ArticleMemorias do Instituto Oswaldo Cruz2024
Characterization of larval habitats of Anopheles (Nyssorhynchus) darlingi and associated species in malaria areas in western Brazilian Amazon.
Article in Memorias do Instituto Oswaldo Cruz, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Larvicidal Potential ofPharmaceuticals (Basel, Switzerland) · 2025Article
- Distribution of Anophelinae (Diptera: Culicidae) and challenges for malaria elimination in Brazil.Memorias do Instituto Oswaldo Cruz · 2025Article
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Authors and funding
5 authors.
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Abstract
backgroundAnopheles darlingi is the most efficient vector of malaria parasites in the Neotropics. Nevertheless, the specificities of its larval habitats are still poorly known.
objectivesCharacterize permanent larval habitats, and population dynamics of An. darlingi and other potential vectors in relation to climate, physicochemical variables, insect fauna and malaria cases.
methodsA 14-month longitudinal study was conducted in Porto Velho, Rondônia, western Brazilian Amazon. Monthly, 21 permanent water bodies were sampled. Immature anophelines and associated fauna were collected, physicochemical characteristics, and climate variables were recorded and analyzed.
findingsFive types of habitats were identified: lagoon, stream, stream combined with lagoon, stream combined with dam, and fishpond. A total of 60,927 anophelines were collected. The most abundant species in all habitats were Anopheles braziliensis and An. darlingi. The highest density was found in the lagoon, while streams had the highest species richness. Abundance was higher during the transition period wet-dry season. There was a lag of respectively four and five months between the peak of rainfall and the Madeira River level and the highest abundance of An. darlingi larvae, which were positively correlated with habitats partially shaded, pH close to neutrality, increase dissolved oxygen and sulphates. MAIN
conclusionsThe present study provides data on key factors defining permanent larval habitats for the surveillance of An. darlingi and other potential vectors as well as a log-linear Negative Binomial model based on immature mosquito abundance and climate variables to predict the increase in the number of malaria cases.
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