20 resultados para Interval model
Resumo:
OBJECTIVE: Sensitivity analysis was applied to a mathematical model describing malaria transmission relating global warming and local socioeconomic conditions. METHODS: A previous compartment model was proposed to describe the overall transmission of malaria. This model was built up on several parameters and the prevalence of malaria in a community was characterized by the values assigned to them. To assess the control efforts, the model parameters can vary on broad intervals. RESULTS: By performing the sensitivity analysis on equilibrium points, which represent the level of malaria infection in a community, the different possible scenarios are obtained when the parameters are changed. CONCLUSIONS: Depending on malaria risk, the efforts to control its transmission can be guided by a subset of parameters used in the mathematical model.
Resumo:
OBJECTIVE: To introduce a fuzzy linguistic model for evaluating the risk of neonatal death. METHODS: The study is based on the fuzziness of the variables newborn birth weight and gestational age at delivery. The inference used was Mamdani's method. Neonatologists were interviewed to estimate the risk of neonatal death under certain conditions and to allow comparing their opinions and the model values. RESULTS: The results were compared with experts' opinions and the Fuzzy model was able to capture the expert knowledge with a strong correlation (r=0.96). CONCLUSIONS: The linguistic model was able to estimate the risk of neonatal death when compared to experts' performance.
Resumo:
OBJECTIVE: Low birth weight children are unusual among well-off families. However, in Brazil, low birth weight rate was higher in a more developed city than in a less developed one. The study objective was to find out the reasons to explain this paradox. METHODS: A study was carried out in two municipalities, Ribeirão Preto (Southeastern Brazil) and São Luís (Northeastern Brazil), which low birth weight rates were 10.7% and 7.6% respectively. Data from two birth cohorts were analyzed: 2,839 newborns in Ribeirão Preto in 1994 and 2,439 births in São Luís in 1997-1998. Multiple logistic regression analysis was performed, adjusted for confounders. RESULTS: Low birth weight risk factors in São Luís were primiparity, maternal smoking and maternal age less than 18 years. In Ribeirão Preto, the associated variables were family income between one and three minimum wages, maternal age less than 18 and equal to or more than 35 years, maternal smoking and cesarean section. In a combined model including both cohorts, Ribeirão Preto presented a 45% higher risk of low birth weight than São Luís. When adjusted for maternal smoking habit, the excess risk for low birth weight in Ribeirão Preto compared to São Luís was reduced by 49%, but the confidence interval was marginally significant. Differences in cesarean section rates between both cities contributed to partially explain the paradox. CONCLUSIONS: Maternal smoking was the most important risk factor for explaining the difference in low birth weight between both cities. The other factors contributed little to explain the difference in low birth weight rates.
Resumo:
The objective of the study was to compare information collected through face-to-face interviews at first time and six years later in a city of Southeastern Brazil. In 1998, 32 mothers (N=32) of children aged 20 to 30 months answered a face-to-face interview with structured questions regarding their children's brushing habits. Six years later this same interview was repeated with the same mothers. Both interviews were compared for overall agreement, kappa and weighted kappa. Overall agreement between both interviews varied from 41 to 96%. Kappa values ranged from 0.00 to 0.65 (very bad to good) without any significant differences. The results showed lack of agreement when the same interview is conducted six years later, showing that the recall bias can be a methodological problem of interviews.