Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware

La teoría de la probabilidad permitió el desarrollo de la caminata al azar, que es útil para predecir el número de casos de epidemias como las muertes causadas por accidentes de tráfico. En esta investigación se buscó la aplicabilidad de la caminata aleatoria probabilística para predecir la incidenc...

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Autores:: Correa Herrera, Sandra Catalina
González Bernal, María Alejandra
Prieto Bohórquez, Signed
Ruíz Gómez, Adiela

Tipo de recurso:: Article of journal

Fecha de publicación:: 2022

Institución:: Universidad Cooperativa de Colombia

Repositorio:: Repositorio UCC

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dc.title.none.fl_str_mv	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
title	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
spellingShingle	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware Probabilidad Incidencia Accidentes de transito Probability Incidence Traffic accidents
title_short	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
title_full	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
title_fullStr	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
title_full_unstemmed	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
title_sort	Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware
dc.creator.fl_str_mv	Correa Herrera, Sandra Catalina González Bernal, María Alejandra Prieto Bohórquez, Signed Ruíz Gómez, Adiela
dc.contributor.author.none.fl_str_mv	Correa Herrera, Sandra Catalina González Bernal, María Alejandra Prieto Bohórquez, Signed Ruíz Gómez, Adiela
dc.subject.none.fl_str_mv	Probabilidad Incidencia Accidentes de transito
topic	Probabilidad Incidencia Accidentes de transito Probability Incidence Traffic accidents
dc.subject.other.none.fl_str_mv	Probability Incidence Traffic accidents
description	La teoría de la probabilidad permitió el desarrollo de la caminata al azar, que es útil para predecir el número de casos de epidemias como las muertes causadas por accidentes de tráfico. En esta investigación se buscó la aplicabilidad de la caminata aleatoria probabilística para predecir la incidencia anual de muertes secundarias a traumatismos causados por el tránsito en Connecticut y Delaware para 2017 y 2016 respectivamente. Para ello, los espacios de probabilidad que consideran las incidencias de muertes secundarias a traumatismos causados por el tránsito se presentan como los aumentos y disminuciones de los eventos probables. Se construyeron incidencias para Connecticut y Delaware con el fin de aplicar un ecuación cuadrática que predijo el número de casos para ambos estados en 2017 y 2016. Se encontró que la metodología predijo que para Connecticut y Delaware la incidencia de muertes fue de 288 y 123, respectivamente, que al compararlos con los valores reales reportados, 278 y 119, obteniendo precisiones superiores al 96%. Por lo tanto, se confirmó que la caminata al azar probabilística puede ser aplicable para predecir con alta precisión el comportamiento de la incidencia de muertes para Connecticut y Delaware, sugiriendo su papel potencial como herramienta para la vigilancia epidemiológica.
publishDate	2022
dc.date.issued.none.fl_str_mv	2022-12-18
dc.date.accessioned.none.fl_str_mv	2023-04-10T15:40:32Z
dc.date.available.none.fl_str_mv	2023-04-10T15:40:32Z
dc.type.none.fl_str_mv	Artículo
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dc.identifier.uri.none.fl_str_mv	https://www.ripublication.com/ijde22/v17n2p14.pdf https://hdl.handle.net/20.500.12494/49098
dc.identifier.bibliographicCitation.none.fl_str_mv	Correa-Herrera, SC., González-Bernal, MA., Ruiz-Gómez A., Prieto-Bohórquez SE. (2022). Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware. International Journal of Difference Equations (IJDE). 17(2), 319-328. https://www.ripublication.com/ijde22/v17n2p14.pdf
identifier_str_mv	0973-6069 Correa-Herrera, SC., González-Bernal, MA., Ruiz-Gómez A., Prieto-Bohórquez SE. (2022). Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware. International Journal of Difference Equations (IJDE). 17(2), 319-328. https://www.ripublication.com/ijde22/v17n2p14.pdf
url	https://www.ripublication.com/ijde22/v17n2p14.pdf https://hdl.handle.net/20.500.12494/49098
