Abstract
Aedes aegypti and Ae. albopictus are the vectors of dengue, the most important arboviral disease of humans. To date, Aedes ecology studies have assumed that the vectors are truly absent from sites where they are not detected; since no perfect detection method exists, this assumption is questionable. Imperfect detection may bias estimates of key vector surveillance/control parameters, including site-occupancy (infestation) rates and control intervention effects. We used a modeling approach that explicitly accounts for imperfect detection and a 38-month, 55-site detection/non-detection dataset to quantify the effects of municipality/state control interventions on Aedes site-occupancy dynamics, considering meteorological and dwelling-level covariates. Ae. aegypti site-occupancy estimates (mean 0.91; range 0.79–0.97) were much higher than reported by routine surveillance based on ‘rapid larval surveys’ (0.03; 0.02–0.11) and moderately higher than directly ascertained with oviposition traps (0.68; 0.50–0.91). Regular control campaigns based on breeding-site elimination had no measurable effects on the probabilities of dwelling infestation by dengue vectors. Site-occupancy fluctuated seasonally, mainly due to the negative effects of high maximum (Ae. aegypti) and minimum (Ae. albopictus) summer temperatures (June-September). Rainfall and dwelling-level covariates were poor predictors of occupancy. The marked contrast between our estimates of adult vector presence and the results from ‘rapid larval surveys’ suggests, together with the lack of effect of local control campaigns on infestation, that many Aedes breeding sites were overlooked by vector control agents in our study setting. Better sampling strategies are urgently needed, particularly for the reliable assessment of infestation rates in the context of control program management. The approach we present here, combining oviposition traps and site-occupancy models, could greatly contribute to that crucial aim.
Highlights
Dengue is the most common arboviral disease of humans [1,2,3]
Aedes aegypti detection/non-detection data are best explained by a model with just one covariate on y, the average of maximum daily temperatures measured with a 2-week-lag, which had a negative effect on site-occupancy (Table 1)
The second-ranking model is substantially supported by the data (DAICc = 0.73); it includes the additive effects of tmax-2-week-lag and control interventions carried out during the same month on y
Summary
Dengue is the most common arboviral disease of humans [1,2,3]. About 50 million people contract dengue annually, and an estimated 22,000 die from severe forms of the disease [3,4]. In the absence of effective drugs or vaccines, prevention of dengue infections and severe dengue forms heavily relies upon vector control. Despite massive spending and some encouraging results (e.g., [6,7,8,9]), neither vector populations nor, dengue transmission are currently under control; on the contrary, they are both clearly expanding [2,10]. In South America, dengue incidence increased from ,16/100,000 population in the 1980s to ,72/ 100,000 in 2000–2007 [11]
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