Meteorological variables and mosquito monitoring are good predictors for infestation trends of Aedes aegypti, the vector of dengue, chikungunya and Zika

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.MethodsWe 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.ResultsAdult 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-017-2025-8) contains supplementary material, which is available to authorized users.

Arbovirus Vectors of Epidemiological Concern in the Americas: A Scoping Review of Entomological Studies on Zika, Dengue and Chikungunya Virus Vectors

“…albopictus early in the wet season, and that interspecific mosquito crowding was highest one kilometer from the coast [17]. Degener et al [18], Lucio et al [19], Da Cruz Ferreira et al [20] and Regis et al [21] studied the impact of meteorological variables on Ae. aegypti infestation levels in South America.…”

Travel-related Zika virus cases in Canada: October 2015–June 2017

“…The peak in cases recorded in July and August of 2016 was due to increases in cases exposed in Central America and the Caribbean, and to some extent from Mexico, but at a time when travel to these destinations are typically at their seasonal lows. Climatic factors such as temperature, humidity and precipitation have been shown to affect vector abundance, and ultimately level of disease transmission for diseases such dengue and chikungunya (33), resulting in seasonal trends in transmission favouring the warmer, wetter months. Both outbreak intensity and seasonality of ZIKV transmission should be monitored over time in order to inform the timing of public health education campaigns, as some may turn out be more effective in the 'off-peak' travel season when, despite lower absolute travel volumes, the risk of disease transmission may be higher.…”

Inferring the ecological drivers of arboviral outbreaks

“…Elevated precipitation and humidity levels have also been shown to correlate with arboviral outbreaks by creating additional mosquito breeding sites and decreasing mosquito mortality, respectively Hu et al, 2006;Li et al, 1985;Messina et al, 2016;Scott et al, 2000). However the exact relationships between these climate factors and vector suitability are often disputed and have yet to be rigorously established within in the field (Alto and Juliano, 2001;Canyon et al, 2013;Da Cruz Ferreira et al, 2017;Descloux et al, 2012;Naish et al, 2014).…”