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...

Full description

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)
id EDOCUR2_52fa28865245783f1311a5bf427957e2
oai_identifier_str oai:repository.urosario.edu.co:10336/23157
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 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
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
bitstream.url.fl_str_mv https://repository.urosario.edu.co/bitstreams/66368c2b-cca4-4177-af61-959ad7f8c41b/download
https://repository.urosario.edu.co/bitstreams/baacae34-e6e2-4710-aa2c-10bd88097a77/download
https://repository.urosario.edu.co/bitstreams/b3d4722f-6eef-47a5-a317-7b7088b15ec1/download
bitstream.checksum.fl_str_mv a021e4c448bf9eedd4809ae32b1db603
0cc86e39ad0efaa83d90361deb8681e0
c6ed55a509e9d4b0ff6dee043d41aae5
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
_version_ 1818106536407334912