Please use this identifier to cite or link to this item: https://www.arca.fiocruz.br/handle/icict/18017
Title: Meteorological variables and mosquito monitoring are good predictors for infestation trends of Aedes aegypti, the vector of dengue, chikungunya and Zika
Authors: Ferreira, Danielle Andreza da Cruz
Degener, Carolin Marlen
Toledo, Cecilia de Almeida Marques
Bendati, Maria Mercedes
Fetzer, Liane Oliveira
Teixeira, Camila P.
Eiras, Álvaro Eduardo
Affilliation: Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Parasitologia. Belo Horizonte, MG, Brasil.
Fundação Oswaldo Cruz. Programa de Computação Científica. Rio de Janeiro, RJ, Brasil.
Parque Tecnológico de Belo Horizonte (BHTec). Ecovec Ltda. Belo Horizonte, Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. ICB. Departamento de Bioquímica e Imunologia. Belo Horizonte, MG, Brasil.
CGVS/6SMS. Vigilância de Roedores e Vetores. Porto Alegre, RS, Brasil.
CGVS/6SMS. Vigilância de Roedores e Vetores. Porto Alegre, RS, Brasil.
UNIFEMM. Sete Lagoas, MG, Brasil.
Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Parasitologia. Belo Horizonte, MG, Brasil.
Abstract: Background: Aedes aegypti is an important vector for arboviroses and widely distributed throughout the world. Climatic factors can influence vector population dynamics and, consequently, disease transmission. The aim of this study was to characterize the temporal dynamics of an Ae. aegypti population and dengue cases and to investigate the relationship between meteorological variables and mosquito infestation. Methods: We monitored and analyzed the adult female Ae. aegypti population, the dengue-fever vector, in Porto Alegre, a subtropical city in Brazil using the MI-Dengue system (intelligent dengue monitoring). This system uses sticky traps to monitor weekly infestation indices. We fitted generalized additive models (GAM) with climate variables including precipitation, temperature and humidity, and a GAM that additionally included mosquito abundance in the previous week as an explanatory variable. Logistic regression was used to evaluate the effect of adult mosquito infestation on the probability of dengue occurrence. Results: Adult mosquito abundance was strongly seasonal, with low infestation indices during the winters and high infestation during the summers. Weekly minimum temperatures above 18 °C were strongly associated with increased mosquito abundance, whereas humidity above 75% had a negative effect on abundance. The GAM model that included adult mosquito infestation in the previous week adjusted and predicted the observed data much better than the model which included only meteorological predictor variables. Dengue was also seasonal and 98% of all cases occurred at times of high adult Ae. aegypti infestation. The probability of dengue occurrence increased by 25%, when the mean number of adult mosquitos caught by monitoring traps increased by 0.1 mosquitoes per week. Conclusions: The results suggest that continuous monitoring of dengue vector population allows for more reliable predictions of infestation indices. The adult mosquito infestation index was a good predictor of dengue occurrence. Weekly adult dengue vector monitoring is a helpful dengue control strategy in subtropical Brazilian cities.
Keywords: Aedes aegypti
Dengue
Surveillance
MosquiTRAP
keywords: Aedes aegypti
Dengue
Vigilância
Mosquito
DeCS: Aedes
Dengue
Vigilância Epidemiológica
Issue Date: 2017
Publisher: CrossMark
Citation: FERREIRA, Danielle Andreza da Cruz et al. Meteorological variables and mosquito monitoring are good predictors for infestation trends of Aedes aegypti, the vector of dengue, chikungunya and Zika. Parasites & Vectors, v.10, n.78, p.1-11, 2017.
Description: DACF, CMD, and AEE received fellowships from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and FAPEMIG (Fundação de Amparo a Pesquisa do Estado de Minas Gerais). This project was funded by CNPq/DECIT-MS (Grant # 404211/2012-7), and CAPES (Grant # 3048–2011).
ISSN: 1756-3305
Copyright: open access
Appears in Collections:Presidência Fiocruz – Artigos de Periódicos

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