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dc.relation.references.none.fl_str_mv	Cattoni, D., Ozu, M,, Chara, O. (2004). Ruidos en la naturaleza. ANALES AFA, 16: 294-99. De Gennes, P.G. (1980). Scaling Concepts in Polymer Physics. London: Cornell University Press. Doi, M., & Edwards, S.F. (1986). The Theory of Polymer Dynamics. Oxford: Clarendon Press. Feynman, R.P., Leighton, R.B., & Sands M. (1964). Probabilidad. In: R. P. Feynman, R. B. Leighton & M. Sands. Física (pp. 1-16) Wilmington: AddisonWesley Iberoamericana. García, B., Bumbacher, A., Deublein, M. & Adey, B.T. (2018). Predicting road traffic accidents using artificial neural network models. Infrastructure Asset Management 5(4):132–144, https://doi.org/10.1680/jinam.17.00028 Goel, N.W., & Richter, N. (1974). Stochastic Models in Biology. New York: Academic Press. Hernández, M., Arboleda, D., Arce, S., Benavides, A., Tejada, P., Ramírez S, et al. (2016). Methodology to develop endemic channels and notification trends for dengue in Valle del Cauca, Colombia, 2009-2013. Biomedica, 36:98–107 Huang, H., Yin, Q., Schwebel, D.C., Li, L., Hu, G. (2016). Examining Road Traffic Mortality Status in China: A Simulation Study. PLoS ONE, 11(4): e0153251. https://doi.org/10.1371/journal.pone.0153251 Ihueze, C.C., & Onwurah, U.O. (2018). Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria. Accident Analysis & Prevention, 112:21-29 Laplace, P. (1995). Ensayo filosófico sobre las probabilidades. Barcelona: Altaza NHTSA. (2018). Fatality Analysis Reporting System (FARS) Encyclopedia. Resource document. http://www-fars.nhtsa.dot.gov/Main/index.aspx. Accessed 06 Februrary 2019 Pearson, K. (1905) The Problem of the Random Walk. Nature. 1905;72:294. Redner, S. (2001). A Guide to First-Passage Process. Cambridge: Cambridge University Press. Rodríguez, J. (2008). Binding to class II HLA theory: probability, combinatory and entropy applied to peptide sequences. Inmunología, 27:151–166. Rodríguez, J., & Correa, C. (2009). Predicción temporal de la epidemia de dengue en Colombia: dinámica probabilista de la epidemia. Rev. Salud pública, 11(3): 443-453. Rodríguez, J., Jattin, J., Soracipa, Y. (2020). Probabilistic temporal prediction of the deaths caused by traffic in Colombia. Mortality caused by traffic prediction. Accident Analysis & Prevention, 135:105332. Rodríguez, J., Oliveros, D., Rodríguez, D., Sosa, J., Prieto, S., & Correa, C. (2018b). Diagnostic methodology of cardiac dynamics based on the ZipfMandelbrot law: evaluation with 50 patients. Rev. Mex. Cardiol, 29: 83–89 Rodríguez, J., Oliveros, D., Soracipa, Y., Bernal, L., Correa, C., Abrahem, L., et al. (2018a). Análisis probabilista con caminata al azar del número de personas viviendo con VIH mundialmente. Rev. Fac. Nac. Salud Pública, 36(1): 27-33. Rodríguez, J., Prieto, S., Correa, C., Bernal, P., Puerta, G., & Vitery S. (2010). Theoretical generalization of normal and sick coronary arteries with fractal dimensions and the arterial intrinsic mathematical harmony. BMC Med. Phys, 10:1–6. Rodríguez, J., Prieto, S., Correa, C., Pérez, C., Mora, J., & Bravo, J. (2013). Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count. BMC Med. Phys, 2013;13:3. Rodríguez, J., Prieto, S.E., Correa, S.C., Pérez, C.E., & Soracipa, M.Y. (2017). Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal. Rev. Salud. Pública, 19(1):52-59. Samuel, J., Sankhulani, E., Qureshi, J., Baloyi, P., Thupi, C., Lee, C., et al. (2012). Under-reporting of road traffic mortality in developing countries: application of a capture-recapture statistical model to refine mortality estimates. PLoS One, 7,e31091. Van Kampen, N.G. (1992). Stochastic Processes in Physics and Chemistry. Amsterdam: North-Holland Publishing Company. Wangdi, C., Gurung, M.S., Duba, T., Wilkinson, E., Tun, Z.W., et al. (2017). Burden, pattern and causes of road traffic accidents in Bhutan, 2013–2014: a police record review. International Journal of Injury Control and Safety, https://doi.org/10.1080/17457300.2017.1341930 Weiss, G. (1994). Aspects and Applications of the Random Walk. Amsterdam: North-Holland Publishing Company. World Health Organization. (2018). Global Status Report on Road Safety. Resource document. https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/. Accessed 27 january 2019.
