Viral diseases are among the main public health problems, especially arboviruses, which are among the viruses that most infect humans, with an estimated 3 billion people living in areas at risk of infection. The aim of this research was to evaluate the application of spectroscopic techniques in the detection of arboviruses in Aedes aegypti mosquitoes and clinical samples. In the described studies, on this thesis, molecular fluorescence spectroscopy was applied together with the multivariate analysis techniques PARAFAC-LDA, PARAFAC-QDA, and NPLS-DA, as a new sensitive, specific, fast, simple methodology capable of identifying spectral variations between clinical samples with and without dengue and chikungunya viruses. To get this, Excitation-Emission Matrix (EEM) of 26 samples for each class (healthy x dengue x chikungunya) were used, totaling 78 samples. The samples were divided into calibration and test sets and, after building the models, the results were analyzed based on calculations of accuracy, sensitivity, specificity, and F-score. It was observed that the most efficient model in the classification work was the PARAFAC-QDA, obtaining the maximum value for all the calculated figures. PARAFAC-LDA and NPLS-DA also achieved encouraging results. The loadings captured in PARAFAC were provided and can be used in future studies to prove the relationship (or not) of the spectral data with the presence of viruses. In another study, infrared spectra (NIR and MIR) were used together with the SPA and GA variable selection algorithms, to select wave numbers capable of discriminating female Aedes aegypti mosquitoes infected with dengue (n = 32) from uninfected mosquitoes (n = 66). For this, SPA-LDA and GA-LDA models were constructed for the two techniques (NIR and ATR-FTIR). The built models were evaluated based on sensitivity and specificity calculations, and it was observed that for both SPA-LDA and GA-LDA, the models based on NIR spectra obtained better classification values, reaching 82.65 % of sensitivity and specificity for NIR-SPA-LDA; and 100.00 % for sensitivity and specificity for NIR-GA-LDA. Finally, it was observed that EEM matrices have the potential to be used as screening or diagnosis of arboviruses, having advantages when compared to more conventional techniques, demonstrating that, in the future, it will be possible to rely on portable NIR instruments in the work of entomological surveillance and prediction of dengue outbreaks.