Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/49345
Title: Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation
Author: Monleón Getino, Toni
Puig, C.
Vall, O.
Ríos Alcolea, Martín
Chiandetti, A.
García Algar, Óscar
Keywords: Models matemàtics
Estadística mèdica
Asma infantil
Asma
Mathematical models
Medical statistics
Asthma in children
Asthma
Issue Date: 1-Dec-2013
Publisher: Lifescience Global
Abstract: Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.
Note: Reproducció del document publicat a: http://dx.doi.org/10.6000/1929-6029.2013.02.03.2
It is part of: International Journal of Statistics in Medical Research, 2013, vol. 2, p. 181-191
Related resource: http://dx.doi.org/10.6000/1929-6029.2013.02.03.2
URI: http://hdl.handle.net/2445/49345
ISSN: 1929-6029
Appears in Collections:Articles publicats en revistes (Genètica, Microbiologia i Estadística)

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