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Objective: To evaluate the incidence of variant hemoglobins of newborn samples from the Neonatal Screening Center in the state of Mato Grosso do Sul, Brazil, and to analyze the distribution and spatial autocorrelation of newborns with sickle cell trait., Methods: Samples from 35,858 newborns screened by the Neonatal Screening Center. The samples with inconclusive diagnosis were submitted to electrophoretic, chromatographic, cytological and molecular analyses. The spatial distribution analysis of newborns with sickle cell trait was performed by spatial autocorrelation., Results: A total of 919 newborns showed an abnormal hemoglobin profile; in that, ten genotypes had significant clinical impacts identified. Among the asymptomatic newborns, the sickle cell trait was the most frequent (incidence of 1.885 cases/100 newborns). The highest incidence rates were registered in the municipalities of Terenos, Figueirão, Corguinho and Selvíria. There was positive spatial autocorrelation between the proportion of declared individuals of black race/color and the incidence of newborns with sickle cell trait., Conclusion: The early diagnosis by neonatal screening and laboratory tests was very important to identify abnormal hemoglobin profiles and guide the spatial autocorrelation analysis of sickle cell trait newborns in Mato Grosso do Sul, serving as a support to anticipate health measures aimed to discuss efficient therapeutic behaviors and effective planning of municipalities with the greatest need for care, monitoring and orientations for affected families.

In the last 30 years, the growth of the agriculture and livestock industries in the Cerrado biome has caused severe changes in land use and land cover (LULC), and areas previously occupied by native vegetation are changing to agricultural monocultures (e.g., soybean or corn) and/or pastures. Thus, the objective of this study was to analyze the LULC changes for the years 1986, 1999, 2007, and 2016 based on Landsat time series and object-based image analysis (OBIA) for the Prata River Basin. Twelve LULC classes were mapped: riparian forest, cerrado, swampy grasslands, wetlands, semideciduous forest, pasture, agriculture, fallow agricultural land, barren land, eucalyptus, water bodies, and burnt area. The classifications presented results with an overall accuracy of more than 93% and a kappa coefficient of 0.92. In 2007, the pasture class had the highest increase in area (48.5%), with a total area of 118.32 km 2 of Cerrado biome vegetation converted to pasture, and the classes banhado, riparian forest, swampy grasslands, and cerrado had the greatest reductions in area (41.58%, 29.67%, 25.44%, and 21.63%, respectively). More precisely, the wetlands class underwent the greatest decrease under the advancement of pasture in the studied period (- 36.2%). These changes are due to factors favorable to agropastoral practices, such as a flat relief and soil with good agricultural suitability. Graphical abstract.