9b5a-cc3364e0d3b453741498-8f66-48f6-97c5-2b1ab097b1963bef77ff-a2b0-48b6-8999-2ef27996fc7e8641a662-7dd6-4505-8f48-e82b3aa2f5c82020-05-26T00:00:04Z2020-05-26T00:00:04Z2018Objective To establish a new predictive methodology to determine the proportion of severe dengue with respect to the annual total of dengue infections per department based on the probability theory. Materials and Methods Based on annual data on the number of infected persons by department in the period 2005-2010, the proportion of cases of severe dengue was calculated with respect to the total for each year. Probability spaces were constructed to evaluate these events in the ranges 0.5 and 0.3. Sets of ranges were determined and probability, mean square deviation and the difference between them were estimated. A prediction of the range of infected people for 2011 was made using the arithmetic average of the values of the last two years. Results The range in which the proportion of the number of people infected with severe dengue is included with respect to the total amount in each department was correctly predicted, with an effectiveness of 93.3% for the 0.5 range and 86.7% for the 0.3 range. Conclusion A mathematical spatial-temporal self-organization was found in the proportion of severe dengue with respect to the total, which allows establishing useful predictions for decision-making in public health. © 2018, Universidad Nacional de Colombia. All rights reserved.application/pdfhttps://doi.org/10.15446/rsap.v20n3.427011240064https://repository.urosario.edu.co/handle/10336/23157engUniversidad Nacional de Colombia358No. 3352Revista de Salud PublicaVol. 20Revista de Salud Publica, ISSN:1240064, Vol.20, No.3 (2018); pp. 352-358https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057819969&doi=10.15446%2frsap.v20n3.42701&partnerID=40&md5=116d49d67502c55a7698076cbed79d36Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURBiological modelColombiaEpidemicHumanProbabilitySevere dengueSpatiotemporal analysisColombiaEpidemicsHumansProbabilitySevere dengueSpatio-temporal analysisDengueEpidemicsProbabilitybiologicalModelsSevere dengueProbabilistic spatial-temporal prediction of total and severe epidemic of dengue in ColombiaPredicción espacio-temporal probabilista de la epidemia de dengue total y grave en ColombiaarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Rodríguez-Velásquez J.O.Prieto-Bohórquez S.E.Pérez-Díaz C.E.Pardo Oviedo, Juan MauricioCorrea-Herrera S.C.Mendoza-Beltrán F.C.Bravo-Ojeda J.S.Morales-Pertuz C.A.Rojas-Avila N.A.Flórez-Cárdenas M.ORIGINAL42701-405857-1-PB.pdfapplication/pdf393077https://repository.urosario.edu.co/bitstreams/66368c2b-cca4-4177-af61-959ad7f8c41b/downloada021e4c448bf9eedd4809ae32b1db603MD51TEXT42701-405857-1-PB.pdf.txt42701-405857-1-PB.pdf.txtExtracted texttext/plain30440https://repository.urosario.edu.co/bitstreams/baacae34-e6e2-4710-aa2c-10bd88097a77/download0cc86e39ad0efaa83d90361deb8681e0MD52THUMBNAIL42701-405857-1-PB.pdf.jpg42701-405857-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg3854https://repository.urosario.edu.co/bitstreams/b3d4722f-6eef-47a5-a317-7b7088b15ec1/downloadc6ed55a509e9d4b0ff6dee043d41aae5MD5310336/23157oai:repository.urosario.edu.co:10336/231572022-05-02 07:37:16.997762https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
dc.title.TranslatedTitle.spa.fl_str_mv |
Predicción espacio-temporal probabilista de la epidemia de dengue total y grave en Colombia |
title |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
spellingShingle |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia Biological model Colombia Epidemic Human Probability Severe dengue Spatiotemporal analysis Colombia Epidemics Humans Probability Severe dengue Spatio-temporal analysis Dengue Epidemics Probability biological Models Severe dengue |
title_short |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
title_full |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
title_fullStr |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
title_full_unstemmed |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
title_sort |
Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia |
dc.subject.keyword.spa.fl_str_mv |
Biological model Colombia Epidemic Human Probability Severe dengue Spatiotemporal analysis Colombia Epidemics Humans Probability Severe dengue Spatio-temporal analysis Dengue Epidemics Probability |
topic |
Biological model Colombia Epidemic Human Probability Severe dengue Spatiotemporal analysis Colombia Epidemics Humans Probability Severe dengue Spatio-temporal analysis Dengue Epidemics Probability biological Models Severe dengue |
dc.subject.keyword.eng.fl_str_mv |
biological Models Severe dengue |
description |
Objective To establish a new predictive methodology to determine the proportion of severe dengue with respect to the annual total of dengue infections per department based on the probability theory. Materials and Methods Based on annual data on the number of infected persons by department in the period 2005-2010, the proportion of cases of severe dengue was calculated with respect to the total for each year. Probability spaces were constructed to evaluate these events in the ranges 0.5 and 0.3. Sets of ranges were determined and probability, mean square deviation and the difference between them were estimated. A prediction of the range of infected people for 2011 was made using the arithmetic average of the values of the last two years. Results The range in which the proportion of the number of people infected with severe dengue is included with respect to the total amount in each department was correctly predicted, with an effectiveness of 93.3% for the 0.5 range and 86.7% for the 0.3 range. Conclusion A mathematical spatial-temporal self-organization was found in the proportion of severe dengue with respect to the total, which allows establishing useful predictions for decision-making in public health. © 2018, Universidad Nacional de Colombia. All rights reserved. |
publishDate |
2018 |
dc.date.created.spa.fl_str_mv |
2018 |
dc.date.accessioned.none.fl_str_mv |
2020-05-26T00:00:04Z |
dc.date.available.none.fl_str_mv |
2020-05-26T00:00:04Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.15446/rsap.v20n3.42701 |
dc.identifier.issn.none.fl_str_mv |
1240064 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/23157 |
url |
https://doi.org/10.15446/rsap.v20n3.42701 https://repository.urosario.edu.co/handle/10336/23157 |
identifier_str_mv |
1240064 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
358 |
dc.relation.citationIssue.none.fl_str_mv |
No. 3 |
dc.relation.citationStartPage.none.fl_str_mv |
352 |
dc.relation.citationTitle.none.fl_str_mv |
Revista de Salud Publica |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 20 |
dc.relation.ispartof.spa.fl_str_mv |
Revista de Salud Publica, ISSN:1240064, Vol.20, No.3 (2018); pp. 352-358 |
dc.relation.uri.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057819969&doi=10.15446%2frsap.v20n3.42701&partnerID=40&md5=116d49d67502c55a7698076cbed79d36 |
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http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
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Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
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Universidad Nacional de Colombia |
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Universidad del Rosario |
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