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the particularity of this study is related to the number of case, which exceeds 140 000 cases, a value never seen in any other brazilian state. the large number of cases was not only caused by an increase in the number of dengue cases in the state. our data show that the number of cases, in 2007, was already high, with 5598 cases. this result was obtained even though it was the first year of implementation of the dengue program in the state of ceará. this series of cases was confirmed by a seroprevalence study performed in 2009, in which 9.2% of the study subjects had dengue, suggesting a higher incidence than that observed in the past decade [ 42 ].
in this work, we used the time series of dengue cases to (1) determine, through the evaluation of the signal to noise ratio, the optimal parameters to use for the periodogram and (2) to estimate the interannual and intraannual variability of the time series, respectively. we also applied statistical tests to evaluate the goodness of the estimated spectrum. in addition, we estimated the dengue incidence in the state of ceará in different periods. our research is focused on the introduction of a new method and the creation of a website that provides the results of the analyses of the dengue epidemic time series, so that the cases in fortaleza are not diagnosed locally, but are sent for confirmation to the reference laboratory, professor da hércio pessôa of the oswaldo cruz foundation (fiocruz).
the evaluation of the signal to noise ratio (snr) refers to the ratio between the relevant components of the whole spectrum (signal) and the noise. the noise here consists of random frequencies, noise, and low-frequency random variations. to select the optimal spectrum, we performed three preprocessing steps (shown in figure 2): (1) low-pass filtering; (2) mean correction, as the case may be; and (3) normalization. the first preprocessing step consisted of filtering the time series by a low-pass filter, as shown in figure 3. figure 2. three preprocessing steps.
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