METODOLOGIA PARA CARACTERIZAÇÃO DE ASSINATURA GEOQUÍMICA DE TRAJETOS DE ÁGUA EM ZONAS DE RECARGA DE INTERFLÚVIOS (Methodology for geochemical signature characterization of water paths in interfluves recharge zones)

Apresenta-se uma metodologia para caracterização de assinaturas hidrogeoquímicas de partilha de aquífero entre bacias e de trajetos de água comuns em zonas de recarga de interflúvios. O método baseia-se na coleta e análise de características químicas de águas subterrâneas a partir de fontes. As Bacias de Paracatu, São Marcos, Alto Paranaíba e São Mateus foram investigadas. Palavras-chave: hidrogeoquímica; aqüíferos; recarga; Noroeste de Minas Gerais. ABSTRACT This a proposal of a methodology for the characterization of hydrogeochemistry signature of water ways in interflow recharge zones of neighbouring watersheds. The method is based in the systematic sampling and chemical analysis of underground and sources of water. Paracatu, São Marcos, São Bartolomeu and Alto Paranaíba watersheds were chemically investigated. Keywords: hydrogeochemistry; aquifer; recharge; Northwestern Minas Gerais State. RESUMEN Se propone una metodología para la caracterización de las firmas hidrogeoquímicas en los trayectos de las aguas en las zonas de recarga interfluviales. El método se basa en el muestreo de las aguas subterráneas y en las fuentes con en el análisis de sus características químicas. Las cuencas de los ríos Paracatu, São Marcos, Alto Paranaíba y São Marcos fueron investigadas. Palabras clave: hidrogeoquímica; acuíferos; recarga; Noroeste del Estado de Minas Gerais. DOI: 10.5654/actageo2013.0714.001

METODOLOGIA PARA CARACTERIZAÇÃO DE ASSINATURA GEOQUÍMICA DE TRAJETOS DE ÁGUA EM ZONAS DE RECARGA DE INTERFLÚVIOS (Methodology for geochemical signature characterization of water paths in interfluves recharge zones)

Apresenta-se uma metodologia para caracterização de assinaturas hidrogeoquímicas de partilha de aquífero entre bacias e de trajetos de água comuns em zonas de recarga de interflúvios. O método baseia-se na coleta e análise de características químicas de águas subterrâneas a partir de fontes. As Bacias de Paracatu, São Marcos, Alto Paranaíba e São Mateus foram investigadas. Palavras-chave: hidrogeoquímica; aqüíferos; recarga; Noroeste de Minas Gerais. ABSTRACT This a proposal of a methodology for the characterization of hydrogeochemistry signature of water ways in interflow recharge zones of neighbouring watersheds. The method is based in the systematic sampling and chemical analysis of underground and sources of water. Paracatu, São Marcos, São Bartolomeu and Alto Paranaíba watersheds were chemically investigated. Keywords: hydrogeochemistry; aquifer; recharge; Northwestern Minas Gerais State. RESUMEN Se propone una metodología para la caracterización de las firmas hidrogeoquímicas en los trayectos de las aguas en las zonas de recarga interfluviales. El método se basa en el muestreo de las aguas subterráneas y en las fuentes con en el análisis de sus características químicas. Las cuencas de los ríos Paracatu, São Marcos, Alto Paranaíba y São Marcos fueron investigadas. Palabras clave: hidrogeoquímica; acuíferos; recarga; Noroeste del Estado de Minas Gerais. DOI: 10.5654/actageo2013.0714.001

Dengue Fever Occurrence and Vector Detection by Larval Survey, Ovitrap and MosquiTRAP: A Space-Time Clusters Analysis

<div><p>The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector <em>Aedes (Stegomyia) aegypti</em> was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools.</p> </div

Ovitrap-annual results of <i>Aedes sp.</i> monitoring. 2007–2008.

1<p>OPI  =  Ovitrap Positivity Index;</p>2<p>EDI  =  Eggs Density Index.</p

MosquiTRAP-annual results of <i>Aedes aegypti</i> monitoring. 2007–2008.

1<p>MPI  =  MosquiTRAP Positivity Index;</p>2<p>MFAI  =  Mean Female Aedes Index.</p

Meteorological data of Belo Horizonte, Minas Gerais, Brazil, January 1^st, 2007 to June 30^th, 2008.

<p>Demonstrates two different seasons, a warmer and umid summer and a dry winter with mild temperatures. Average Temperature: 25,17±3,66°C (black), Highest Temperature: 27,08±3,17°C (dash black); Lower Temperature: 17,74±4,01°C (dash gray); Precipitation average: 2,41±7,03 mm³ (blue). <i>Source: CPTEC/INPE</i>.</p

Distribution of collected data along the study period.

<p>The graphic shows the number of registries by week for each dataset, dengue fever cases (red), positive MosquiTRAPs (dash green), positive ovitraps (blue) and positive larval surveys (yellow).</p

Clusters reliability maps.

<p><b>A</b>: Dengue fever clusters; <b>B</b>: Positive larval survey clusters; <b>C</b>: Positive ovitrap clusters Positive; <b>D</b>: MosquiTRAP clusters. Dark colors represents higher reliability values (<i>Ri</i>).</p