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.

Resumo Os incêndios ocorrem devido às ações antrópicas e causam problemas socioambientais no Nordeste do Brasil (NEB). Portanto, este estudo avaliou a variabilidade espaço-temporal dos focos de calor (FC) nas três mesorregiões climáticas de Alagoas: Sertão, Leste e Agreste Alagoano. Os dados de FC foram obtidos do Banco de Dados de Queimadas (BDQueimadas) entre 1998-2020. A série temporal de FC foi submetida às análises estatísticas descritiva, exploratória e multivariada aplicada aos 102 municípios alagoanos. Com base no agrupamento hierárquico identificaram-se três grupos homogêneos (G1, G2 e G3) no Sertão e dois grupos homogêneos de FC no Agreste e Leste Alagoano (G1 e G2). Alguns municípios não formaram grupos (NA), tais como: Belo Monte (26,83 ± 25,87 focos), Limoeiro de Anadia (54,48 ± 38,65 focos), Penedo (262,83 ± 183,80 focos) e Coruripe (553 ± 369,40 focos). A variabilidade interanual dos FC em Alagoas está associada com atividades agrícolas, desmatamento, novas áreas para a criação de animais e colheita da cana-de-açúcar. Na avaliação espacial via densidade de FC por município utilizou-se o período total (1998-2020) e os anos de destaque na série temporal (2012 e 2019). O maior registro de densidade de FC no período total encontra-se na mesorregião do Leste Alagoano e não se descarta que os anos em destaque sejam influenciados pela ocorrência de seca e períodos de estiagens em Alagoas.

Abstract Fires occur due to anthropic actions and cause socio-environmental problems in Northeast Brazil (NEB). Therefore, this study evaluated the spatiotemporal variability of fire focis (FF) in the three climatic mesoregions of Alagoas: Arid Zone, East and Hinterland Alagoano. FF data were obtained from the Queimadas Database (BDQueimadas) between 1998-2020. The FF time series was submitted to descriptive, exploratory, and multivariate statistical analysis applied to 102 municipalities in Alagoas. Based on the hierarchical grouping, three homogeneous groups were identified (G1, G2 and G3) in the Arid Zone and two homogeneous groups of FF in the Hinterland and East Alagoas (G1 and G2). Some municipalities did not form groups (NA), such as: Belo Monte (26.83 ± 25.87 foci), Limoeiro de Anadia (54.48 ± 38.65 foci), Penedo (262.83 ± 183.80 foci) and Coruripe (553 ± 369.40 foci). The interannual FF variability in Alagoas is associated with agricultural activities, deforestation, new areas for animal husbandry and sugarcane harvest. In the spatial evaluation via FF density per municipality, the total period (1998-2020) and the years highlighted in the time series (2012 and 2019) were used. The highest FF density record in the total period is found in the East Alagoas mesoregion and it is not ruled out that the highlighted years are influenced by the occurrence of drought and dry periods in Alagoas.

Resumo O objetivo deste trabalho é avaliar os parâmetros biofísicos, chuva e a temperatura de superfície nas condições da vegetação, no Parque Nacional da Serra das Confusões (PNSC), Piauí-NEB. Com auxílio das imagens obtidas do satélite Landsat 8 foi possível calcular o Normalized Difference Vegetation Index (NDVI) e a temperatura de superfície (Ts). A chuva do PNSC apresentou sazonalidade bem definida, estações seca e chuvosa. Ambas as estações têm papel crucial nas condições da vegetação do PNSC. A classe de NDVI (>0,693) apresentou a maior redução da área de cobertura do PNSC próximo de 72,7%, enquanto que as classes (0,347-0,433) e (0,433-0,52) tiveram um aumento de 34,7% e 31,8%, respectivamente. Além disso, ficou claro que as condições da vegetação influenciam na Ts da região.

Abstract The objective of this work is to evaluate the biophysical parameters, rainfall and surface temperature in the vegetation conditions, in the Serra das Confusões National Park (SCNP), Piau-NEB. With the aid of the images obtained from the satellite Landsat 8 it was possible to calculate the Normalizes Difference Vegetation Index (NDVI) and the surface temperature (Ts). The SCNP rainfall presented a well-defined seasonality, dry and rainy seasons, which play a crucial role in the vegetation conditions of the SCNP. The NDVI class (> 0.693) had the greatest reduction o the coverage area around 72.7%, while the classes (0.347-0.433) and (0.433-0.52) had an increase of 34.7% and 31, 8%, respectively. In addition, it was clear that vegetation condition influenced the Ts of the region.

Resumo Este trabalho avaliou as queimadas e os incêndios na Região Metropolitana de Maceió (RMM) via dados de focos de calor (FC) disponíveis no BQueimadas para no período de 1999 a 2019. A série temporal de focos calor foi submetida às análises estatísticas descritivas e multivariadas (Análise de Agrupamento - AA) juntamente com Vegetation Health Index (VHI) aplicadas aos FC nos municípios da RMM. Com base no agrupamento hierárquico identificaram-se três grupos homogêneos (G1, G2 e G3) de FC e o município de Atalaia que não se agrupou (NA). Os Grupos G1 (145,5 ± 7,77 FC) e G2 (28,5 ± 44 FC) apresentaram similaridades quanto à sazonalidade dos FC. Enquanto o Grupo G3 (91 ± 7,07 FC) que inclui a capital Maceió, apresentou distribuição irregular espacialmente. Toda a variabilidade dos FC está associada às atividades agrícolas vigentes na RMM. Mas também, à negligência de ateio de material inflamável sobre a vegetação propicia aumento de incêndios e queimadas, principalmente na colheita da cana-de-açúcar.

