Lifescience Global




Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation - Pages 181-191

T. Monleón-Getino1,2, C. Puig2, O. Vall2,3, M. Ríos1, A. Chiandetti2 and O. Garcia-Algar2,3

1Department of Statistics, University of Barcelona, Barcelona, Spain; 2Unitat de Recerca Infància i Entorn (URIE), Paediatrics Unit, Hospital del Mar, Barcelona, Spain; 3Department of Paediatrics, Autonomous University of Barcelona, Barcelona, Spain


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    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.

    Keywords: Children, Asthma, Model, Discrete event, Probability, Tobacco.


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