Data analysis
The general characteristics of subjects were described according to the median, ranges, frequencies, and percentages. A Conditional inference tree, a non-parametric multivariate regression model, using thepartykit library of R 3.5.1 software, was applied to classify groups according to the presence of any adverse outcomes potentially related to ZIKV infection (miscarriages, stillbirths, microcephaly with or without brain abnormities, and brain abnormalities without microcephaly) from gestational age25. In general, this method selects, among independent variables, the ones that better classifies the individuals according to the presence of the outcome. In the next step, the algorithm considers all the independent variables to select another (or the same variable previously selected but estimating different cut-off from the first step) that better classifies the individuals according to the outcome and the process extends until there are no more variables selected. The independent variable used by us in these analyses was the gestational age. The same method was used to classify groups more likely to present a typical CZS phenotype as a function of gestational age. Log-binomial regression models were adjusted to estimate relative risks and their respective 95% confidence intervals. Data were analyzed using SPSS software version 20.0.