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Design and Evaluation of a Sticky Attractant Trap for Intra-Domiciliary Surveillance of Aedes aegypti Populations in Mexico.

Keila Elizabeth Paiz-MoscosoLuis Alberto Cisneros-VázquezRogelio Danís-LozanoJorge Jesús Rodríguez-RojasEduardo A Rebollar-TéllezRosa María Sanchez-CasasIldefonso Fernández-Salas
Published in: Insects (2023)
Surveillance consists of systematic data collection, analysis, and interpretation and is essential for planning and implementing control activities. The lack of success in the control and surveillance of the Ae. aegypti mosquito elsewhere demands the development of new accessible and effective strategies. This work aimed to develop and evaluate an adhesive lure trap for household indoor surveillance of Ae . aegypti . Based on a bibliographic review, four compounds that have significant attraction percentages for Ae . aegypti were considered. Our more effective blend was determined through preliminary bioassays using the high-throughput screening system (HITSS) and 90 × 90 cm mosquito cages. We designed a low-cost, pyramid-shaped, sticky cardboard trap to incorporate the selected blend. Semi-field 2 × 2 m cages and field tests were utilized to evaluate its effectiveness through mosquito capture percentages. In laboratory tests, blend number 2 presented an attraction percentage of 47.5 ± 4.8%; meanwhile, in semi-field cages, a 4-inch, 110 v powered fan was used to disperse the attractants, and then a similar capture percentage of 43.2 ± 4.0% was recorded. Results were recorded during the field evaluation of the at-house indoor environment and were compared with those recorded with the golden-standard BG-Sentinel trap, i.e., our prototype trapped an average of 6.0 ± 1.5 mosquitoes versus 10.0 ± 2.6. In most Latin American countries, there is a lack of formal and accessible strategies for monitoring adult populations of Ae . Aegypti ; therefore, we must develop tools that reinforce entomological surveillance methods.
Keyphrases
  • aedes aegypti
  • public health
  • dengue virus
  • zika virus
  • low cost
  • randomized controlled trial
  • air pollution
  • particulate matter
  • heavy metals
  • health risk
  • big data
  • drinking water