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spelling	Correa Herrera, Sandra CatalinaGonzález Bernal, María AlejandraPrieto Bohórquez, SignedRuíz Gómez, Adiela17/22023-04-10T15:40:32Z2023-04-10T15:40:32Z2022-12-180973-6069https://www.ripublication.com/ijde22/v17n2p14.pdfhttps://hdl.handle.net/20.500.12494/49098Correa-Herrera, SC., González-Bernal, MA., Ruiz-Gómez A., Prieto-Bohórquez SE. (2022). Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware. International Journal of Difference Equations (IJDE). 17(2), 319-328. https://www.ripublication.com/ijde22/v17n2p14.pdfLa teoría de la probabilidad permitió el desarrollo de la caminata al azar, que es útil para predecir el número de casos de epidemias como las muertes causadas por accidentes de tráfico. En esta investigación se buscó la aplicabilidad de la caminata aleatoria probabilística para predecir la incidencia anual de muertes secundarias a traumatismos causados por el tránsito en Connecticut y Delaware para 2017 y 2016 respectivamente. Para ello, los espacios de probabilidad que consideran las incidencias de muertes secundarias a traumatismos causados por el tránsito se presentan como los aumentos y disminuciones de los eventos probables. Se construyeron incidencias para Connecticut y Delaware con el fin de aplicar un ecuación cuadrática que predijo el número de casos para ambos estados en 2017 y 2016. Se encontró que la metodología predijo que para Connecticut y Delaware la incidencia de muertes fue de 288 y 123, respectivamente, que al compararlos con los valores reales reportados, 278 y 119, obteniendo precisiones superiores al 96%. Por lo tanto, se confirmó que la caminata al azar probabilística puede ser aplicable para predecir con alta precisión el comportamiento de la incidencia de muertes para Connecticut y Delaware, sugiriendo su papel potencial como herramienta para la vigilancia epidemiológica.Probability theory allowed the development of the probabilistic random walk, which is useful to predict the number of cases for epidemics such as the deaths caused by traffic accidents. In this investigation, it was wanted to confirm the applicability of the probabilistic random walk to predict the annual incidence of deaths secondary to road traffic injuries in Connecticut and Delaware for 2017 and 2016 respectively. For this, probability spaces that consider the incidences of deaths secondary to road traffic injuries as probabilistic events as well as the increases and decreases of annual incidences were built for Connecticut and Delaware in order to apply a quadratic equation thar predicted the number of cases for both states in 2017 and 2016. It was found that the methodology predicted that for Connecticut and Delaware the incidence of deaths were 288 and 123, respectively, that when compared with the real values reported, 278 and 119, obtaining accuracies superior to 96%. Hence, it was confirmed that the probabilistic random walk can be applicable to predict with high precision the behavior of the incidence of deaths for Connecticut and Delaware, suggesting its potential role as an epidemiological surveillance tool.https://scienti.minciencias.gov.co/cvlac/EnRecursoHumano/inicio.dohttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000313254https://scienti.minciencias.gov.co/cvlac/EnRecursoHumano/query.do0000-0003-4998-12280000-0002-6299-21350000-0002-7896-231X0000-0003-2011-2555Insight Group. Insight Research Group SASOdontopostgradosUCCmaria.gonzalezbe@campusucc.edu.cohttps://scholar.google.com/citations?user=ZQjzf2kAAAAJ&hl=eshttps://scholar.google.es/citations?user=HyZOE6MAAAAJ&hl=eshttps://scholar.google.es/citations?user=DakKhIYAAAAJ&hl=es319-328Universidad Cooperativa de Colombia, Facultad de Ciencias de la Salud, Odontología, BogotáOdontologíaBogotáProbabilidadIncidenciaAccidentes de transitoProbabilityIncidenceTraffic accidentsPrediction of the incidence of deaths secondary to road traffic injuries in Connecticut and DelawareArtículohttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionNINGUNAinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2International journal of difference equations IJDECattoni, D., Ozu, M,, Chara, O. (2004). Ruidos en la naturaleza. ANALES AFA, 16: 294-99.De