Distinct variation in vector competence among nine field populations of Aedes aegypti from a Brazilian dengue-endemic risk city

Abstract

BackgroundIn Brazil, dengue epidemics erupt sporadically throughout the country and it is unclear if outbreaks may initiate a sustainable transmission cycle. There are few studies evaluating the ability of Brazilian Aedes aegypti populations to transmit dengue virus (DENV). The aim of this study was to compare DENV susceptibility of field-captured Ae. aegypti populations from nine distinct geographic areas of the city of Belo Horizonte in 2009 and 2011. Infection Rate (IR), Vector Competence (VC) and Disseminated Infection Rate (DIR) were determined.MethodsAedes aegypti eggs from each region were collected and reared separately in an insectary. Adult females were experimentally infected with DENV-2 and the virus was detected by qPCR in body and head samples. Data were analyzed with the Statistical Package for the Social Sciences version 17.ResultsIR varied from 40.0% to 82.5% in 2009 and 60.0% to 100.0% in 2011. VC ranged from 25.0% to 77.5% in 2009 and 25.0% to 80.0% in 2011. DIR oscillated from 68.7% to 100.0% in 2009 and 38.4% to 86.8 in 2011. When the results were evaluated by a logistic model using IR as covariate, North, Barreiro, South-Central and Venda Nova showed the strongest association in 2009. In 2011, a similar association was observed for South-Central, Venda Nova, West and Northeast regions. Using VC as covariate, South-Central and Venda Nova showed the most relevant association in 2009. In 2011, South-Central, Venda Nova and Barreiro presented the greatest revelation associations. When DIR data were analyzed by logistic regression models, Pampulha, South-Central, Venda Nova, West, Northeast and East (2009) as well as South-Central, Venda Nova and West (2011) were the districts showing the strongest associations.ConclusionsWe conclude that Ae. aegypti populations from Belo Horizonte exhibit wide variation in vector competence to transmit dengue. Therefore, vector control strategies should be adapted to the available data for each region. Further analysis should be conducted to better understand the reasons for this large variability in vector competence and how these parameters correlate with epidemiological findings in subsequent years.

Aedes ( Stegomyia ) albopictus ’ dynamics influenced by spatiotemporal characteristics in a Brazilian dengue-endemic risk city

“…All individual field-caught mosquitoes classified as Ae. albopictus were checked for their GPS-district location, quantified, visually checked for absence of blood meal under stereoscope and analyzed for DENV infection (Gonçalves et al, 2014). …”

“…albopictus were carefully re-checked under a stereoscope to confirm the species identification and the absence of blood meal. RNA extraction and DENV detection by real-time RT-PCR were conducted as previously reported (Gonçalves et al, 2014). In brief, whole bodies of field-caught Ae.…”

“…All analyses were performed in duplicate and in parallel with standardized samples (to provide standard curves), positive controls and negative controls. Results indicative of DENV presence in each mosquito were obtained as previously described (Gonçalves et al, 2014) using a standard curve and analyzing the melting curve for specificity of the amplified products (melting point ∼78.6 °C) and CT of 35, according to rigorous criteria from literature for The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) (Bennett et al, 2002). …”

Abbreviations and acronyms

“…aegypti is also a vector of Wuchereria bancrofti and Brugia malayi, both of which cause lymphatic filariasis or elephantiasis (Service, 2012; Consequently, Ae. aegypti has been the subject of numerous vector competence and population genetic studies (Aitken, Downs and Shope, 1977;Gubler et al, 1979;Tabachnick and Powell, 1979;Rosen et al, 1985;Tabachnick et al, 1985;Tardieux et al, 1990;Miller and Mitchell, 1991;Apostol, Reiter and Miller, 1996;Bosio and Beaty, 1998;Vazeille-Falcoz et al, 1999;Bosio, Fulton and Salasek, 2000;Bennett et al, 2002b;Gorrochotegui-Escalante et al, 2002;Mercado-Curiel, Black and Muñoz, 2008;Lozano-Fuentes et al, 2009;Sylla et al, 2009;Lambrechts, 2011;Lambrechts et al, 2011;Guo et al, 2013;Muñoz et al, 2013b;Chepkorir et al, 2014;Diagne et al, 2014;Dickson et al, 2014;Gonçalves et al, 2014;Vega-Rúa et al, 2014).…”

“…All in all, they indicate that vector control strategies should be adapted to the available data for each region. Further analysis should be conducted to better understand the reasons for this large variability in VC and how these parameters correlate with epidemiological findings (Gonçalves et al, 2014).…”