Memorias do Instituto Oswaldo Cruz · 2026
Reframing vector control: land use and climate shape malaria risk in Amazonian communities.
СтатьяНазвание и аннотация: Перевод в очереди
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Acosta André Luis, Bergo Eduardo Sterlino, Figueira Elder Augusto G, Conn Jan E, Sallum Maria Anice Mureb
Аннотация
BACKGROUND: Malaria remains a major public health challenge in the Brazilian Amazon, where ecological heterogeneity and socio-economic vulnerability hinder the effectiveness of vector elimination. The primary vector, Nyssorhynchus darlingi, shows substantial spatiotemporal variation influenced by land-use changes and local microclimates.
OBJECTIVES: Investigate how land cover and microclimatic factors affect Ny. darlingi human biting rate (HBR) across different Amazonian ecoregions.
METHODS: HBR was measured through human landing catches at 70 sites in four ecoregions, with simultaneous temperature and humidity recordings. Landscape composition was quantified within 100-, 250-, and 500-m buffers. Data were analyzed using linear regressions, mixed-effects models, and principal component analysis.
FINDINGS: We recorded 14,689 mosquito bites across 384 events. HBR was highest in areas with intermediate forest degradation and was positively associated with temperature and negatively with humidity. Floodable vegetation was the strongest land cover predictor, especially at the 500-m scale. Intrazonal variation exceeded interzonal differences.
MAIN CONCLUSIONS: Local environmental conditions, particularly floodable vegetation near human settlements, strongly influence Ny. darlingi activity. Vector elimination in the Amazon should adopt climate-sensitive, spatially targeted strategies informed by land cover and microclimate data.
OBJECTIVES: Investigate how land cover and microclimatic factors affect Ny. darlingi human biting rate (HBR) across different Amazonian ecoregions.
METHODS: HBR was measured through human landing catches at 70 sites in four ecoregions, with simultaneous temperature and humidity recordings. Landscape composition was quantified within 100-, 250-, and 500-m buffers. Data were analyzed using linear regressions, mixed-effects models, and principal component analysis.
FINDINGS: We recorded 14,689 mosquito bites across 384 events. HBR was highest in areas with intermediate forest degradation and was positively associated with temperature and negatively with humidity. Floodable vegetation was the strongest land cover predictor, especially at the 500-m scale. Intrazonal variation exceeded interzonal differences.
MAIN CONCLUSIONS: Local environmental conditions, particularly floodable vegetation near human settlements, strongly influence Ny. darlingi activity. Vector elimination in the Amazon should adopt climate-sensitive, spatially targeted strategies informed by land cover and microclimate data.