Identification of key areas for Aedes aegypti control through geoprocessing in Nova Iguaçu, Rio de Janeiro State, Brazil

Lagrotta, Marcos Thadeu Fernandes; Silva, Wellington da Costa; Souza-Santos, Reinaldo

doi:10.1590/s0102-311x2008000100007

Cited by 54 publications

(50 citation statements)

References 19 publications

(21 reference statements)

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“…aegypti in real time, as compared to other georeferenced studies that used sampling of immature forms of the mosquito 13,14,15,16,17,18 (eggs and larvae), which demand time and infrastructure for identification, quantification, and data processing. The georeferenced maps produced by MI-Dengue and provided weekly on the Internet allowed municipal health managers to identify city blocks by colors (green, yellow, orange, and red) according to the number of female Ae.…”

Section: Discussionmentioning

confidence: 99%

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Preliminary evaluation of the "Dengue-MI" technology for Aedes aegyptimonitoring and control

Eiras

Resende

2009

Cad. Saúde Pública

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Section: Discussionmentioning

confidence: 99%

“…aegypti larvae 13,14,15,16 and eggs 17,18 in urban areas. The field data collected by larval surveys, ovitraps, and the Nasci aspirator are recorded on printed spreadsheets, usually attached to a clipboard by field inspectors.…”

Section: Introductionmentioning

confidence: 99%

Preliminary evaluation of the "Dengue-MI" technology for Aedes aegyptimonitoring and control

Eiras

Resende

2009

Cad. Saúde Pública

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“…4), where there is limited access to water, high population density high building density, and low neighbourhood quality. Several studies (Honório et al, 2003;Lagrotta et al, 2008;Siqueira-Junior et al, 2008;, found that Aedes mosquitoes and DF risk cases increase in areas with high human population density and high concentrations of dwellings. Similar results were also found by da Costa and Natal (1998), who stated that people from low socioeconomic backgrounds are more affected and at a greater risk of contracting DF.…”

Section: Discussionmentioning

confidence: 99%

Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment

Khormi

Kumar

2012

Geospat Health

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Abstract. An important option in preventing the spread of dengue fever (DF) is to control and monitor its vector (Aedes aegypti) as well as to locate and destroy suitable mosquito breeding environments. The aim of the present study was to use a combination of environmental and socioeconomic variables to model areas at risk of DF. These variables include clinically confirmed DF cases, mosquito counts, population density in inhabited areas, total populations per district, water access, neighbourhood quality and the spatio-temporal risk of DF based on the average, weekly frequency of DF incidence. Out of 111 districts investigated, 17 (15%), covering a total area of 121 km², were identified as of high risk, 25 (22%), covering 133 km², were identified as of medium risk, 18 (16%), covering 180 km², were identified as of low risk and 51 (46%), covering 726 km², were identified as of very low risk. The resultant model shows that most areas at risk of DF were concentrated in the central part of Jeddah county, Saudi Arabia. The methods used can be implemented as routine procedures for control and prevention. A concerted intervention in the medium-and high-risk level districts identified in this study could be highly effective in reducing transmission of DF in the area as a whole.

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“…Además de determinar prioridades de acción, este tipo de estudios permiten identificar la población humana en riesgo y los factores favorables en el establecimiento de poblaciones densas de esta especie de mosquito (14).…”

Section: Discussionunclassified

“…Las características de estas técnicas de geoprocesamiento hacen de ellas herramientas poderosas en la planificación, la vigilancia y la evaluación de los programas de control. Muchos países han adoptado el análisis espacial de indicadores entomológicos dirigido a vigilar y controlar las poblaciones de vectores, principalmente en África, donde estas técnicas se orientan a mosquitos del género Anopheles, aunque los pocos estudios enfocados a A. aegypti han resultado promisorios en lo que respecta a vigilancia entomológica (13)(14)(15).…”

Section: Discussionunclassified

Uso de la función semivariograma y estimación kriging en el análisis espacial de un indicador entomológico de Aedes aegypti (Diptera: Culicidae)

Niño¹

2008

biomedica

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Introducción. Aedes aegypti es el principal vector del dengue en América. La prevención y control de esta enfermedad requieren de nuevas técnicas de vigilancia para este mosquito. El análisis de la distribución espacial de estas poblaciones puede llegar a jugar un papel importante en la planificación y evaluación de medidas orientadas a la disminución del contacto vector-hombre. Objetivo. Analizar y representar gráficamente el patrón de variación espacial del indicador aédico correspondiente al índice de recipientes, definido como el porcentaje de depósitos con agua infestados con larvas de A. aegypti. Materiales y métodos. Se realizaron encuestas sobre larvas en la totalidad de las viviendas del barrio La Independencia (Acacías, Meta) en mayo de 2007, con las cuales se calcularon los índices de recipientes en cada manzana. La metodología empleada en el análisis de este indicador correspondió a la estadística espacial, concretamente a la función semivariograma junto con estimaciones kriging. Resultados. El semivariograma experimental obtenido se ajustó al modelo matemático de Gauss, cuya meseta se calculó en 5,1, el rango en 57,1 m y la pepita en 0,09. Se construyó una gráfica bidimensional de la estimación kriging que permitió identificar las manzanas con mayores índices de recipientes. Conclusión. El análisis y la representación gráfica de la distribución del índice de recipientes pueden ser útiles en la vigilancia, la toma y la evaluación de acciones contra la infestación de A. aegypti. Palabras clave:Aedes aegypti, modelos estadísticos, vigilancia epidemiológica, vectores de enfermedades, mapa de riesgo, Colombia. Use of the function semivariogram and kriging estimation in the spacial analysis of Aedes aegypti (Diptera: Culicidae) distributionsIntroduction. Aedes aegypti is the main vector of dengue in the Americas. The prevention and control of this disease require new monitoring techniques for this mosquito. Knowledge of the spatial and temporal distributions of A. aegypti populations allow the planning and evaluation of measures to decrease the vector-human contact. Objective. The spatial variation pattern of the A. aegypti container index (defined as the percentage of artificial containers infested with A. aegypti larva) was analyzed for the purpose of developing a graphical representation. Materials and methods. Larval surveys were undertaken in every household of La Independencia neighborhood in May 2007 (Acacías-Meta). Spatial statistics employing the semivariogram function and kriging estimations were applied to these data. Results. The experimental semivariogram output was adjusted to the gaussian mathematical model, whose sill was calculated to be 5.1, the range as 57.1 meters and the nugget as 0.01. A bidimensional graph of the kriging estimation was built, allowing the identification of the urban areas with highest container index. Conclusion. The analysis of the container index and distribution map provided a useful tool in monitoring, evaluating and making control decisions concerning A. aegypt...

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Identification of key areas for Aedes aegypti control through geoprocessing in Nova Iguaçu, Rio de Janeiro State, Brazil

Abstract: This study discusses the use of geoprocessing to identify key areas for

Cited by 54 publications

References 19 publications

Preliminary evaluation of the "Dengue-MI" technology for Aedes aegyptimonitoring and control

Preliminary evaluation of the "Dengue-MI" technology for Aedes aegyptimonitoring and control

Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment

Uso de la función semivariograma y estimación kriging en el análisis espacial de un indicador entomológico de Aedes aegypti (Diptera: Culicidae)

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