Use of Novaluron-Based Autocidal Gravid Ovitraps to Control Aedes Dengue Vector Mosquitoes in the District of Gampaha, Sri Lanka

Improving the Safety and Acceptability of Autocidal Gravid Ovitraps (AGO Traps)

Gravid traps that collect eggs or adult mosquitoes use color, size, or volume as well as water or plant infusions as attractants. Biorational larvicides have been used to prevent these devices from producing adult mosquitoes within the traps. Results from field assays on the use of several biorational larvicides for various mosquito species have provided mixed results in terms of increased, neutral, or reduced attraction. We investigated the use of Bacillus thuringiensis var. israelensis, spinosad, and novaluron in field assays in Puerto Rico to evaluate the behavioral response of Aedes aegypti and Culex spp. to autocidal gravid ovitraps (AGO traps). The purpose of the study was to increase the safety of these traps by preventing accidental release of adult mosquitoes when traps are opened or damaged. We also investigated whether trap color (blue, green, terracotta) that may be more amenable for use by residents in their properties induced a similar attraction response to the original black trap color. We found that the use of biorational larvicides did not significantly change the behavioral attraction of these mosquito species to AGO traps. For Ae. aegypti, green traps yielded the lowest captures while black, terracotta, and blue produced similar higher yields. Culex spp. in black traps showed significantly higher captures compared with other colors. These results suggest that black, terracotta, or blue AGO traps can be used for the surveillance and control of Ae. aegypti.

Multivariate spatio-temporal approach to identify vulnerable localities in dengue risk areas using Geographic Information System (GIS)

Dengue is one of the most important vector-borne infection in Sri Lanka currently leading to vast economic and social burden. Neither a vaccine nor drug is still not being practiced, vector controlling is the best approach to control disease transmission in the country. Therefore, early warning systems are imminent requirement. The aim of the study was to develop Geographic Information System (GIS)-based multivariate analysis model to detect risk hotspots of dengue in the Gampaha District, Sri Lanka to control diseases transmission. A risk model and spatial Poisson point process model were developed using separate layers for patient incidence locations, positive breeding containers, roads, total buildings, public places, land use maps and elevation in four high risk areas in the district. Spatial correlations of each study layer with patient incidences was identified using Kernel density and Euclidean distance functions with minimum allowed distance parameter. Output files of risk model indicate that high risk localities are in close proximity to roads and coincide with vegetation coverage while the Poisson model highlighted the proximity of high intensity localities to public places and possibility of artificial reservoirs of dengue. The latter model further indicate that clustering of dengue cases in a radius of approximately 150 m in high risk areas indicating areas need intensive attention in future vector surveillances.