Modeling Dengue Vector Dynamics under Imperfect Detection: Three Years of Site-Occupancy by Aedes aegypti and Aedes albopictus in Urban Amazonia

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.

2 nd Brazilian Consensus on Chagas Disease, 2015

“…This approach has and will increasingly enable future improvement of the estimates of eco-epidemiological indicators and may significantly strengthen the strategies for integrated monitoring and control of vectors (70) (71) (83) (84) . The failures were observed in areas with well-established triatomine infestation, where active searches by trained and motivated agents usually detect approximately 40-60% of intradomiciliary and extradomiciliary infestation outbreaks, while undetected foci are not eliminated (70) .…”

Trypanosomatid infections in captive wild mammals and potential vectors at the Brasilia Zoo, Federal District, Brazil

“…longipalpis in Mato Grosso do Sul was higher in the wet season of the second year of sampling (Oliveira, Galati, Fernandes, Dorval, & Brazil, ). In addition, all methods for vector detection are imperfect; future sampling should consider other detection methods and analytical approaches (Padilla‐Torres, Ferraz, Luz, Zamora‐Perea, & Abad‐Franch, ;Valença‐Barbosa, Lima, Sarquis, Bezerra, & Abad‐Franch, ). We did not capture phlebotomines in the gallery forest adjacent to the zoo.…”

Modeling Disease Vector Occurrence When Detection Is Imperfect II: Drivers of Site-Occupancy by Synanthropic Triatoma brasiliensis in the Brazilian Northeast

“…We note that while multi-model inference has been used in a few studies similar to ours [32]–[34], the formal treatment of detection failures has hardly entered the vector ecology literature thus far [14], [28], [29], [35], [36]. Yet, as discussed below, standard approaches can yield biased effect-size estimates and SEs; site-occupancy models may provide a more reliable and realistic picture of key population parameters and their environmental correlates [15], [16].…”