Search

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.

COVID-19 (coronavirus disease 2019) started in late 2019 in Wuhan, China. Subsequently, the disease was disseminated in several cities around the world, where measures were taken to control the spread of the virus through the adoption of quarantine (social isolation and closure of commercial sectors). This article analyzed the environmental impact of the COVID-19 outbreak in the state of Mato Grosso do Sul, Brazil, regarding the variations of nitrogen dioxide (NO2) in the atmosphere. NO2 data from the AURA satellite, in the period before the beginning of the epidemic (2005–2019) and during the adoption of the preventive and control measures of COVID-19 in 2020, were acquired and compared. The results obtained from the analysis showed that the blockade from COVID-19, beginning in March 2020, improved air quality in the short term, but as soon as coal consumption in power plants and refineries returned to normal levels (since June 2020), due to the resumption of works, the pollution levels returned to the level of the previous years of 2020. NO2 levels showed a significant decrease, since they were mainly associated with the decrease in economic growth and transport restrictions that led to a change in energy consumption and a reduction in emissions. This study can complement the scientific community and policy makers for environmental protection and public management, not only to assess the impact of the outbreak on air quality, but also for its effectiveness as a simple alternative program of action to improve air quality.

The climate is described by the predominant atmospheric conditions in a particular region and influences several human activities. In agriculture, water availability defines the growth and yield of crops and can be obtained by the water balance. The climate classification also aids to identify suitable areas for agricultural crops. Thus, the aim of this work was to elaborate the water balance and perform the climate classification through the method of Thornthwaite and Mather (1955) for six weather stations (Bohicon, Cotonou-Airport, Kandi-Airport, Natitingou, Parakou-Airport and Savè) located in Benin, Western Africa. For the execution of this work, monthly series of precipitation and potential evapotranspiration from 1970 to 2015 were used. Once the monthly water balance of the six seasons was elaborated, it was observed that the rainy (dry) period decreases (increases) from the coast (Cotonou-Airport) to the north of Benin (Kandi-Airport) and, coincides with Boreal summer and part of autumn (Boreal winter and part of spring). Regarding the climate classification, the Cotonou-Airport station was characterized as Subhumid Megathermal climate with moderate winter deficit (C2wA’a’); the stations of Bohicon and Savè presented similar climate classification with Subhumid Dry Megathermal climate with low or without water surplus (C1dA’a’); Natitingou with Subhumid Dry climate Megathermal with large summer surplus (C1s2A’a’); Parakou-Airport with Subhumid climate Dry Megathermic with moderate summer surplus (C1sA’a’) and, Kandi-Airport presented Semi-arid Megathermal climate with moderate summer surplus (DsA’a’). In Benin, subsistence and rainfed farming showed greater risk in the north of the country due to the decrease in the rainy season and the water surplus from the coast (south) to the north of the country, with the increase in aridity. The climate is described by the predominant atmospheric conditions in a particular region and influences several human activities. In agriculture, water availability defines the growth and yield of crops and can be obtained by the water balance. The climate classification also aids to identify suitable areas for agricultural crops. Thus, the aim of this work was to elaborate the water balance and perform the climate classification through the method of Thornthwaite and Mather (1955) for six weather stations (Bohicon, Cotonou-Airport, Kandi-Airport, Natitingou, Parakou-Airport and Savè) located in Benin, Western Africa. For the execution of this work, monthly series of precipitation and potential evapotranspiration from 1970 to 2015 were used. Once the monthly water balance of the six seasons was elaborated, it was observed that the rainy (dry) period decreases (increases) from the coast (Cotonou-Airport) to the north of Benin (Kandi-Airport) and, coincides with Boreal summer and part of autumn (Boreal winter and part of spring). Regarding the climate classification, the Cotonou-Airport station was characterized as Subhumid Megathermal climate with moderate winter deficit (C2wA’a’); the stations of Bohicon and Savè presented similar climate classification with Subhumid Dry Megathermal climate with low or without water surplus (C1dA’a’); Natitingou with Subhumid Dry climate Megathermal with large summer surplus (C1s2A’a’); Parakou-Airport with Subhumid climate Dry Megathermic with moderate summer surplus (C1sA’a’) and, Kandi-Airport presented Semi-arid Megathermal climate with moderate summer surplus (DsA’a’). In Benin, subsistence and rainfed farming showed greater risk in the north of the country due to the decrease in the rainy season and the water surplus from the coast (south) to the north of the country, with the increase in aridity.