Gennes, P.G. (1980). Scaling Concepts in Polymer Physics. London: Cornell University Press.Doi, M., & Edwards, S.F. (1986). The Theory of Polymer Dynamics. Oxford: Clarendon Press.Feynman, R.P., Leighton, R.B., & Sands M. (1964). Probabilidad. In: R. P. Feynman, R. B. Leighton & M. Sands. Física (pp. 1-16) Wilmington: AddisonWesley Iberoamericana.García, B., Bumbacher, A., Deublein, M. & Adey, B.T. (2018). Predicting road traffic accidents using artificial neural network models. Infrastructure Asset Management 5(4):132–144, https://doi.org/10.1680/jinam.17.00028Goel, N.W., & Richter, N. (1974). Stochastic Models in Biology. New York: Academic Press.Hernández, M., Arboleda, D., Arce, S., Benavides, A., Tejada, P., Ramírez S, et al. (2016). Methodology to develop endemic channels and notification trends for dengue in Valle del Cauca, Colombia, 2009-2013. Biomedica, 36:98–107Huang, H., Yin, Q., Schwebel, D.C., Li, L., Hu, G. (2016). Examining Road Traffic Mortality Status in China: A Simulation Study. PLoS ONE, 11(4): e0153251. https://doi.org/10.1371/journal.pone.0153251Ihueze, C.C., & Onwurah, U.O. (2018). Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria. Accident Analysis & Prevention, 112:21-29Laplace, P. (1995). Ensayo filosófico sobre las probabilidades. Barcelona: AltazaNHTSA. (2018). Fatality Analysis Reporting System (FARS) Encyclopedia. Resource document. http://www-fars.nhtsa.dot.gov/Main/index.aspx. Accessed 06 Februrary 2019Pearson, K. (1905) The Problem of the Random Walk. Nature. 1905;72:294.Redner, S. (2001). A Guide to First-Passage Process. Cambridge: Cambridge University Press.Rodríguez, J. (2008). Binding to class II HLA theory: probability, combinatory and entropy applied to peptide sequences. Inmunología, 27:151–166.Rodríguez, J., & Correa, C. (2009). Predicción temporal de la epidemia de dengue en Colombia: dinámica probabilista de la epidemia. Rev. Salud pública, 11(3): 443-453.Rodríguez, J., Jattin, J., Soracipa, Y. (2020). Probabilistic temporal prediction of the deaths caused by traffic in Colombia. Mortality caused by traffic prediction. Accident Analysis & Prevention, 135:105332.Rodríguez, J., Oliveros, D., Rodríguez, D., Sosa, J., Prieto, S., & Correa, C. (2018b). Diagnostic methodology of cardiac dynamics based on the ZipfMandelbrot law: evaluation with 50 patients. Rev. Mex. Cardiol, 29: 83–89Rodríguez, J., Oliveros, D., Soracipa, Y., Bernal, L., Correa, C., Abrahem, L., et al. (2018a). Análisis probabilista con caminata al azar del número de personas viviendo con VIH mundialmente. Rev. Fac. Nac. Salud Pública, 36(1): 27-33.Rodríguez, J., Prieto, S., Correa, C., Bernal, P., Puerta, G., & Vitery S. (2010). Theoretical generalization of normal and sick coronary arteries with fractal dimensions and the arterial intrinsic mathematical harmony. BMC Med. Phys, 10:1–6.Rodríguez, J., Prieto, S., Correa, C., Pérez, C., Mora, J., & Bravo, J. (2013). Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count. BMC Med. Phys, 2013;13:3.Rodríguez, J., Prieto, S.E., Correa, S.C., Pérez, C.E., & Soracipa, M.Y. (2017). Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal. Rev. Salud. Pública, 19(1):52-59.Samuel, J., Sankhulani, E., Qureshi, J., Baloyi, P., Thupi, C., Lee, C., et al. (2012). Under-reporting of road traffic mortality in developing countries: application of a capture-recapture statistical model to refine mortality estimates. PLoS One, 7,e31091.Van Kampen, N.G. (1992). Stochastic Processes in Physics and Chemistry. Amsterdam: North-Holland Publishing Company.Wangdi, C., Gurung, M.S., Duba, T., Wilkinson, E., Tun, Z.W., et al. (2017). Burden, pattern and causes of road traffic accidents in Bhutan, 2013–2014: a police record review. International Journal of Injury Control and Safety, https://doi.org/10.1080/17457300.2017.1341930Weiss, G. (1994). Aspects and Applications of the Random Walk. Amsterdam: North-Holland Publishing Company.World Health Organization. (2018). Global Status Report on Road Safety. Resource document. https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/. 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Prediction of the incidence of deaths secondary to road traffic injuries in Connecticut and Delaware

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