Habitat suitability mapping of Anopheles darlingi in the surroundings of the Manso hydropower plant reservoir, Mato Grosso, Central Brazil

Zeilhofer, Peter; Santos, Emerson Soares dos; Ribeiro, Ana Lúcia Maria; Miyazaki, Rosina Djunko; Santos, Marina Atanaka dos

doi:10.1186/1476-072x-6-7

Cited by 42 publications

(59 citation statements)

References 33 publications

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“…Females of An. darlingi, main malaria vector in the Amazon region, generally search for places with permanent clean water and relatively covered by vegetation for oviposition (Zeilhofer et al 2007).…”

Section: Fusarium Sppmentioning

confidence: 99%

Filamentous fungi associated with mosquito larvae (Diptera: Culicidae) in municipalities of the Brazilian Amazon

Pereira¹,

Sarquis²,

Ferreira-Keppler³

et al. 2009

Neotrop. entomol.

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Section: Fusarium Sppmentioning

confidence: 99%

Filamentous fungi associated with mosquito larvae (Diptera: Culicidae) in municipalities of the Brazilian Amazon

Pereira¹,

Sarquis²,

Ferreira-Keppler³

et al. 2009

Neotrop. entomol.

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“…Malaria risk mapping is traditionally obtained through various statistical techniques and datadriven modeling [5,12,13,16,[21][22][23][24][25][26]. Such models are often either very specific or very general, as they are generated from data characterizing either local scale contexts at high resolutions, preventing obtaining reproducible results and to describe or predict large scale phenomena [23], or large scale contexts at low resolutions, preventing the ability to precisely describe disease transmission mechanisms [5,12,16].…”

Section: Introductionmentioning

confidence: 99%

Mapping a Knowledge-Based Malaria Hazard Index Related to Landscape Using Remote Sensing: Application to the Cross-Border Area between French Guiana and Brazil

Roux

Dessay

et al. 2016

Remote Sensing

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Malaria remains one of the most common vector-borne diseases in the world and the definition of novel control strategies can benefit from the modeling of transmission processes. However, data-driven models are often difficult to build, as data are very often incomplete, heterogeneous in nature and in quality, and/or biased. In this context, a knowledge-based approach is proposed to build a robust and general landscape-based hazard index for malaria transmission that is tailored to the Amazonian region. A partial knowledge-based model of the risk of malaria transmission in the Amazonian region, based on landscape features and extracted from a systematic literature review, was used. Spatialization of the model was obtained by generating land use and land cover maps of the cross-border area between French Guiana and Brazil, followed by computing and combining landscape metrics to build a set of normalized landscape-based hazard indices. An empirical selection of the best index was performed by comparing the indices in terms of adequacy with the knowledge-based model, intelligibility and correlation with P. falciparum incidence rates. The selected index is easy to interpret and successfully represents the current knowledge about the role played by landscape patterns in malaria transmission within the study area. It was significantly associated with P. falciparum incidence rates, using the Pearson and Spearman correlation coefficients (up to 0.79 and 0.75, respectively; p-value < 0.001), and the linear regression coefficient of determination (reaching 0.63; p-values < 0.001). This study establishes a spatial knowledge-driven, landscape-based hazard malaria index using remote sensing that can be easily produced on a regular basis and might be useful for malaria prediction, surveillance, and control.Keywords: remote sensing; land use and land cover; landscape metric; knowledge-based hazard modeling; malaria; cross-border area between French Guiana and Brazil

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“…darling because this species preferentially uses these environments for egg laying and the breeding of its larvae. This result demonstrates that climatic factors had a secondary infl uence on the result of this study (6) (7) (15) (16) . An.…”

Section: Studies Conducted Near the Itaipu Hydroelectric Plantmentioning

confidence: 57%

The influence of the area of the Serra da Mesa Hydroelectric Plant, State of Goiás, on the frequency and diversity of anophelines (Diptera: Culicidae): a study on the effect of a reservoir

Melandri

Alencar

Guimarães

2015

Rev. Soc. Bras. Med. Trop.

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Introduction: Bioecological aspects of anophelines (Diptera: Culicidae) near areas under the direct infl uence of the hydroelectric plant reservoir of Serra da Mesa in Goiás, Brazil, were analyzed. Methods: Samples were collected at the surrounding dam area during the phases before and after reservoir impoundment. The infl uence of climatic and environmental factors on the occurrence of Anopheles darlingi, Anopheles albitarsis, Anopheles triannulatus, Anopheles oswaldoi and Anopheles evansae was assessed using Pearson's correlations with indicators for richness and diversity as well as the index of species abundance (ISA) and the standardized index of species abundance (SISA). Results: The highest anopheline density occurred during the phase after fi lling the tank; however, no direct correlation with the climatic factors was observed during this stage. The reservoir formation determined the incidence of the anopheline species. An. darlingi was the predominant species (SISA = 1.00). Conclusions: The signifi cant difference (p < 0.05) observed between the species incidence during the different reservoir phases demonstrates the environmental effect of the reservoir on anophelines.

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Habitat suitability mapping of Anopheles darlingi in the surroundings of the Manso hydropower plant reservoir, Mato Grosso, Central Brazil

Cited by 42 publications

References 33 publications

Filamentous fungi associated with mosquito larvae (Diptera: Culicidae) in municipalities of the Brazilian Amazon

Filamentous fungi associated with mosquito larvae (Diptera: Culicidae) in municipalities of the Brazilian Amazon

Mapping a Knowledge-Based Malaria Hazard Index Related to Landscape Using Remote Sensing: Application to the Cross-Border Area between French Guiana and Brazil

The influence of the area of the Serra da Mesa Hydroelectric Plant, State of Goiás, on the frequency and diversity of anophelines (Diptera: Culicidae): a study on the effect of a reservoir

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