RESUMO
The use of near-infrared spectroscopy (NIRS) based on a low-cost portable instrument for monitoring the quality of the three major formulations of ethanol-based hand sanitizers used for prevention against CoVID-19 disease is described. The quality of the sanitizers was evaluated using two approaches. In the first, a qualitative method was developed to identify gross non-conformities, using NIR spectral data compression by principal components analysis and projection of the spectrum of the tested sample in the principal component space delimited by samples of sanitizers prepared in the laboratory. In the second, a quantitative method was designed to determine the active substance (ethanol) employing multivariate regression based on partial least squares. The results demonstrate that the first approach can be used to detect non-conformities in the sanitizer composition, mostly associated with incorrect ethanol content. The second explores the use of NIRS for determination of the ethanol content in the three formulations aiming the quality control of the sanitizer manufacturing process. The ethanol content can be determined with an absolute root mean square error of prediction (RMSEP) equal to 0.68% (m/m), 0.83% (m/m) and 1.0% (v/v) for the three formulations evaluated. The RMSEP was estimated as 1.3% (m/m) for the commercial products. The measurement protocol takes approximately 1 min and requires only about 120 µL of a sample. Besides, NIRS was employed to compare the rate of volatilization of the ethanol in the different formulations, an important parameter concerning the efficacy of ethanol-based sanitizers.
RESUMO
Vaccinia virus (VACV), the etiological agent of bovine vaccinia (BV), is widespread in Brazil and present in most of the milk-producing regions. We conducted a horizontal study of BV in Bahia, a state of Brazil in which the production of milk is increasing. During 2011, human and bovine clinical samples were collected during outbreaks for BV diagnosis, virus isolation and molecular analysis. We collected data for epidemiological inferences. Vaccinia virus was detected in 87.7% of the analyzed outbreaks, highlighting the effective circulation of VACV in Bahia. The molecular data showed the spreading of group 1 Brazilian VACV to Bahia. We observed a seasonal profile of BV, with its peak in the drier and cooler season. Manual milking was observed in 96 % of the visited properties, showing its importance to viral spread in herds. Under-notification of BV, ineffective animal trade surveillance, and bad milking practices have contributed to the spread of VACV in Brazil.