Abstract Dengue is a viral disease whose number of cases has increased in Brazil. This study aimed to characterize the spatio-temporal distribution patterns of the reported dengue infection cases in the state of Alagoas (AL), Northeastern Brazil (NEB). The data of the officially reported dengue cases from 2000 to 2015 was retrieved from the State Health Secretariat of Alagoas (SESAL), which captures national demographic and health data from the System for the Reporting of Notifiable Conditions (SINAN). After applying the Kernel Density Estimation (KDE) function, maps were generated based on the Inverse Distance Weighting (IDW) interpolation method. By using the clusters analysis (CA) technique, three homogeneous groups of dengue in AL were determined. Next, the LN (Lognormal), GUM (Gumbel) and GEV (Generalized Extreme Value) probability distributions were applied to monthly model dengue case data in AL, with the LN continuous probability distribution standing out. Maceió and Arapiraca have a higher number of dengue cases than other cities, being the main reason for their interpretation as separate groups. The coefficients of determination (R2) of dengue cases analysis as a function of month of each year for the studied years were low (between 0.03 and 0.63) and many regression slopes were not significant. Pearson's correlation coefficient (r) between dengue and the Human Development Index (HDI) of LA was considered moderate (0.53) and the correlation between dengue and demographic density was high (0.76). The importance of constant monitoring and assistance for these areas is reinforced.

Abstract The climatic zones of Mato Grosso do Sul (MS) were defined based on the mathematical methodology of cluster analysis (CA). Data from 77 climatic seasons of average annual temperatures (maximum and minimum) and total annual precipitation data from 1978 to 2013 were used, and hierarchical (Ward) and partitional or non-hierarchical (k-means) CA algorithms were chosen, as two of the most used approaches, to carry out the regionalization. The optimum number of clusters in which the data can be grouped was determined by the statistical methods of elbow, silhouette and gap. The stability of the clusters is also tested by statistical approaches and four homogeneous groups were found, as in conventional climatic zones, but with considerable border differences. Pearson's correlation coefficient (r) between the series in each cluster helps to understand the dynamics of these clusters. The hierarchical cluster analysis and the elbow method for the optimal number of clusters was the most appropriate and satisfactory and was able to train and validate homogeneous regions of climate in the state of Mato Grosso do Sul. The efficient application of these methodologies is confirmed by the delimitation of four distinct clusters (homogeneous regions of climate), consistent with recorded heights and temperatures (maximum and minimum) and geographical characteristics as topography, in the state of Mato Grosso do Sul.

Resumo Este trabalho objetiva avaliar a aplicação do Standardized Precipitation Index (SPI) para as escalas mensal (SPI-1), trimestral (SPI-3) e anual (SPI-12) para a vertente paranaense da bacia hidrográfica do rio Itararé (BHRI). Foram utilizados os dados pluviométricos de catorze postos pluviométricos obtidos do Instituto das águas do Paraná e pelo Instituto Agronômico do Paraná para o período de 1976 a 2012 na avaliação espaço-temporal do SPI desenvolvido por McKee et al. (1993). Verificou-se que 71,1% dos anos foram categorizados como próximo ao normal (SPI-12) e, entretanto, para o período entre julho a setembro verificou-se um aumento significativo das secas na BHRI, segundo o SPI-3 e o SPI-1. No outono e inverno verificou-se a maior frequência nas categorias de seca, enquanto que na primavera predominou a normalidade e no verão as categorias úmidas foram mais expressivas. A utilização do índice SPI para diferentes escalas demonstrou que, embora a escala SPI-12 tenha predominado a categoria próxima ao normal, as escalas SPI-3 e SPI-1 mostraram com maior acurácia os períodos de maior susceptibilidade às secas na BHRI.

Abstract This paper aims to evaluate the application of the Standardized Precipitation Index (SPI) for the monthly (SPI-1), quarterly (SPI-3) and annual (SPI-12) scales for Paraná slope of the Itararé watershed (PSIW). Were used the rainfall data from fourteen pluviometric stations obtained from the Paraná Water Institute and the Paraná Agronomic Institute for the period between 1976 to 2012 in the spatiotemporal evaluation of SPI developed by McKee et al. (1993). The interannual variability of SPI-12 and the relative frequency of SPI-3 and SPI-1 categories were evaluated. It was verified that 71.1% of the years were classified as close to normal and however, from July to September there was a significant increase in droughts in the PSIW according to SPI-3 and SPI-1. In the autumn and winter the highest frequency was observed in the categories of drought, whereas in the spring normality prevailed and in the summer the humid categories were more expressive. The use of the SPI index for different scales showed that although the SPI-12 scale prevailed in the normality category, the SPI-3 and SPI-1 scales showed more accurately the quarters and months of greater susceptibility to droughts in the PSIW.