Abstract This work evaluated the burnings and fires in the Maceió Metropolitan Region (MMR) via Fire Foci (FF) data available in BQueimadas for the period 1999 to 2019. The FF time series was submitted to descriptive and multivariate statistical analysis (Cluster Analysis - CA) together with the Vegetation Health Index (VHI) applied to the fire foci in the municipalities of MMR. Based on the hierarchical grouping, three homogeneous groups (G1, G2 and G3) of FF were identified and the municipality of Atalaia was not grouped (NA). Groups G1 (145.5 ± 7.77 FF) and G2 (28.5 ± 44 FF) presented similarities regarding the seasonality of the foci. While Group G3 (91 ± 7.07 FF), which includes the capital Maceió, presented irregular distribution spatially. All the variability of the FF is associated with the agricultural activities in the MMR. But also, the negligence of atheism of flammable material on the vegetation propitiates an increase of fires and burns, mainly in the sugarcane harvest.

Resumo A escassez de dados pluviográficos em Alagoas, similar em muitas regiões do país, faz com que utilizem equações de regressão obtidas em outras regiões do Brasil para calcular o fator R da Equação Universal de Perda de Solo. O estudo tem por objetivos: i) definir uma equação para estimar a erosividade das chuvas baseada no índice EI30 e no coeficiente de chuva Rc, ii) validar o método de imputação de dados para a chuva e erosividade e iii) estimar espacialmente a erosividade nos períodos chuvoso, seco e transição para Alagoas. Utilizaram-se dados pluviométricos mensais de 54 estações no período (1960-2016). A equação utilizada apresentou correlação significativa entre os dados observados e estimados, de acordo com os coeficientes r (93%), R2 (87%) e RMSE (775,2 MJ.mm.ha−1.h−1.ano−1). A Krigagem Ordinária foi o melhor interpolador espacial. A isoerosividade mensal mostrou que os maiores índices de EI30 ocorreram entre abril e julho, período coincidente com a quadra chuvosa do estado. Na erosividade anual, os maiores registros estão situados no Leste Alagoano, próximas ao litoral. Destaque para as estações Satuba, Maceió, São Luiz do Quitunde e Flexeiras, categorizadas entre moderada e forte. Estes resultados auxiliarão no planejamento de práticas conservacionistas, principalmente em áreas de vulnerabilidade.

Abstract The lack of rainfall data in Alagoas, similar in many regions of the country, makes them use regression equations obtained in other regions of Brazil to calculate the R factor of the Universal Soil Loss Equation. The study aims to: i) define an equation to estimate rainfall erosivity based on the EI30 index and the rain coefficient Rc, ii) validate the data imputation method for rain and erosivity and iii) spatially estimate erosivity in rainy, dry and transition periods to Alagoas. Monthly rainfall data from 54 stations in the period (1960-2016) were used. The equation used showed a significant correlation between the observed and estimated data, according to the coefficients r (93%), R2 (87%) and RMSE (775.2 MJ.mm.ha−1.h−1). The Ordinary Kriging was the best spatial interpolator. The monthly isoerosivity showed that the highest EI30 rates occurred between April and July, a period coinciding with the rainy season in the state. In annual erosivity, the largest records are located in eastern Alagoas, close to the coast. Highlight for the stations Satuba, Maceió, São Luiz do Quitunde and Flexeiras, categorized between moderate and strong. These results will assist in planning conservation practices, especially in areas of vulnerability.

Abstract INTRODUCTION: Meteorological influences along with the lack of basic sanitation has contributed to disease outbreaks, resulting in large socio-economic losses, especially in terms of dengue. This study aimed to evaluate the meteorological influences on the monthly incidence of dengue in Arapiraca-AL, Brazil during 2008-2015. METHODS: We used generalized linear models constructed via logistic regression to assess the association between the monthly incidence of dengue (MID) of and 8 meteorological variables [rainfall (R), air temperature (AT), dew point temperature (DPT), relative humidity (RH), pressure surface, wind speed (WS), wind direction (WD), and gust], based on data obtained from DATASUS and meteorological station databases, respectively. The dengue-1 model included R, AT, DPT, and RH and the dengue-2 model included AT, DPT, RH, WS, and WD. A MID >100 (classified as moderate incidence) indicated an abnormal month. RESULTS: Based on the dengue-1 model, variables with the highest odds ratio included R-lag1, DPT-lag1, and AT-lag1 with a 10.1, 18.3, and 26.7 times greater probability of a moderate MID, respectively. Based on the dengue-2 model, variables with the highest odds ratio were AT-lag1 and RH-lag0 indicating an 8.9 and 18.1 times greater probability of a moderate MID, respectively. CONCLUSIONS: AT, DPT, R, RH and WS influenced the occurrence of a moderate MID.