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1.
Acta Trop ; 205: 105391, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32057775

RESUMO

Rapid larval surveys have been mandated in nearly every urban Brazilian municipality and promoted by the Pan American Health Organization. These surveys purport to classify arbovirus transmission risk as a basis to triage local surveillance and vector control operations, yet no previous analyses have determined relative risk associated with marginal changes in infestation at administrative and temporal scales relevant to vector control. We estimated associations between entomological indices from six larval surveys and daily incidence rates of confirmed dengue cases in Fortaleza, Brazil using models adjusted for rainfall, and indicators of spatial association. Poor correspondence between infestation and incidence indicates that these surveys may systematically mislead vector control activities and treatment strategies in Fortaleza and in similar cities throughout Latin America. The co-circulation of multiple arboviruses enhances the importance of determining the true informational value of these surveys, and of identifying complementary tools to discern local and inter-annual transmission risk.


Assuntos
Aedes/virologia , Dengue/transmissão , Mosquitos Vetores/virologia , Animais , Brasil/epidemiologia , Dengue/epidemiologia , Humanos , Larva/virologia , Estações do Ano , Inquéritos e Questionários , Fatores de Tempo
2.
Rev. Soc. Bras. Med. Trop ; Rev. Soc. Bras. Med. Trop;51(1): 71-76, Jan.-Feb. 2018. tab, graf
Artigo em Inglês | LILACS | ID: biblio-1041446

RESUMO

Abstract INTRODUCTION: the Building Infestation Index (BII) uses the Rapid Assay of the Larval Index for Aedes aegypti (LIRAa) to express the relationship between positive and surveyed properties. We evaluated LIRAa and the relationship between the BII and climate variables for dengue cases in Foz do Iguaçu municipality, Paraná. METHODS: Spearman's correlations for mean precipitation, mean temperature, BII, and dengue cases (time lag). RESULTS: positive correlations between BII and cases, and mean temperature and cases at two months. Weak correlation between precipitation and cases at three months. CONCLUSIONS: LIRAa and climate variables correlate with dengue cases.


Assuntos
Humanos , Animais , Aedes/virologia , Dengue/epidemiologia , Insetos Vetores/virologia , Estações do Ano , População Urbana , Brasil/epidemiologia , Densidade Demográfica , Aedes/classificação , Dengue/transmissão , Insetos Vetores/classificação
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